Updated on 2021/10/21

写真a

 
FUJIWARA Koichi
 
Organization
Institute for Advanced Research Associate professor
Graduate School of Engineering Associate professor
Graduate School
Graduate School of Engineering
Undergraduate School
School of Engineering Materials Science and Engineering
Title
Associate professor

Degree 1

  1. 博士(工学) ( 2009.3   京都大学 ) 

Research Interests 12

  1. Epileptology

  2. Sleep Medicine

  3. Biosignal Processing

  4. Machine Learning

  5. Biomedical Engineering

  6. Process Systems Engineering

  7. Process Systems Engineering

  8. Sleep Medicine

  9. Epileptology

  10. Biomedical Engineering

  11. Biosignal Processing

  12. Machine Learning

Research Areas 4

  1. Informatics / Life, health and medical informatics

  2. Life Science / Medical systems

  3. Informatics / Statistical science

  4. Manufacturing Technology (Mechanical Engineering, Electrical and Electronic Engineering, Chemical Engineering) / Chemical reaction and process system engineering

Current Research Project and SDGs 6

  1. てんかん発作予知AIの開発

  2. 認知症の早期診断

  3. 睡眠障害の診断

  4. 熱中症アラームの開発

  5. 生産プロセスの異常検知・診断AIの開発

  6. 心不全の早期検知

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Research History 7

  1. Nagoya University   Department of Material Process Engineering   Associate professor

    2018.11

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    Country:Japan

  2. JST

    2018.10

  3. Kyoto University   Department of Systems Science   Assistant Professor

    2012.7 - 2018.11

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    Country:Japan

  4. NTT Communication Science Laboratories

    2010.4 - 2012.6

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    Country:Japan

  5. Research Fellowships for Young Scientists   PD

    2009.4 - 2010.3

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    Country:Japan

  6. Research Fellowships for Young Scientists   DC2

    2008.4 - 2009.3

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    Country:Japan

  7. Toyota Motor Corporation

    2006.4 - 2007.3

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    Country:Japan

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Education 3

  1. Kyoto University   Graduate School, Division of Engineering   Department of Chemical Engineering

    2007.4 - 2009.3

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    Country: Japan

  2. Kyoto University   Graduate School, Division of Engineering   Department of Chemical Engineering

    2004.4 - 2006.3

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    Country: Japan

  3. Kyoto University   Faculty of Engineering

    2000.4 - 2004.3

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    Country: Japan

Professional Memberships 7

  1. IEEE

  2. THE JAPANESE SOCIETY FOR ARTIFICIAL INTELLIGENCE

  3. THE SOCIETY OF INSTRUMENT AND CONTROL ENGINEERS

  4. JAPAN EPILEPSY SOCIETY

  5. THE JAPANESE SOCIETY OF SLEEP RESEARCH

  6. THE SOCIETY OF CHEMICAL ENGINEERS, JAPAN

  7. APSIPA

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Committee Memberships 10

  1. APSIAP   BioSiPS Technical Committee Chair  

    2021.1   

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    Committee type:Academic society

  2.   APSIPA BioSips Technical Committee Chair  

    2021.1   

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    Committee type:Academic society

  3. International Journal of Environmental Research and Public Health   Special Issue Chief Editor  

    2020.6   

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    Committee type:Academic society

  4.   International Journal of Environmental Research and Public Health Special Chief Editor  

    2020.6   

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    Committee type:Academic society

  5. Frontiers in ICT   Special Issue Chief Editor  

    2019.8   

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    Committee type:Academic society

  6. Frontiers   Special Issue Chief Editor  

    2019.6   

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    Committee type:Academic society

  7. 三菱総研厚労省委託事業   センサ情報を用いた介護認定の客観化に係る検討会・委員  

    2017.10 - 2018.3   

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    Committee type:Other

  8. 日本睡眠学会   若手の会幹事  

    2017.1   

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    Committee type:Academic society

  9. APSIPA BioSips   Technical Committee  

    2013.10   

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    Committee type:Academic society

  10. 日本学術振興会   第143委員会  

    2012.10   

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    Committee type:Academic society

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Awards 19

  1. テレコムシステム技術賞

    2021.3   電気通信普及財団  

  2. 支部賞

    2021.1   計測自動制御学会 中部支部  

  3. 学術年会 優秀研究発表賞

    2020.6   日本毒性学会  

  4. 全国大会優秀賞

    2018.11   人工知能学会  

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    Award type:Award from Japanese society, conference, symposium, etc. 

  5. システム・情報部門 学術講演会 2018 優秀発表賞

    2018.11   計測自動制御学会  

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    Award type:Award from Japanese society, conference, symposium, etc.  Country:Japan

  6. システム・情報部門 学術講演会 2018 優秀論文賞

    2018.11   計測自動制御学会  

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    Award type:Award from Japanese society, conference, symposium, etc.  Country:Japan

  7. システム・情報部門 学術講演会 2018 優秀発表賞

    2018.11   計測自動制御学会  

    藤原 幸一

  8. システム・情報部門 学術講演会 2018 優秀論文賞

    2018.11   計測自動制御学会  

    藤原 幸一

  9. BRAVE 2017 Winter 優秀賞

    2017.12   Beyond Next Ventures  

    藤原 幸一

  10. システム・情報部門 学術講演会 2017 最優秀論文賞

    2017.11   計測自動制御学会  

    藤原 幸一

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    Award type:Award from Japanese society, conference, symposium, etc. 

  11. 論文賞

    2017.9   計測自動制御学会  

    藤原 幸一

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    Award type:Honored in official journal of a scientific society, scientific journal 

  12. バイオテックグランプリ・サントリー賞

    2017.9   リバネス  

    藤原 幸一

  13. 市村学術賞 功績賞

    2017.4   新技術開発財団  

    藤原 幸一

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    Award type:International academic award (Japan or overseas) 

  14. 技術賞

    2016.9   計測自動制御学会  

    藤原 幸一

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    Award type:Honored in official journal of a scientific society, scientific journal 

  15. システム・情報部門 学術講演会 2015 優秀論文賞

    2015.11   計測自動制御学会  

    藤原 幸一

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    Award type:Award from Japanese society, conference, symposium, etc. 

  16. 第1回制御部門マルチシンポジウム 部門大会賞

    2015.3   計測自動制御学会  

    藤原 幸一

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    Award type:Award from Japanese society, conference, symposium, etc. 

  17. システム・情報部門 学術講演会 2014 奨励賞

    2014.11   計測自動制御学会  

    藤原 幸一

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    Award type:Award from Japanese society, conference, symposium, etc. 

  18. システム・情報部門 学術講演会 2014 優秀論文賞

    2014.11   計測自動制御学会  

    藤原 幸一

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    Award type:Award from Japanese society, conference, symposium, etc. 

  19. 奨励賞

    2012.10   計測自動制御学会関西支部  

    藤原 幸一

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Papers 107

  1. Prediction of GABA receptor antagonist-induced convulsion in cynomolgus monkeys by combining machine learning and heart rate variability analysis. Reviewed

    Nagata S, Fujiwara K, Kuga K, Ozaki H

    Journal of pharmacological and toxicological methods   Vol. 112   page: 107127   2021.10

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    Language:English   Publishing type:Research paper (scientific journal)  

    DOI: 10.1016/j.vascn.2021.107127

    PubMed

  2. Measurement and analysis technology using wearable system for prediction of autonomic change related to neurological symptoms and health condition Reviewed

    YAMAKAWA Toshitaka, FUJIWARA Koich, KANO Manabu, MIYAJIMA Miho, MAEHARA Taketoshi

    Annual Meeting of the Japanese Society of Toxicology   Vol. 48 ( 0 ) page: S8 - 4   2021

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    Language:Japanese   Publishing type:Research paper (scientific journal)   Publisher:The Japanese Society of Toxicology  

    <p>Heart rate variability (HRV) reflects autonomic nerve activity and provides beneficial information for both clinical and healthcare diagnoses. A telemetry system for the measurement of HRV has been developed with a low-cost manufacturing process and a low-power consumption design. All the components and functions for the measurement were implemented on a wearable telemeter that has a function for automated calibration of various ECG amplitudes among the subjects, and the obtained data is stored into a smartphone via a Bluetooth wireless transmission. The measurement accuracy and reliability of the system are reviewed in this talk, and the preliminary results of the application to the clinical and healthcare purposes: the prediction of epileptic seizures and drowsy driving are explained.</p>

    DOI: 10.14869/toxpt.48.1.0_S8-4

    CiNii Article

  3. Research on Human Resource Development that Contributes to Technological Innovation and International Competitiveness in Artificial Intelligence for Healthcare Reviewed

    OKUMURA TAKASHI, ANDO YUICHI, FUKUDA TAKASHI, NAKAMURA MOTONORI, KAMITANI TATSUO, OKAMOTO ETSUJI, KIMURA SHINJI, KAMEDA YOSHIHITO, FUJIWARA KOICHI

    Japan Journal of Medical Informatics   Vol. 40 ( 1 ) page: 16 - 17   2020

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    Language:Japanese   Publishing type:Research paper (scientific journal)   Publisher:Japan Association for Medical Informatics  

    DOI: 10.14948/jami.40.16

    CiNii Article

  4. 埋込サイボーグ技術の社会実装に係る技術・ 社会的課題 Invited

    藤原幸一, 藤田卓仙, 山川俊貴, 久保孝富, 日永田智絵, 桐山瑶子, 川島浩誉, 川治徹真, 野田隼人, 田畑淳

    人工知能   Vol. 36 ( 6 ) page: 674 - 683   2021.11

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    Authorship:Lead author, Corresponding author   Language:Japanese   Publishing type:Research paper (scientific journal)  

  5. Autoencoder-Based Extrasystole Detection and Modification of RRI Data for Precise Heart Rate Variability Analysis Reviewed

    Koichi Fujiwara, Shota Miyatani, Asuka Goda, Miho Miyajima, Tetsuo Sasano, Manabu Kano

    Sensors   Vol. 21 ( 9 ) page: 3235 - 3235   2021.5

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:MDPI AG  

    Heart rate variability, which is the fluctuation of the R-R interval (RRI) in electrocardiograms (ECG), has been widely adopted for autonomous evaluation. Since the HRV features that are extracted from RRI data easily fluctuate when arrhythmia occurs, RRI data with arrhythmia need to be modified appropriately before HRV analysis. In this study, we consider two types of extrasystoles—premature ventricular contraction (PVC) and premature atrial contraction (PAC)—which are types of extrasystoles that occur every day, even in healthy persons who have no cardiovascular diseases. A unified framework for ectopic RRI detection and a modification algorithm that utilizes an autoencoder (AE) type of neural network is proposed. The proposed framework consists of extrasystole occurrence detection from the RRI data and modification, whose targets are PVC and PAC. The RRI data are monitored by means of the AE in real time in the detection phase, and a denoising autoencoder (DAE) modifies the ectopic RRI caused by the detected extrasystole. These are referred to as AE-based extrasystole detection (AED) and DAE-based extrasystole modification (DAEM), respectively. The proposed framework was applied to real RRI data with PVC and PAC. The result showed that AED achieved a sensitivity of 93% and a false positive rate of 0.08 times per hour. The root mean squared error of the modified RRI decreased to 31% in PVC and 73% in PAC from the original RRI data by DAEM. In addition, the proposed framework was validated through application to a clinical epileptic seizure problem, which showed that it correctly suppressed the false positives caused by PVC. Thus, the proposed framework can contribute to realizing accurate HRV-based health monitoring and medical sensing systems.

    DOI: 10.3390/s21093235

  6. Sympathetic hyperactivity, hypertension, and tachycardia induced by stimulation of the ponto-medullary junction in humans. Reviewed

    Hamasaki T, Yamakawa T, Fujiwara K, Harashima H, Nakamura K, Ikuta Y, Yamamoto T, Hasegawa Y, Takezaki T, Mukasa A

    Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology     2021.3

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    Publishing type:Research paper (scientific journal)  

    DOI: 10.1016/j.clinph.2021.03.006

    PubMed

  7. Synthesis of deuterated γ-linolenic acid and application for biological studies: metabolic tuning and Raman imaging. Reviewed

    Dodo K, Sato A, Tamura Y, Egoshi S, Fujiwara K, Oonuma K, Nakao S, Terayama N, Sodeoka M

    Chemical communications (Cambridge, England)   Vol. 57 ( 17 ) page: 2180 - 2183   2021.3

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    Publishing type:Research paper (scientific journal)  

    DOI: 10.1039/d0cc07824g

    PubMed

  8. Sympathetic hyperactivity, hypertension, and tachycardia induced by stimulation of the ponto-medullary junction in humans Reviewed

    T. Hamasaki, T. Yamakawa, K. Fujiwara, H. Harashima, K. Nakamura, Y. Ikuta, T. Yamamoto, Y. Hasegawa, T. Takezaki, A. Mukasa

    Clinical Neurophysiology     2021.3

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    Language:English   Publishing type:Research paper (scientific journal)  

  9. Synthesis of Resolvin E1 and Its Conformationally Restricted Cyclopropane Congeners with Potent Anti-Inflammatory Effect. Reviewed

    Ishimura K, Fukuda H, Fujiwara K, Muromoto R, Hirashima K, Murakami Y, Watanabe M, Ishihara J, Matsuda T, Shuto S

    ACS medicinal chemistry letters   Vol. 12 ( 2 ) page: 256 - 261   2021.2

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    Publishing type:Research paper (scientific journal)  

    DOI: 10.1021/acsmedchemlett.0c00639

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  10. Work habit-related sleep debt; insights from factor identification analysis of actigraphy data Invited Reviewed International journal

      Vol. 10   page: 630640   2021.2

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    Authorship:Corresponding author   Language:English   Publishing type:Research paper (scientific journal)  

    The present study investigates the factors of "Weekday sleep debt (WSD)" by comparing activity data collected from persons with and without WSD. Since it has been reported that the amount of sleep debt as well the difference between the social clock and the biological clock is associated with WSD, specifying the factors of WSD other than chronotype may contribute to sleep debt prevention. We recruited 324 healthy male employees working at the same company and collected their one-week wrist actigraphy data and answers to questionnaires. Because 106 participants were excluded due to measurement failure of the actigraphy data, the remaining 218 participants were included in the analysis. All participants were classified into WSD or non-WSD groups, in which persons had WDS if the difference between their weekend sleep duration and the mean weekday sleep duration was more than 120 min. We evaluated multiple measurements derived from the collected actigraphy data and trained a classifier that predicts the presence of WSD using these measurements. A support vector machine (SVM) was adopted as the classifier. In addition, to evaluate the contribution of each indicator to WSD, permutation feature importance was calculated based on the trained classifier. Our analysis results showed significant importance of the following three out of the tested 32 factors: 1) WSD was significantly related to persons with evening tendency. 2) Daily activity rhythms and sleep were less stable in the WSD group than in the non-WSD group. 3) A specific day of the week had the highest importance in our data, suggesting that work habit contributes to WSD. These findings indicate some WSD factors: evening chronotype, instability of the daily activity rhythm, and differences in work habits on the specific day of the week. Thus, it is necessary to evaluate the rhythms of diurnal activities as well as sleep conditions to identify the WSD factors. In particular, the diurnal activity rhythm influences WSD. It is suggested that proper management of activity rhythm may contribute to the prevention of sleep debt.

    DOI: 10.3389/fpubh.2021.630640

    PubMed

  11. Screening of sleep apnea based on heart rate variability and long short-term memory Reviewed International journal

    Ayako Iwasaki, Chikao Nakayama, Koichi Fujiwara, Yukiyoshi Sumi, Masahiro Matsuo, Manabu Kano, Hiroshi Kadotani

    Sleep and Breathing     2021.1

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:Springer Science and Business Media LLC  

    <title>Abstract</title><sec>
    <title>Purpose</title>
    Sleep apnea syndrome (SAS) is a prevalent sleep disorder in which apnea and hypopnea occur frequently during sleep and result in increase of the risk of lifestyle-related disease development as well as daytime sleepiness. Although SAS is a common sleep disorder, most patients remain undiagnosed because the gold standard test polysomnography (PSG), is high-cost and unavailable in many hospitals. Thus, an SAS screening system that can be used easily at home is needed.


    </sec><sec>
    <title>Methods</title>
    Apnea during sleep affects changes in the autonomic nervous function, which causes fluctuation of the heart rate. In this study, we propose a new SAS screening method that combines heart rate measurement and long short-term memory (LSTM) which is a type of recurrent neural network (RNN). We analyzed the data of intervals between adjacent R waves (R-R interval; RRI) on the electrocardiogram (ECG) records, and used an LSTM model whose inputs are the RRI data is trained to discriminate the respiratory condition during sleep.


    </sec><sec>
    <title>Results</title>
    The application of the proposed method to clinical data showed that it distinguished between patients with moderate-to-severe SAS with a sensitivity of 100% and specificity of 100%, results which are superior to any other existing SAS screening methods.


    </sec><sec>
    <title>Conclusion</title>
    Since the RRI data can be easily measured by means of wearable heart rate sensors, our method may prove to be useful as an SAS screening system at home.


    </sec>

    DOI: 10.1007/s11325-020-02249-0

    PubMed

    Other Link: http://link.springer.com/article/10.1007/s11325-020-02249-0/fulltext.html

  12. Synthesis of Resolvin E3, a Proresolving Lipid Mediator, and Its Deoxy Derivatives: Identification of 18-Deoxy-resolvin E3 as a Potent Anti-Inflammatory Agent. Reviewed

    Fukuda H, Ikeda H, Muromoto R, Hirashima K, Ishimura K, Fujiwara K, Aoki-Saito H, Hisada T, Watanabe M, Ishihara J, Matsuda T, Shuto S

    The Journal of organic chemistry   Vol. 85 ( 21 ) page: 14190 - 14200   2020.11

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    Publishing type:Research paper (scientific journal)  

    DOI: 10.1021/acs.joc.0c01701

    PubMed

  13. Auditory Feedback of False Heart Rate for Video Game Experience Improvement Reviewed International journal

    Sayaka Ogawa, Koichi Fujiwara, Manabu Kano

    IEEE Transactions on Affective Computing     page: 1 - 1   2020.11

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    Authorship:Corresponding author   Language:English   Publishing type:Research paper (scientific journal)   Publisher:Institute of Electrical and Electronics Engineers (IEEE)  

    DOI: 10.1109/taffc.2020.3039874

  14. Optimal Design of Neuroprotective Focal Brain Cooling Device Using Surrogate Model Approach Reviewed International journal

    Takuto Abe, Koichi Fujiwara, Takao Inoue, Takatomi Kubo, Toshitaka Yamakawa, Sadahiro Nomura, Michiyasu Suzuki, Manabu Kano

    IEEE Transactions on Medical Robotics and Bionics   Vol. 2 ( 4 ) page: 681 - 691   2020.11

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    Authorship:Corresponding author   Language:English   Publishing type:Research paper (scientific journal)   Publisher:Institute of Electrical and Electronics Engineers (IEEE)  

    DOI: 10.1109/tmrb.2020.3020687

  15. Resting Heart Rate Variability Is Associated With Subsequent Orthostatic Hypotension: Comparison Between Healthy Older People and Patients With Rapid Eye Movement Sleep Behavior Disorder Reviewed International journal

    Y. Sumi, C. Nakayama, H. Kadotani, M. Matsuo, Y. Ozeki, T. Kinoshita, Y. Goto, M. Kano, T. Yamakawa, M. Ohira, K. Ogawa, K. Fujiwara

    Frontiers in Neurology   Vol. 11   page: 567984   2020.11

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    Authorship:Last author   Language:English   Publishing type:Research paper (scientific journal)  

    DOI: 10.3389/fpubh.2020.00178

  16. Wearable Epileptic Seizure Prediction System with Machine-Learning-Based Anomaly Detection of Heart Rate Variability Reviewed International journal

    Toshitaka Yamakawa, Miho Miyajima, Koichi Fujiwara, Manabu Kano, Yoko Suzuki, Yutaka Watanabe, Satsuki Watanabe, Tohru Hoshida, Motoki Inaji, Taketoshi Maehara

    Sensors   Vol. 20 ( 14 ) page: 3987 - 3987   2020.7

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:MDPI AG  

    A warning prior to seizure onset can help improve the quality of life for epilepsy patients. The feasibility of a wearable system for predicting epileptic seizures using anomaly detection based on machine learning is evaluated. An original telemeter is developed for continuous measurement of R-R intervals derived from an electrocardiogram. A bespoke smartphone app calculates the indices of heart rate variability in real time from the R-R intervals, and the indices are monitored using multivariate statistical process control by the smartphone app. The proposed system was evaluated on seven epilepsy patients. The accuracy and reliability of the R-R interval measurement, which was examined in comparison with the reference electrocardiogram, showed sufficient performance for heart rate variability analysis. The results obtained using the proposed system were compared with those obtained using the existing video and electroencephalogram assessments; it was noted that the proposed method has a sensitivity of 85.7% in detecting heart rate variability change prior to seizures. The false positive rate of 0.62 times/h was not significantly different from the healthy controls. The prediction performance and practical advantages of portability and real-time operation are demonstrated in this study.

    DOI: 10.3390/s20143987

    PubMed

  17. Over- and Under-sampling Approach for Extremely Imbalanced and Small Minority Data Problem in Health Record Analysis Invited Reviewed International journal

    Koichi Fujiwara, Yukun Huang, Kentaro Hori, Kenichi Nishioji, Masao Kobayashi, Mai Kamaguchi, Manabu Kano

    Frontiers in Public Health   Vol. 8   page: 178   2020.5

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    Authorship:Lead author, Corresponding author   Language:English   Publishing type:Research paper (scientific journal)  

    © Copyright © 2020 Fujiwara, Huang, Hori, Nishioji, Kobayashi, Kamaguchi and Kano. A considerable amount of health record (HR) data has been stored due to recent advances in the digitalization of medical systems. However, it is not always easy to analyze HR data, particularly when the number of persons with a target disease is too small in comparison with the population. This situation is called the imbalanced data problem. Over-sampling and under-sampling are two approaches for redressing an imbalance between minority and majority examples, which can be combined into ensemble algorithms. However, these approaches do not function when the absolute number of minority examples is small, which is called the extremely imbalanced and small minority (EISM) data problem. The present work proposes a new algorithm called boosting combined with heuristic under-sampling and distribution-based sampling (HUSDOS-Boost) to solve the EISM data problem. To make an artificially balanced dataset from the original imbalanced datasets, HUSDOS-Boost uses both under-sampling and over-sampling to eliminate redundant majority examples based on prior boosting results and to generate artificial minority examples by following the minority class distribution. The performance and characteristics of HUSDOS-Boost were evaluated through application to eight imbalanced datasets. In addition, the algorithm was applied to original clinical HR data to detect patients with stomach cancer. These results showed that HUSDOS-Boost outperformed current imbalanced data handling methods, particularly when the data are EISM. Thus, the proposed HUSDOS-Boost is a useful methodology of HR data analysis.

    DOI: 10.3389/fpubh.2020.00178

    Scopus

  18. Design and Synthesis of Benzene Congeners of Resolvin E2, a Proresolving Lipid Mediator, as Its Stable Equivalents. Reviewed

    Murakami Y, Fukuda H, Muromoto R, Hirashima K, Ishimura K, Fujiwara K, Ishihara J, Matsuda T, Watanabe M, Shuto S

    ACS medicinal chemistry letters   Vol. 11 ( 4 ) page: 479 - 484   2020.4

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    Publishing type:Research paper (scientific journal)  

    DOI: 10.1021/acsmedchemlett.9b00596

    PubMed

  19. Regression and independence based variable importance measure Reviewed International journal

    Xinmin Zhang, Takuya Wada, Koichi Fujiwara, Manabu Kano

    Computers and Chemical Engineering   Vol. 135 ( 6 ) page: 106757   2020.4

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    Language:English   Publishing type:Research paper (scientific journal)  

    © 2020 Elsevier Ltd Evaluating the importance of input (predictor) variables is of interest in many applications of statistical models. However, nonlinearity and correlation among variables make it difficult to measure variable importance accurately. In this work, a novel variable importance measure, called regression and independence based variable importance (RIVI), is proposed. RIVI is designed by integrating Gaussian process regression (GPR) and Hilbert-Schmidt independence criterion (HSIC) so that it is applicable to nonlinear systems. The results of two numerical examples demonstrate that RIVI is superior to several conventional measures including the Pearson correlation coefficient, PLS-β, PLS-VIP, Lasso, HSIC, and permutation importance with random forest in the variable identification accuracy.

    DOI: 10.1016/j.compchemeng.2020.106757

    Web of Science

    Scopus

  20. Sleep Spindle Detection Using RUSBoost and Synchrosqueezed Wavelet Transform. Reviewed International journal

    Takafumi Kinoshita, Koichi Fujiwara, Manabu Kano, Keiko Ogawa, Yukiyoshi Sumi, Masahiro Matsuo, Hiroshi Kadotani

    IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society   Vol. 28 ( 2 ) page: 390 - 398   2020.2

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    Language:English   Publishing type:Research paper (scientific journal)  

    Sleep spindles are important electroencephalographic (EEG) waveforms in sleep medicine; however, it is burdensome even for experts to detect spindles, so automatic spindle detection methodologies have been investigated. Conventional methods utilize waveforms template matching or machine learning for detecting spindles. In the former approach, it is necessary to tune thresholds for individual adaptation, while the latter approach has the problem of imbalanced data because the amount of sleep spindles is small compared with the entire EEG data. The present work proposes a sleep spindle detection method that combines wavelet synchrosqueezed transform (SST) and random under-sampling boosting (RUSBoost). SST is a time-frequency analysis method suitable for extracting features of spindle waveforms. RUSBoost is a framework for coping with the imbalanced data problem. The proposed SST-RUS can deal with the imbalanced data in spindle detection and does not require threshold tuning because RUSBoost uses majority voting of weak classifiers for discrimination. The performance of SST-RUS was validated using an open-access database called the Montreal archives of sleep studies cohort 1 (MASS-C1), which showed an F-measure of 0.70 with a sensitivity of 76.9% and a positive predictive value of 61.2%. The proposed method can reduce the burden of PSG scoring.

    DOI: 10.1109/TNSRE.2020.2964597

    PubMed

  21. Trial of evaluation of emotions using heart rate variability in free moving dogs Reviewed International journal

    MIKURU MURAYAMA, MIHO NAGASAWA, MAKI KATAYAMA, KAZUSHI IKEDA, TAKATOMI KUBO, TOSHITAKA YAMAKAWA, KOICHI FUJIWARA, TAKEFUMI KIKUSUI

    Japanese Journal of Animal Psychology   Vol. 70 ( 1 ) page: 15 - 18   2020

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    DOI: 10.2502/janip.70.1.1

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  22. Development of Sleep Spindle Detection Method by Combining Wavelet Synchrosqueezed Transform and RUSBoost Reviewed

    FUJIWARA Koichi Fujiwara, KINOSHITA Takafumi, SUMI Yukiyoshi, MATSUO Masahiro, OGAWA Keiko, KANO Manabu, KADOTANI Hiroshi

    Proceedings of the Annual Conference of JSAI   Vol. 2020 ( 0 ) page: 1M4GS1301 - 1M4GS1301   2020

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    <p>Sleep spindles are important electroencephalographic (EEG) waveforms in sleep medicine; however, it is burdensome even for experts to detect spindles, so automatic spindle detection methodologies have been investigated. Conventional methods utilize waveforms template matching or machine learning for detecting spindles. In the former approach, it is necessary to tune thresholds for individual adaptation, while the latter approach has the problem of imbalanced data because the amount of sleep spindles is small compared with the entire EEG data. The present work proposes a sleep spindle detection method that combines wavelet synchrosqueezed transform (SST) and random under-sampling boosting (RUSBoost). SST is a time-frequency analysis method suitable for extracting features of spindle waveforms. RUSBoost is a framework for coping with the imbalanced data problem. The proposed SST-RUS can deal with the imbalanced data in spindle detection and does not require threshold tuning because RUSBoost uses majority voting of weak classifiers for discrimination. The performance of SST-RUS was validated using an open-access database called the Montreal archives of sleep studies cohort 1 (MASS-C1), which showed an F-measure of 0.70 with a sensitivity of 76.9% and a positive predictive value of 61.2%. The proposed method can reduce the burden of PSG scoring.</p>

    DOI: 10.11517/pjsai.JSAI2020.0_1M4GS1301

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  23. Verification of Heart Rate Variability and Autoencoder Based Seizure Prediction Algorithm Using Large Clinical Database Reviewed

    GODA Asuka, FUJIWARA Koichi, MIYAJIMA Miho, YAMAKAWA Toshitaka, KANO Manabu, MAEHARA Taketoshi

    Proceedings of the Annual Conference of JSAI   Vol. 2020 ( 0 ) page: 3Rin461 - 3Rin461   2020

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    <p>Epileptic patients have a risk of accidents associated with seizures, which can lead to severe injury or death. If patients can predict seizures before a seizure onset, they can prevent such accidents by ensuring their safety. We have developed an algorithm to predict seizures by detecting changes in heart rate patterns observed before seizure onsets. In our previous research, heart rate variability (HRV), which is the fluctuations of an RR interval (RRI), is monitored using autoencoder (AE) for seizure prediction. However, our previous studies have limitations: a small amount of clinical data included in the study. In this study, we report the verification results of our developing seizure prediction algorithm using clinical data collected from 180 epileptic patients. As a result, the sensitivity of 77.9% and the area under the ROC curve (AUC) of 0.91 were achieved. Although seizure prediction was effective in most patients in our algorithm, a few patients experienced many false positives. We will investigate the characteristics of such patients based on their medical records.</p>

    DOI: 10.11517/pjsai.JSAI2020.0_3Rin461

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  24. Prediction of drug-induced convulsion by using heart rate variability in monkeys Reviewed

    KUGA Kazuhiro, NAGATA Shoya, NAKAYAMA Chikao, OZAKI Harushige, FUJIWARA Koichi

    Annual Meeting of the Japanese Society of Toxicology   Vol. 47 ( 0 ) page: P - 77E   2020

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    <p>Convulsion causes significant impact on drug development but there is no good biomarker. The aim of this study was to investigate the potential of heart rate variability (HRV) as novel biomarker for drug-induced convulsion in monkeys. Telemetry-implanted monkeys were dosed with convulsants, and HRV was analyzed for 3 hours after dosing by multivariate statistical process management. As a result, frequency and duration of alarms were tended to be increased by picrotoxin and penthylentetrazole. It suggests HRV is useful for predicting drug-induced convulsions in monkeys.</p>

    DOI: 10.14869/toxpt.47.1.0_P-77E

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  25. Development of Heart Rate Variability Analysis-based Heat Stroke detection model with Multivariate Statistical Process Control Reviewed

    OTA Koshi, FUJIWARA Koichi, INATSU Nao, YAMAKAWA Toshitaka, KUBO Takatomo

    Proceedings of the Annual Conference of JSAI   Vol. 2020 ( 0 ) page: 1C5GS1301 - 1C5GS1301   2020

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    <p>Objective: This study proposes a heat stroke detecting model using heart rate variability (HRV) and an anomaly detecting technique. If heat stroke can be detected at an early stage, its patient can rest before it is too late. Methods: Since it is reported that heat stress influences HRV, we developed the heat stroke detecting model that detects abnormality in HRV due to heat stroke by using multivariate statistical process control (MSPC). Results: We measured the HRV data from 30 employees who worked in multiple steel works, whose total data length was 1,042 hours. The result of applying the developed heat stroke detection model showed that the sensitivity of 40.0% and the false positive rate of 1.9 times per hour. Conclusion: This study constructed an early-stage heat stroke detection model by using HRV analysis and MSPC. Significance: This study illustrated the possibility of detecting heat stroke by using HRV analysis.</p>

    DOI: 10.11517/pjsai.JSAI2020.0_1C5GS1301

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  26. Factor Analysis of NAFLD with Health Check Data based on BExSAM Reviewed

    OUCHI Kohei, FUJIWARA Koichi, NISHIOJI Kenichi, KANO Manabu

    Proceedings of the Annual Conference of JSAI   Vol. 2020 ( 0 ) page: 4Rin158 - 4Rin158   2020

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    <p>NAFLD is a disease in which fatty liver disorder occur even without a history of excessive alcohol intake. Although a lot of studies wes conducted to identify the factors of the emergence and progress of NAFLD, few studies focused on causal relationships of test items of the electronic health record (EHR) data. It's important to prevent the emergence and progress of NAFLD, but Cause of NAFLD is unclear. Therefore, we clarify the factors which cause NAFLD by analyzing of EHR data of the Kyoto Second RedCross hospital. Considering the previous researchs, We analyze binary variables of the EHR data. We use the new method we propose in order to estimate the causal relationship of binary variables. As a result, intake of medicine of blood pressure is a cause of NAFLD for women. For men, on the other hand, weight change in a year, medical history of anemia, intake of medicine of blood pressure, intake of medicine of blood glucose, the habit of skipping breakfast, eating habit at night and medical history of cardiovascular are causes of NAFLD.</p>

    DOI: 10.11517/pjsai.JSAI2020.0_4Rin158

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  27. Application of Wearable Devices for the Risk Assessment and Prevention of Sudden Unexpected Death in Epilepsy Reviewed

    Miyajima Miho, Yamakawa Toshitaka, Fujiwara Koichi, Maehara Taketoshi

    Journal of the Japan Epilepsy Society   Vol. 38 ( 1 ) page: 91 - 97   2020

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    <p>Sudden unexpected death in epilepsy (SUDEP) typically occurs following postictal respiratory depression and cardiac abnormalities. Additionally, abnormal interictal heart rate variability (HRV), which reflects autonomic dysregulation, may have potential as a biomarker of SUDEP risk. Daily monitoring of heart rate and respiratory condition would contribute to SUDEP risk assessment and effective preventative strategies in patients with intractable epilepsy. Therefore, we have been examining the usefulness of wearable heart rate monitoring systems with garment-type electrocardiogram (ECG) sensors and their potential for clinical application in SUDEP risk assessment. Combining garment-type sensor with multiple-lead electrodes and anti-noise transmitter would optimize the accuracy in accordance with individual differences in body structure and movement. The ring-figured pulse oximeter confers a reduced feeling of restriction than that conferred by conventional oximeters; thus, the former may be a useful option for detecting respiratory disturbances.</p>

    DOI: 10.3805/jjes.38.91

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  28. Resting Heart Rate Variability Is Associated With Subsequent Orthostatic Hypotension: Comparison Between Healthy Older People and Patients With Rapid Eye Movement Sleep Behavior Disorder. Reviewed

    Sumi Y, Nakayama C, Kadotani H, Matsuo M, Ozeki Y, Kinoshita T, Goto Y, Kano M, Yamakawa T, Hasegawa-Ohira M, Ogawa K, Fujiwara K

    Frontiers in neurology   Vol. 11   page: 567984   2020

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    DOI: 10.3389/fneur.2020.567984

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  29. Factor Analysis of Nitrogen Oxides Emissions in Coal Fired Power Plant with LiNGAM Reviewed

    SAITO Tatsuki, FUJIWARA Koichi

    Proceedings of the Annual Conference of JSAI   Vol. 2020 ( 0 ) page: 4M3GS1303 - 4M3GS1303   2020

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    <p>Coal has been an important energy source worldwide, and over 30\% of electricity in japan is covered by coal fired power generation; however, its NOx emissions is large since the amount of nitrogen contained in coal is larger than other fossil fuels. Thus, precise control of NOx emissions is required in coal-fired power plant operation. Although the trend of NOx generation can be theoretically calculated, it is difficult to predict real NOx generation because it is affected by complicated factors such as furnace design and the operating conditions. To identify operating factors that affect NOx generation is needed. LiNGAM is an exploratory causal analysis method, which identifies a causal ordering of variable and their connection strengths without any prior knowledge on causal relationship among variables. In this study, real operation data collected from a coal-fired power plant were analyzed using LiNGAM in order to identify NOx generation factors. The causal relationship between each process variable and NOx generation was estimated by LiNGAM, and their connection strengths on NOx generation was estimated. The results agreed with previous reports about the NOx generation causes. Our analysis demonstrated that LiNGAM is an useful method for identifying important operational factors in processes.</p>

    DOI: 10.11517/pjsai.JSAI2020.0_4M3GS1303

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  30. Obstructive sleep apnea screening by heart rate variability-based apnea/normal respiration discriminant model. Reviewed International journal

    Chikao Nakayama, Koichi Fujiwara, Yukiyoshi Sumi, Masahiro Matsuo, Manabu Kano, Hiroshi Kadotani

    Physiological measurement   Vol. 40 ( 12 ) page: 125001 - 125001   2019.12

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    OBJECTIVE: Obstructive sleep apnea (OSA) is a common sleep disorder; however, most patients are undiagnosed and untreated because it is difficult for patients themselves to notice OSA in daily living. Polysomnography (PSG), which is the gold standard test for sleep disorder diagnosis, cannot be performed in many hospitals. This fact motivates us to develop a simple system for screening OSA at home. APPROACH: The autonomic nervous system changes during apnea, and such changes affect heart rate variability (HRV). This work develops a new apnea screening method based on HRV analysis and machine learning technologies. An apnea/normal respiration (A/N) discriminant model is built for respiration condition estimation for every heart rate measurement, and an apnea/sleep ratio is introduced for final diagnosis. A random forest is adopted for the A/N discriminant model construction, which is trained with the PhysioNet apnea-ECG database. MAIN RESULTS: The screening performance of the proposed method was evaluated by applying it to clinical PSG data. Sensitivity and specificity achieved 76% and 92%, respectively, which are comparable to existing portable sleep monitoring devices used in sleep laboratories. SIGNIFICANCE: Since the proposed OSA screening method can be used more easily than existing devices, it will contribute to OSA treatment.

    DOI: 10.1088/1361-6579/ab57be

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  31. てんかん患者におけるウェアラブル自律神経機能モニタリングの試み てんかん突然死のリスク評価を目指し International journal

    宮島 美穂, 山川 俊貴, 藤原 幸一, 関 拓哉, 稲次 基希, 橋本 聡華, 岩崎 真樹, 長綱 敏和, 藤井 正美, 山本 信二, 加納 学, 前原 健寿

    てんかん研究   Vol. 37 ( 2 ) page: 541 - 541   2019.9

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  32. Emotional Contagion From Humans to Dogs Is Facilitated by Duration of Ownership Invited Reviewed

    M. Katayama, T. Kubo, T. Yamakawa, K. Fujiwara, K. Nomoto, K. Ikeda, K. Mogi, M. Nagasawa and T. Kikusui

    Frontiers in Psychology   Vol. 10   page: 1678   2019.7

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    DOI: https://doi.org/10.3389/fpsyg.2019.01678

  33. Emotional Contagion From Humans to Dogs Is Facilitated by Duration of Ownership Reviewed International journal

    M. Katayama, T. Kubo, T. Yamakawa, K. Fujiwara, K. Nomoto, K. Ikeda, K. Mogi, M. Nagasawa, T. Kikusui

    Frontiers in Psychology   Vol. 10   page: 1678   2019.7

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    DOI: 10.3389/fpsyg.2019.01678

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  34. Heart Rate Variability-Based Driver Drowsiness Detection and Its Validation With EEG. Reviewed International journal

    Koichi Fujiwara, Erika Abe, Keisuke Kamata, Chikao Nakayama, Yoko Suzuki, Toshitaka Yamakawa, Toshihiro Hiraoka, Manabu Kano, Yukiyoshi Sumi, Fumi Masuda, Masahiro Matsuo, Hiroshi Kadotani

    IEEE transactions on bio-medical engineering   Vol. 66 ( 6 ) page: 1769 - 1778   2019.6

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    OBJECTIVE: Driver drowsiness detection is a key technology that can prevent fatal car accidents caused by drowsy driving. The present work proposes a driver drowsiness detection algorithm based on heart rate variability (HRV) analysis and validates the proposed method by comparing with electroencephalography (EEG)-based sleep scoring. METHODS: Changes in sleep condition affect the autonomic nervous system and then HRV, which is defined as an RR interval (RRI) fluctuation on an electrocardiogram trace. Eight HRV features are monitored for detecting changes in HRV by using multivariate statistical process control, which is a well known anomaly detection method. RESULT: The performance of the proposed algorithm was evaluated through an experiment using a driving simulator. In this experiment, RRI data were measured from 34 participants during driving, and their sleep onsets were determined based on the EEG data by a sleep specialist. The validation result of the experimental data with the EEG data showed that drowsiness was detected in 12 out of 13 pre-N1 episodes prior to the sleep onsets, and the false positive rate was 1.7 times per hour. CONCLUSION: The present work also demonstrates the usefulness of the framework of HRV-based anomaly detection that was originally proposed for epileptic seizure prediction. SIGNIFICANCE: The proposed method can contribute to preventing accidents caused by drowsy driving.

    DOI: 10.1109/TBME.2018.2879346

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  35. てんかん発作検知・予知に関する最新の研究動向 Reviewed International journal

    宮島 美穂, 藤原 幸一, 山川 俊貴

    クリニシアン   Vol. 66 ( 637 ) page: 40 - 45   2019.5

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  36. The Translation Inhibitor Rocaglamide Targets a Bimolecular Cavity between eIF4A and Polypurine RNA. Reviewed

    Iwasaki S, Iwasaki W, Takahashi M, Sakamoto A, Watanabe C, Shichino Y, Floor SN, Fujiwara K, Mito M, Dodo K, Sodeoka M, Imataka H, Honma T, Fukuzawa K, Ito T, Ingolia NT

    Molecular cell   Vol. 73 ( 4 ) page: 738 - 748.e9   2019.2

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    DOI: 10.1016/j.molcel.2018.11.026

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  37. Epileptic Seizure Suppression by Focal Brain Cooling with Recirculating Coolant Cooling System: Modeling and Simulation Reviewed

    IEEE Transactions on Neural Systems & Rehabilitation Engineering   Vol. 27 ( 2 ) page: 162-171   2019.2

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  38. Epileptic Seizure Suppression by Focal Brain Cooling with Recirculating Coolant Cooling System: Modeling and Simulation Reviewed International journal

    Kei Hata, Koichi Fujiwara, Takao Inoue, Takuto Abe, Takatomi Kubo, Toshitaka Yamakawa, Sadahiro Nomura, Hirochika Imoto, Michiyasu Suzuki, Manabu Kano

    IEEE Transactions on Neural Systems and Rehabilitation Engineering   Vol. 27 ( 2 ) page: 162 - 171   2019.2

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    © 2001-2011 IEEE. A focal brain cooling system for treatment of refractory epilepsy that is implantable and wearable may permit patients with this condition to lead normal daily lives. We have developed such a system for cooling of the epileptic focus by delivery of cold saline to a cooling device that is implanted cranially. The outflow is pumped for circulation and cooled by a Peltier device. Here, we describe the design of the system and evaluate its feasibility by simulation. Mathematical models were constructed based on equations of fluid dynamics and data from a cat model. Computational fluid dynamics simulations gave the following results: 1) a cooling device with a complex channel structure gives a more uniform temperature in the brain; 2) a cooling period of <10 min is required to reach an average temperature of 25.0°Cat 2 mm below the brain surface, which is the target temperature for seizure suppression. This time is short enough for cooling of the brain before seizure onset after seizure prediction by an intracranial electroencephalogram-based algorithm; and 3) battery charging would be required once every several days for most patients. These results suggest that the focal brain cooling system may be clinically applicable.

    DOI: 10.1109/TNSRE.2019.2891090

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  39. Sleep Apnea Detection by Combining Long Short-Term Memory and Heart Rate Variability

    IWASAKI Ayako, NAKAYAMA Chikao, FUJIWARA Koichi, SUMI Yukiyoshi, MATSUO Masahiro, KANO Manabu, KADOTANI Hiroshi

    Proceedings of the Annual Conference of JSAI   Vol. 2019 ( 0 ) page: 1H4J1303-1H4J1303   2019

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    <p>Sleep apnea syndrome (SAS) is a prevalent disorder which causes daytime fatigue with increased risk of cardiovascular diseases. A large number of patients are undiagnosed and untreated partly because of the difficulty in performing its gold standard test, polysomnography (PSG). In this research, we propose a simple screening method utilizing heart rate variability (HRV) and long short-term memory (LSTM) which is a kind of the neural network techniques. The result of applying this algorithm to clinical data demonstrates that it can discriminate between patients and healthy people with sensitivity (100%) and specificity (100%).</p>

    DOI: 10.11517/pjsai.JSAI2019.0_1H4J1303

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  40. Development of Epileptic Seizure Prediction Algorithm by Combining Heart Rate Variability Analysis and Autoencorder

    FUJIWARA Koichi, SAKANE Fumiya, MIYAJIMA Miho, YAMAKAWA Toshitaka, MAEHARA Taketoshi

    Proceedings of the Annual Conference of JSAI   Vol. 2019 ( 0 ) page: 2N4J1303-2N4J1303   2019

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    DOI: 10.11517/pjsai.JSAI2019.0_2N4J1303

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  41. Denoising autoencoder-based modification method for RRI data with premature atrial contraction

    MIYATANI Shota, FUJIWARA Koichi, KANO Manabu

    Proceedings of the Annual Conference of JSAI   Vol. 2019 ( 0 ) page: 2N3J1301-2N3J1301   2019

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    <p>The fluctuation of an RR interval (RRI) on an electrocardiogram (ECG) is called heart rate variability (HRV). Since HRV reflects the activities of the autonomous nervous system, HRV analysis has been used for health monitoring systems. However, the performance of health monitoring systems using HRV features is easily deteriorated by arrhythmias. The present work focuses on premature atrial contraction (PAC) that many healthy people have. To modify RRI data with PAC, the present work proposes a new method based on a denoising autoencoder (DAE), referred to as DAE-based RRI modification (DAE-RM). The proposed method aims to correct the disturbed RRI data by regarding PAC as artifacts. The performance of DAE-RM was evaluated by its application to RRI data which contains artificial PAC (PAC-RRI). The result showed that DAE-RM successfully modified PAC-RRI data. The root means squared error (RMSE) of the modified RRI was improved by 27.4% from the PAC-RRI. The proposed DAE-RM has a potential for realizing precise health monitoring systems which use HRV analysis.</p>

    DOI: 10.11517/pjsai.JSAI2019.0_2N3J1301

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  42. 心拍変動解析とAI/IoTを活用したてんかん発作予知技術の開発

    藤原 幸一, 宮島 美穂, 山川 俊貴

    生体医工学   Vol. 57 ( 0 ) page: S218_1-S218_1   2019

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    <p>てんかん発作に伴う事故はしばしば重傷や死亡につながる場合があるが,患者が数十秒前に発作を予知できれば事故や怪我の防止につながる.脳波を用いたてんかん発作予知の研究が行われているが,脳波計を日常生活で用いることは現実的ではない.てんかん発作起始前には,患者の心拍に変化が現れることが知られており,患者の心拍変動(HRV)を監視することでてんかん発作を知できる可能性がある.我々はこれまでにHRVを用いたてんかん発作予知AIを開発した.開発したAIでは,てんかん患者心拍データからHRV解析によっていくつかの特徴量を抽出し,抽出した特徴量を入力としててんかん発作を予知する.本研究では異常検出手法を用いてAIを開発した.HRVはウェアラブルデバイスを用いることで容易に測定できるため,発作予知AIと組み合わせることで.てんかん発作予知システムを構築した.本研究は2017年8月より,AMED先端計測プログラムに採択され,医療機器としての実用化を目指している.現在,てんかん発作予知システムの実用化に向け,臨床データ収集の継続とAIの精度向上,ウェアラブルデバイス開発を行っており,本発表では現在の開発状況および今後の見通しを述べる.</p>

    DOI: 10.11239/jsmbe.Annual57.S218_1

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  43. Missing RRI interpolation algorithm based on locally weighted partial least squares for precise heart rate variability analysis Reviewed International journal

    Keisuke Kamata, Koichi Fujiwara, Takafumi Kinoshita, Manabu Kano

    Sensors (Switzerland)   Vol. 18 ( 11 ) page: 3870   2018.11

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    © 2018 by the authors. Licensee MDPI, Basel, Switzerland. The R-R interval (RRI) fluctuation in electrocardiogram (ECG) is called heart rate variability (HRV), which reflects activities of the autonomic nervous system (ANS) and has been used for various health monitoring services. Accurate R wave detection is crucial for success in HRV-based health monitoring services; however, ECG artifacts often cause missing R waves and deteriorate the accuracy of HRV analysis. The present work proposes a new missing RRI interpolation technique based on Just-In-Time (JIT) modeling. In the JIT modeling framework, a local regression model is built by weighing samples stored in the database according to the distance from a query and output is estimated only when an estimate is requested. The proposed method builds a local model and estimates missing RRI only when an RRI detection error is detected. Locally weighted partial least squares (LWPLS) is adopted for local model construction. The proposed method is referred to as LWPLS-based RRI interpolation (LWPLS-RI). The performance of the proposed LWPLS-RI was evaluated through its application to RRI data with artificial missing RRIs. We used the MIT-BIH Normal Sinus Rhythm Database for nominal RRI dataset construction. Missing RRIs were artificially introduced and they were interpolated by the proposed LWPLS-RI. In addition, MEAN that replaces the missing RRI by a mean of the past RRI data was compared as a conventional method. The result showed that the proposed LWPLS-RI improved root mean squared error (RMSE) of RRI by about 70% in comparison with MEAN. In addition, the proposed method realized precise HRV analysis. The proposed method will contribute to the realization of precise HRV-based health monitoring services.

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  44. Is hemifacial spasm affected by changes in the heart rate? A study using heart rate variability analysis. Reviewed International journal

    Tadashi Hamasaki, Motohiro Morioka, Koichi Fujiwara, Chikao Nakayama, Miho Harada, Kiyohiko Sakata, Yu Hasegawa, Toshitaka Yamakawa, Kazumichi Yamada, Akitake Mukasa

    Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology   Vol. 129 ( 10 ) page: 2205 - 2214   2018.10

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    OBJECTIVE: Hemifacial spasm (HFS) is caused by arterial conflict at the root exit zone of the facial nerve. As the offending artery is pulsatile in nature, this study investigated the association of heart rate fluctuation with HFS. METHODS: Twenty-four preoperative patients underwent simultaneous recordings of facial electromyogram and electrocardiogram overnight. Series of R-wave to R-wave intervals (RRIs) in the electrocardiogram were analyzed across subjects in relation to HFS. The degree of heart rate fluctuation was quantified by analyzing the heart rate variability (HRV). The sleep stage was evaluated during the period of HFS. RESULTS: A 0.1 Hz fluctuation in RRIs by 5% compared to the baseline preceded a few seconds the onset of the HFS, indicating that a significant increase in the heart rate coincided with HFS. HRV analysis demonstrated that fluctuations in the heart rate were significantly enhanced during HFS. Wake or light sleep stages were more often accompanied by HFS, suggesting an association with autonomic activities. CONCLUSION: Our findings suggest that the etiology of HFS is more than just a mechanical compression of the facial nerve and may involve changes in pulsatile frequency in offending arteries. SIGNIFICANCE: We propose the etiology of HFS from a unique standpoint.

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  45. Deniosing Autoencoder-based Modification of RRI data with Premature Ventricular Contraction for Precise Heart Rate Variability Analysis. Reviewed

    Miyatani S, Fujiwara K, Kano M

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference   Vol. 2018   page: 5018 - 5021   2018.7

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    DOI: 10.1109/EMBC.2018.8513218

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  46. Ischemic stroke detection by analyzing heart rate variability in rat middle cerebral artery occlusion model Reviewed International journal

    Tomonobu Kodama, Keisuke Kamata, Koichi Fujiwara, Manabu Kano, Toshitaka Yamakawa, Ichiro Yuki, Yuichi Murayama

    IEEE Transactions on Neural Systems and Rehabilitation Engineering   Vol. 26 ( 6 ) page: 1152 - 1160   2018.6

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    © 2001-2011 IEEE. Although early reperfusion therapy is effective for acute ischemic stroke, limited therapeutic time-window resulted in only 10% of patients receiving reperfusion therapy. A fast and reliable stroke detection method is desired so that patients can receive early reperfusion therapy. It has been reported that ischemic stroke affects heart rate variability (HRV), which reflects activities of the autonomic nervous function. Thus, ischemic stroke may be detected at an acute stage through monitoring HRV. This paper proposes an HRV-based ischemic stroke detection algorithm by using multivariate statistical process control (MSPC), which is a well-known anomaly detection algorithm. As a feasibility study before collecting a large amount of clinical data from human patients, this paper used the middle cerebral artery occlusion (MCAO) model in rats for collecting HRV data shortly after ischemic stroke onsets. The 11 MCAO-operated rats and 11 sham-operated rats were prepared, and HRV data of three sham-operated rats were used for model construction. The data on the other 19 rats were used for its validation. The experimental result showed that sensitivity and specificity of the proposed algorithm were 82% and 75%, respectively. Thus, the present work shows the possibility of realizing an HRV-based ischemic stroke detection system for human patients.

    DOI: 10.1109/TNSRE.2018.2834554

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  47. Conjugate Addition to Acylketene Acetals Derived from 1,8-Dihydroxynaphthalene and Its Application To Synthesize the Proposed Structure of Spiropreussione A. Reviewed

    Tsukamoto H, Nomura Y, Fujiwara K, Hanada S, Doi T

    Organic letters   Vol. 20 ( 10 ) page: 3140 - 3143   2018.5

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    DOI: 10.1021/acs.orglett.8b01259

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  48. Nearest correlation-based input variable weighting for soft-sensor design Reviewed International journal

    Koichi Fujiwara, Manabu Kano

    Frontiers in Chemistry   Vol. 6 ( MAY ) page: 171   2018.5

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    © 2018 Fujiwara and Kano. In recent years, soft-sensors have been widely used for estimating product quality or other important variables when online analyzers are not available. In order to construct a highly accurate soft-sensor, appropriate data preprocessing is required. In particular, the selection of input variables or input features is one of the most important techniques for improving estimation performance. Fujiwara et al. proposed a variable selection method, in which variables are clustered into variable groups based on the correlation between variables by nearest correlation spectral clustering (NCSC), and each variable group is examined as to whether or not it should be used as input variables. This method is called NCSC-based variable selection (NCSC-VS). However, these NCSC-based methods have a lot of parameters to be tuned, and their joint optimization is burdensome. The present work proposes an effective input variable weighting method to be used instead of variable selection to conserve labor required for parameter tuning. The proposed method, referred to herein as NC-based variable weighting (NCVW), searches input variables that have the correlation with the output variable by using the NC method and calculates the correlation similarity between the input variables and output variable. The input variables are weighted based on the calculated correlation similarities, and the weighted input variables are used for model construction. There is only one parameter in the proposed NCVW since the NC method has one tuning parameter. Thus, it is easy for NCVW to develop a soft-sensor. The usefulness of the proposed NCVW is demonstrated through an application to calibration model design in a pharmaceutical process.

    DOI: 10.3389/fchem.2018.00171

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  49. Nearest Correlation-Based Input Variable Weighting for Soft-sensor Design, Frontiers in Chemistry Reviewed International journal

    K. Fujiwara, M. Kano

    Frontiers in Chemistry     page: .   2018.5

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  50. 心拍数変動解析と多変量統計的プロセス管理を用いたウェアラブルてんかん発作予知システムの開発 Reviewed International journal

    山川 俊貴, 宮島 美穂, 藤原 幸一, 加納 学, 鈴木 陽子, 渡辺 裕貴, 渡邊 さつき, 村田 佳子, 星田 徹, 前原 健寿

    てんかん研究   Vol. 35 ( 3 ) page: 730 - 730   2018.1

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  51. Analysis of VNS Effect on EEG Connectivity with Granger Causality and Graph Theory Reviewed

    Uchida Tsuyoshi, Fujiwara Koichi, Inoue Takao, Maruta Yuichi, Kano Manabu, Suzuki Michiyasu

    2018 ASIA-PACIFIC SIGNAL AND INFORMATION PROCESSING ASSOCIATION ANNUAL SUMMIT AND CONFERENCE (APSIPA ASC)     page: 861 - 864   2018

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  52. Design of False Heart Rate Feedback System for Improving Game Experience Reviewed

    Ogawa Sayaka, Fujiwara Koichi, Yamakawa Toshitaka, Abe Erika, Kano Manabu

    2018 IEEE INTERNATIONAL CONFERENCE ON CONSUMER ELECTRONICS (ICCE)     2018

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  53. MISSING RRI INTERPOLATION ALGORITHM USING JUST-IN-TIME MODELING FRAMEWORK AND ITS APPLICATION TO HRV-BASED DROWSY DRIVING DETECTION Reviewed

    Fujiwara K., Kinoshita T., Kamata K., Yamakawa T., Kano M.

    SLEEP MEDICINE   Vol. 40   page: E101 - E101   2017.12

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  54. ACUTE EFFECT OF CONTINUOUS POSITIVE AIRWAY PRESSURE THERAPY ON HEART RATE VARIABILITY OF SAS PATIENTS IN CONSECUTIVE NIGHTS Reviewed

    Nakayama C., Fujiwara K., Matsuo M., Kano M., Kadotani H.

    SLEEP MEDICINE   Vol. 40   page: E237 - E237   2017.12

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  55. ウェアラブルデバイスとスマートフォンを用いたてんかん発作予知技術 Reviewed International journal

    藤原 幸一, 宮島 美穂, 山川 俊貴

    Epilepsy   Vol. 11 ( 2 ) page: 7 - 13   2017.11

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  56. ウェアラブルデバイスとスマートフォンを用いたてんかん発作予知技術 International journal

    藤原 幸一, 宮島 美穂, 山川 俊貴

    Epilepsy: てんかんの総合学術誌   Vol. 11 ( 2 ) page: 75 - 81   2017.11

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  57. Total Syntheses of (+)- and (-)-Tetrapetalones A and C. Reviewed

    Dhanjee HH, Kobayashi Y, Buergler JF, McMahon TC, Haley MW, Howell JM, Fujiwara K, Wood JL

    Journal of the American Chemical Society   Vol. 139 ( 42 ) page: 14901 - 14904   2017.10

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    DOI: 10.1021/jacs.7b09358

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  58. Seizure prediction in localization-related epilepsy by heart rate variability monitoring Reviewed International journal

    Miyajima M, Fujiwara K, Toshitaka Y, Yoko S, Sasai-Sakuma T, Kano M, Maehara T, Watanabe Y, Watanabe S, Murata Y, Sasano T, Eisuke M

    JOURNAL OF THE NEUROLOGICAL SCIENCES   Vol. 381   page: 554 - 555   2017.10

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    DOI: 10.1016/j.jns.2017.08.3769

  59. ヘルスモニタリングのための心拍変動解析 Invited Reviewed International journal

    藤原 幸一

    システム/制御/情報   Vol. 61 ( 9 ) page: 381 - 386   2017.9

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    DOI: 10.11509/isciesci.61.9_381

  60. 多変量統計的プロセス管理と心拍変動解析を用いたてんかん発作予知技術の開発 Invited Reviewed International journal

    藤原幸一, 宮島美穂, 鈴木陽子, 山川俊貴, 加納学

    計測と制御   Vol. 56 ( 7 ) page: 526 - 529   2017.7

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    DOI: 10.11499/sicejl.56.526

  61. A new infarction detection method based on heart rate variability in rat middle cerebral artery occlusion model.

    Kodata T, Kamata K, Fujiwara K, Kano M, Yamakawa T, Yuki I, Murayama Y

    Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference   Vol. 2017   page: 3061-3064   2017.7

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    DOI: 10.1109/EMBC.2017.8037503

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  62. Design of focal brain cooling system for suppressing epileptic seizures.

    Hata K, Fujiwara K, Kano M, Inoue T, Nomura S, Imoto H, Suzuki M

    Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference   Vol. 2017   page: 283-286   2017.7

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    DOI: 10.1109/EMBC.2017.8036817

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  63. 運転中の能動的行為によるドライバの覚醒維持効果と運転安全性 Reviewed International journal

    伊部達郎, 平岡敏洋, 阿部恵里花, 藤原幸一, 山川俊貴

    自動車技術会論文集   Vol. 48 ( 2 ) page: 463 - 469   2017.2

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    DOI: 10.11351/jsaeronbun.48.463

  64. Canine emotional states assessment with heart rate variability Reviewed International journal

    Eri Nakahara, Yuki Maruno, Takatomi Kubo, Rina Ouchi, Maki Katayama, Koichi Fujiwara, Miho Nagasawa, Takefumi Kikusui, Kazushi Ikeda

    2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2016     2017.1

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    Emotions of a person affect the person's performance in a task and so do emotions of a rescue dog that works after disasters. Hence, estimating emotions of a rescue dog by the handler can improve its performance and welfare. Emotions also appear in physiological signals such as heart rate variability (HRV). In fact, HRV has information of emotions in both cases of human and dogs. To make emotion estimation more practical, we proposed a method for emotion estimation from HRV of dogs and evaluated its performance using real data. The method classified positive, negative, and neutral emotions with 88% accuracy within each subject and 72% over all subjects. These accuracies are high enough for practical use in rescue dogs.

    DOI: 10.1109/APSIPA.2016.7820868

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  65. A new infarction detection method based on heart rate variability in rat middle cerebral artery occlusion model Reviewed

    Kodata Tomonobu, Kamata Keisuke, Fujiwara Koichi, Kano Manabu, Yamakawa Toshiki, Yuki Ichiro, Murayama Yuichi

    2017 39TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)     page: 3061 - 3064   2017

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  66. Development of Correlation-based Process Characteristics Visualization Method and Its Application to Fault Detection Reviewed

    Fujiwara Koichi, Kano Manabu

    2017 13TH IEEE INTERNATIONAL CONFERENCE ON CONTROL & AUTOMATION (ICCA)     page: 940 - 945   2017

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  67. Design of Focal Brain Cooling System for Suppressing Epileptic Seizures Reviewed

    Hata Kei, Fujiwara Koichi, Kano Manabu, Inoue Takao, Nomura Sadahiro, Imoto Hirochika, Suzuki Michiyasu

    2017 39TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)     page: 283 - 286   2017

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  68. Causal Analysis based on Non-time-series Kernel Granger Causality in a Steelmaking Process Reviewed

    Sato Ryosuke, Fujiwara Koichi, Tani Masahiro, Mori Junichi, Ise Junji, Harada Kohhei, Kano Manabu

    2017 11TH ASIAN CONTROL CONFERENCE (ASCC)     page: 1778 - 1782   2017

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  69. ソフトセンサー構築支援ツールの開発 Invited

    金子弘昌,金尚弘,藤原幸一,

    化学工学   Vol. 80 ( 12 ) page: 773-775   2016.12

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  70. Epileptic Seizure Prediction Based on Multivariate Statistical Process Control of Heart Rate Variability Features Reviewed

    K. Fujiwara, M. Miyajima, T. Yamakawa, E. Abe, Y. Suzuki, Y. Sawada, M. Kano, T. Maehara, K. Ohta, T. Sasai-Sakuma, T. Sasano, M. Matsuura, and E. Matsushima

    IEEE Transactions on Biomedical Engineering   Vol. 63   page: 1321-1332   2016.6

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    DOI: 10.1109/TBME.2015.2512276

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  71. Comparisons of Portable Sleep Monitors of Different Modalities: Potential as Naturalistic Sleep Recorders Reviewed

    M. Matsuo, F. Masuda, Y. Sumi, M. Takahashi, N. Yamada, M. H. Ohira, K. Fujiwara, T. Kanemura and H. Kadotani

    Frontiers in Neurology     2016.6

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    DOI: 10.3389/fneur.2016.00110

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  72. Variable Elimination-Based Contribution for Accurate Fault Identification

    Y. Satoyama, K. Fujiwara, M. Kano Fujiwara

    DYCOPS-CAB 2016     2016.6

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    DOI: 10.1016/j.ifacol.2016.07.368

  73. Evaluation of a Portable Two-channel Electroencephalogram Monitoring System to Analyze Sleep Stages Reviewed

    T. Kanemura, H. Kadotani, M. Matsuo, F. Masuda, K. Fujiwara , M. Ohira and N. Yamada

    Journal of Oral and Sleep Medicine   Vol. 2   page: 101-108   2016.5

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  74. 10年後の看 -ウェアラブデバイスが拓くヘルスモニタサービス- Invited

    藤原 幸一

    化学工学,   Vol. 80 ( 2 ) page: 91-95   2016.2

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    CiNii Article

  75. Development of Drowsiness Detection Method by Integrating Heart Rate Variability Analysis and Multivariate Statistical Process Control Reviewed

    E. Abe, K. Fujiwara, T. Hiraoka, T. Yamakawa and M. Kano

    SICE Journal of Control, Measurement, and System Integration   Vol. 9   page: 10-17   2016.1

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    DOI: 10.9746/jcmsi.9.10

  76. Development of Photoplethysmogram Sensor-embedded Video Game Controller

    E. Abe, H. Chigira, K. Fujiwara, T. Yamakawa, M. Kano

    IEEE ICCE 2016     2016.1

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    DOI: 10.1109/ICCE.2016.7430675

  77. Development of Stroke Detection Method by Heart Rate Variability Analysis and Support Vector Machine

    K. Kamata, K. Fujiwara, T. Kodama, M. Kano, T. Yamakawa, N. Kobayashi, F. Shimizu

    APSIPA ASC 2015     2015.12

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    DOI: 10.1109/APSIPA.2015.7415475

  78. Accuracy Comparison of Two Microcontroller-embedded R-wave Detection Methods for Heart-rate Variability Analysis Reviewed

    T. Yamakawa, R. Kinishita, K. Fujiwara, M. Kano, M. Miyajima, T. Sakata, Y. Ueda

    APSIPA ASC 2015     2015.12

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    DOI: 10.1109/APSIPA.2015.7415423

  79. Heart Rate Monitoring by Pulse Sensor Embedded Game Controller

    E. Abe, H. Chigira, T. Yamakawa, K. Kano

    APSIPA ASC 2015     2015.12

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    DOI: 10.1109/APSIPA.2015.7415478

  80. Efficient wavenumber selection based on spectral fluctuation dividing and correlation-based clustering for calibration modeling Reviewed

    T. Miyano, K. Fujiwara, M. Kano, H. Tanabe, H. Nakagawa, T. Watanabe, H. Minami

    Chemometrics and Intelligent Laboratory Systems   Vol. 148   page: 85-94   2015.9

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    DOI: 10.1016/j.chemolab.2015.09.009

  81. Efficient input variable selection for soft-senor design based on nearest correlation spectral clustering and group Lasso Reviewed

    Koichi Fujiwara, Manabu Kano

    ISA Transactions   Vol. 58 ( 9 ) page: 367-379   2015.9

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    Appropriate input variables have to be selected for building highly accurate soft sensor. A novel input variable selection method based on nearest correlation spectral clustering (NCSC) has been proposed, and it is referred to as NCSC-based variable selection (NCSC-VS). Although NCSC-VS can select appropriate input variables, a lot of parameters have to be tuned carefully for selecting proper variables. The present work proposes a new methodology for efficient input variable selection by integrating NCSC and group Lasso. The proposed NCSC-based group Lasso (NCSC-GL) can not only reduce the number of tuning parameters but also achieve almost the same performance as NCSC-VS. The usefulness of the proposed NCSC-GL is demonstrated through applications to soft sensor design for a pharmaceutical process and a chemical process.

    DOI: 10.1016/j.isatra.2015.04.007

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  82. Development of sleep apnea syndrome screening method by using heart rate variability analysis and support vector machine

    C. Nakayama, K. Fujiwara, M. Matsuo, M. Kano, and H. Kodotani

    EMBC 2015     2015.8

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    DOI: 10.1109/EMBC.2015.7320289

  83. Nearest Correlation Louvain Method for Fast and Good Selection of Input Variables of Statistical Model Reviewed

    T. Uchimaru, K. Hazama, K. Fujiwara and M. Kano

    ADCHEM 2015     2015.6

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    DOI: 10.1016/j.ifacol.2015.08.168

  84. Calibration Model Design based on Weighted Nearest Correlation Spectral Clustering Reviewed

    K. Fujiwara and M. Kano

    ASCC 2015     2015.5

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    DOI: 10.1109/ASCC.2015.7244821

  85. Efficient Wavenumber Selection Based on Nearest Correlation Louvain Method for NIR Calibration Modeling

    T. Uchimaru, K. Hazama, K. Fujiwara and M. Kano

    ASCC 2015     2015.5

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  86. A Study on Heart Rate Monitoring in Daily Life by Using a Surface-Type Sensor Reviewed

    H. Chigira, A. Maeda, M. Kobayashi, K. Fujiwara, T. Hiraoka, A. Tanaka, T. Tanaka

    SICE Journal of Control, Measurement, and System Integration   Vol. 8 ( 1 ) page: 74-78   2015.1

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    DOI: 10.9746/jcmsi.8.74

  87. Epileptic Seizure Monitoring by One-Class Support Vector Machine Reviewed

    K. Fujiwara, E. Abe, Y. Suzuki, M. Miyajima, T. Yamakawa, M. Kano, T. Maehara, K. Ohta and T. Sasano

    APSIPA ASC 2014     2014.12

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    DOI: 10.1109/APSIPA.2014.7041713

  88. Development of Drowsy Driving Accident Prediction by Heart Rate Variability Analysis Reviewed

    E. Abe, K. Fujiwara, T. Hiraoka, T. Yamakawa, M. Kano

    APSIPA ASC 2014     2014.12

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    DOI: 10.1109/APSIPA.2014.7041787

  89. Real-Time Heart Rate Variability Monitoring Employing a Wearable Telemeter and a Smartphone Reviewed

    T. Yamakawa, K. Fujiwara, M. Miyajima, E. Abe, M. Kano, Y. Ueda

    APSIPA ASC 2014     2014.12

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    DOI: 10.1109/APSIPA.2014.7041783

  90. Epileptic Seizure Monitoring by Using Multivariate Statistical Process Control Reviewed

    H. Hashimoto, K. Fujiwara, S. Yoko, M. Miyajima, T. Yamakawa, M. Kano, T. Maehara, K. Ohta, T. Sasano, M. Matsuura, E. Matsushima

    IFAC CAB 2013     2013.12

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    DOI: 10.3182/20131216-3-IN-2044.00026

  91. Development of a wearable HRV telemetry system to be operated by non-experts in daily life Reviewed

    T. Yamakawa; K. Fujiwara; M. Kano; M. Miyajima; Y. Suzuki; T. Maehara; K. Ohta; T. Sasano; M. Matsuura; E. Matsushima

    APSIPA 2013     2013.11

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    DOI: 10.1109/APSIPA.2013.6694225

  92. Heart rate variability features for epilepsy seizure prediction Reviewed

    H. Hashimoto; K. Fujiwara; Y. Suzuki; M. Miyajima; T. Yamakawa; M. Kano; T. Maehara; K. Ohta; T. Sasano; M. Matsuura; E. Matsushima

    APSIPA 2013     2013.10

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    DOI: 10.1109/APSIPA.2013.6694240

  93. Efficient input variable selection for calibration model design Reviewed

    K. Fujiwara; M. Kano

    ASCC 2013     2013.6

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    DOI: 10.1109/ASCC.2013.6606102

  94. Virtual sensing technology in process industries: Trends and challenges revealed by recent industrial applications Reviewed

    M. Kano; K. Fujiwara

    Journal of Chemical Engineering of Japan   Vol. 46 ( 1 ) page: 1-17   2013

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    DOI: 10.1252/jcej.12we167

  95. Input variable selection for PLS modeling using nearest correlation spectral clustering Reviewed

    K. Fujiwara; H. Sawada; M. Kano

    Chemometrics and Intelligent Laboratory Systems   Vol. 118   page: 109-119   2012.8

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    DOI: 10.1016/j.chemolab.2012.08.007

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  96. Development of correlation-based pattern recognition algorithm and adaptive soft-sensor design Reviewed

    K. Fujiwara; M. Kano; S. Hasebe

    Control Engineering Practice   Vol. 20 ( 4 ) page: 371-378   2012.4

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    DOI: 10.1016/j.conengprac.2010.11.013

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  97. Correlation-based spectral clustering for flexible process monitoring Reviewed

    K. Fujiwara; M. Kano; S. Hasebe

    Journal of Process Control   Vol. 21 ( 10 ) page: 1438-1448   2011

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    DOI: 10.1016/j.jprocont.2011.06.023

  98. Development of correlation-based clustering method and its application to software sensing Reviewed

    K. Fujiwara; M. Kano; S. Hasebe

    Chemometrics and Intelligent Laboratory Systems   Vol. 101 ( 2 ) page: 130-138   2010.4

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    DOI: 10.1016/j.chemolab.2010.02.006

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  99. Correlation-based spectral clustering for flexible soft-sensor design Reviewed

    K. Fujiwara; M. Kano; S. Hasebe

    IFAC-PapersOnline   Vol. 9 ( 1 ) page: 703-708   2010

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    DOI: 10.3182/20100705-3-BE-2011.0003

  100. Soft-sensor development using correlation-based just-in-time modeling Reviewed

    K. Fujiwara; M. Kano; S. Hasebe; A. Takinami

    AIChE Journal   Vol. 55 ( 7 ) page: 1754-1765   2009.7

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    DOI: 10.1002/aic.11791

  101. 相関型 Just-In-Time モデリングによるソフトセンサの設計 Reviewed

    藤原幸一, 加納学, 長谷部伸治

    計測自動制御学会論文集   Vol. 44 ( 4 ) page: 317-324   2008.4

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    DOI: 10.9746/ve.sicetr1965.44.317

  102. Correlation-based Just-In-Time modeling for soft-sensor design Reviewed

    K. Fujiwara; M. Kano; S. Hasebe

    Computer Aided Chemical Engineering   Vol. 25   page: 471-476   2008

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    DOI: 10.1016/S1570-7946(08)80083-1

  103. ウェーブレット解析を用いたバッチプロセス操作プロファイルの最適化 Reviewed

    藤原幸一;加納学;長谷部伸治;大野弘

    計測自動制御学会論文集   Vol. 42 ( 10 ) page: 1143-1149   2006.10

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    DOI: 10.9746/sicetr1965.42.1143

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  104. 運転データに基づく階層型品質改善システムの開発 : 品質制御のための操作変数選択 Reviewed

    藤原幸一, 加納学, 長谷部伸治, 大野弘

    計測自動制御学会論文集   Vol. 42 ( 8 ) page: 909-915   2006.8

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    DOI: 10.9746/sicetr1965.42.909

  105. 運転データに基づく品質改善のための定性的品質情報の定量化 Reviewed

    加納学;藤原幸一;長谷部伸治;大野弘

    計測自動制御学会論文集   Vol. 42 ( 8 ) page: 902-908   2006.8

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    DOI: 10.9746/sicetr1965.42.902

    J-GLOBAL

  106. Operation profile optimization for batch process through wavelet analysis and multivariate analysis Reviewed

    M. Kano; K. Fujiwara; S. Hasebe; H. Ohno

    SICE-ICASE 2006     2006

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    DOI: 10.1109/SICE.2006.314647

  107. Product quality improvement using multivariate data analysis Reviewed

    M. Kano; K. Fujiwara; S. Hasebe; H. Ohno

    IFAC-PapersOnline   Vol. 16   page: 175-180   2005

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    Language:English   Publishing type:Research paper (scientific journal)  

    DOI: 10.3182/20050703-6-CZ-1902.01708

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Books 4

  1. 日経バイオテク連載「ヘルスケアにAIは貢献できるか」:心拍変動からてんかん発作を予知するAIをつくる

    藤原幸一( Role: Sole author)

    日経BP  2020.11 

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    Language:English

  2. Epilepsy

    藤原 幸一( Role: Contributor ,  特集記事1)

    メディカルレビュー社  2017.11 

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    Language:English

  3. 車載テクノロジー2017年4月号

    藤原 幸一( Role: Contributor ,  特集記事)

    情報機構  2017.4 

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    Language:English

  4. ウェアラブルセンシング最新動向~電源・材料の開発から医療ヘルスケア分野への応用および次世代センシング技術

    藤原 幸一( Role: Joint author ,  第5章)

    情報機構  2016.5 

MISC 28

  1. Over- and Under-sampling Approach for Extremely Imbalanced and Small Minority Data Problem in Health Record Analysis. Reviewed

    Fujiwara K, Huang Y, Hori K, Nishioji K, Kobayashi M, Kamaguchi M, Kano M

    Frontiers in public health   Vol. 8   page: 178   2020

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    DOI: 10.3389/fpubh.2020.00178

    PubMed

  2. Development of a Sleep Apnea Detection Algorithm Using Long Short-Term Memory and Heart Rate Variability. Reviewed International journal

    Ayako Iwasaki, Chikao Nakayama, Koichi Fujiwara, Yukiyoshi Sumi, Masahiro Matsuo, Manabu Kano, Hiroshi Kadotani

    Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference   Vol. 2019   page: 3964 - 3967   2019.7

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    Sleep apnea syndrome (SAS) is a prevalent disorder which causes daytime fatigue with the increased risk of lifestyle diseases. A large number of patients are undiagnosed and untreated partly because of the difficulty in performing its gold standard test, polysomnography (PSG). In this research, we propose a simple screening method utilizing heart rate variability (HRV) and long short-term memory (LSTM) which is a kind of neural network techniques. The result of applying this algorithm to clinical data demonstrates that it can discriminate between patients and healthy people with high sensitivity (100%) and specificity (100%).

    DOI: 10.1109/EMBC.2019.8856463

    PubMed

  3. サポートベクターマシンに基づいた変数重要度による手首アクチグラフによる週末の寝だめ有無の推定および要因検討 International journal

    後藤 有貴, 藤原 幸一, 角 幸頼, 松尾 雅博, 加納 学, 角谷 寛

    日本睡眠学会定期学術集会プログラム・抄録集   Vol. 44回   page: 284 - 284   2019.6

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  4. ウェーブレット・シンクロスクイージング変換とランダムアンダーサンプリングによる高精度睡眠紡錘波検出アルゴリズムの開発 International journal

    藤原 幸一, 木下 貴文, 角 幸頼, 松尾 雅博, 角谷 寛, 加納 学

    日本睡眠学会定期学術集会プログラム・抄録集   Vol. 44回   page: 279 - 279   2019.6

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  5. Emotional Contagion From Humans to Dogs Is Facilitated by Duration of Ownership. Reviewed

    Katayama M, Kubo T, Yamakawa T, Fujiwara K, Nomoto K, Ikeda K, Mogi K, Nagasawa M, Kikusui T

    Frontiers in psychology   Vol. 10   page: 1678   2019

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    Language:English  

    DOI: 10.3389/fpsyg.2019.01678

    PubMed

  6. Sleep Apnea Detection by Combining Long Short-Term Memory and Heart Rate Variability International journal

    IWASAKI Ayako, NAKAYAMA Chikao, FUJIWARA Koichi, SUMI Yukiyoshi, MATSUO Masahiro, KANO Manabu, KADOTANI Hiroshi

    Proceedings of the Annual Conference of JSAI   Vol. 2019 ( 0 ) page: 1H4J1303 - 1H4J1303   2019

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    Language:Japanese   Publisher:The Japanese Society for Artificial Intelligence  

    <p>Sleep apnea syndrome (SAS) is a prevalent disorder which causes daytime fatigue with increased risk of cardiovascular diseases. A large number of patients are undiagnosed and untreated partly because of the difficulty in performing its gold standard test, polysomnography (PSG). In this research, we propose a simple screening method utilizing heart rate variability (HRV) and long short-term memory (LSTM) which is a kind of the neural network techniques. The result of applying this algorithm to clinical data demonstrates that it can discriminate between patients and healthy people with sensitivity (100%) and specificity (100%).</p>

    DOI: 10.11517/pjsai.JSAI2019.0_1H4J1303

    CiNii Article

    J-GLOBAL

  7. Analysis of VNS Effect on EEG Connectivity with Granger Causality and Graph Theory Reviewed International journal

    T. Uchida, K. Fujiwara, T. Inoue, Y. Maruta, M. Kano, M. Suzuki

    APSIPA ASC 2018     2018.11

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  8. Denoising Autoencoder-based Modification of RRI data with Premature Ventricular Contraction for Precise Heart Rate Variability Analysis Reviewed International journal

    S. Miyatani, K. Fujiwara, M. Kano

    IEEE EMBC 2018     2018.7

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  9. Deniosing Autoencoder-based Modification of RRI data with Premature Ventricular Contraction for Precise Heart Rate Variability Analysis. Reviewed

    Miyatani S, Fujiwara K, Kano M

    Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference   Vol. 2018   page: 5018-5021   2018.7

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    DOI: 10.1109/EMBC.2018.8513218

    PubMed

  10. RRI Modification by Integrating of the Combination of Singular Spectrum Analysis and Denoising Autoencoder and its Application to Open Data International journal

    宮谷将太, 藤原幸一, 加納学

    システム制御情報学会研究発表講演会講演論文集(CD-ROM)   Vol. 62nd   page: ROMBUNNO.137‐7   2018.5

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    J-GLOBAL

  11. Optimization of channel structure and operating condition of neuroprotective focal brain cooling device International journal

    阿部拓斗, 井上貴雄, 藤原幸一, 野村貞宏, 井本浩哉, 鈴木倫保, 加納学

    システム制御情報学会研究発表講演会講演論文集(CD-ROM)   Vol. 62nd   page: ROMBUNNO.212‐6   2018.5

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    J-GLOBAL

  12. Design of false heart rate feedback system for improving game experience Reviewed International journal

    Sayaka Ogawa, Koichi Fujiwara, Toshitaka Yamakawa, Erika Abe, Manabu Kano

    2018 IEEE International Conference on Consumer Electronics, ICCE 2018   Vol. 2018-January   page: 1 - 4   2018.3

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    © 2018 IEEE. When players are excited by playing a video game, corresponding physiological responses such as sweating or changes in heart rate may appear. It is assumed that presenting physiological responses during game play to players in real-time alters their game experience even when they play the same game. Based on this assumption, this work investigated the effect of false heart rate (HR) feedback on game experience through experiments using a simple action game. Our experimental results indicated that false HR feedback not only prevented the players from becoming tired of the game but also enhanced players' experiences. In addition, a new game controller that can present HR information audibly and tactually was developed for realizing a game system based on false HR feedback.

    DOI: 10.1109/ICCE.2018.8326254

    Scopus

  13. Accurate softsensor development by nearest corrleation based-variable weighting International journal

    藤原幸一, 加納学

    計測自動制御学会制御部門マルチシンポジウム(CD-ROM)   Vol. 5th   page: ROMBUNNO.Sa41‐4   2018.3

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    J-GLOBAL

  14. Comparison of causal inference methods for time series data of nonlinear systems International journal

    和田拓也, 藤原幸一, 加納学

    計測自動制御学会制御部門マルチシンポジウム(CD-ROM)   Vol. 5th   page: ROMBUNNO.Fr43‐3   2018.3

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    J-GLOBAL

  15. Causal analysis based on non-time-series kernel Granger causality in a steelmaking process Reviewed International journal

    Ryosuke Sato, Koichi Fujiwara, Masahiro Tani, Junichi Mori, Junji Ise, Kohhei Harada, Manabu Kano

    2017 Asian Control Conference, ASCC 2017   Vol. 2018-January   page: 1778 - 1782   2018.2

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    © 2017 IEEE. In the manufacturing industry, it is extremely important to identify variables that affect product quality. Identifying variables which affect quality variables is called causal analysis. In batch processes, time-series data of process variables and the corresponding data of quality variables are generally acquired. Since causal analysis using the raw data needs a large computation load, it is often performed after compressing time-series process variables data into non-time-series feature variables data. Various causal analysis methods using such data have been developed, however, none have shown effective results in actual plants. In the present work, non-time-series kernel Granger causality (NTS-KGC) is proposed for causal analysis with non-time-series data of batch processes. This is a method that kernel Granger causality [1], which is used for causal analysis with time-series data in nonlinear systems, is expanded for causal analysis with non-time-series data. The validity of the proposed method is demonstrated through a numerical example of a nonlinear batch process. In addition, we conducted a case study of applying NTS-KGC to data obtained from a real steelmaking process. The results demonstrate that NTS-KGC is superior to other existing methods using the following indexes, i.e. variable influence on projection (VIP) of partial least squares (PLS), regression coefficients of PLS, and variable importance of Random Forest.

    DOI: 10.1109/ASCC.2017.8287443

    Scopus

  16. CFD-Based Design of Focal Brain Cooling System for Suppressing Epileptic Seizures International journal

    Kei Hata, Takuto Abe, Takao Inoue, Koichi Fujiwara, Takatomi Kubo, Toshitaka Yamakawa, Sadahiro Nomura, Hirochika Imoto, Michiyasu Suzuki, Manabu Kano

    Computer Aided Chemical Engineering   Vol. 44   page: 2089 - 2094   2018.1

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    © 2018 Elsevier B.V. Epilepsy is a group of neurological disorders which is caused by excessive neuronal activities in cerebrum and characterized by recurrent seizures. A quarter of patients have intractable epilepsy and do not become seizure-free with medication. We are developing an implantable and wearable focal brain cooling system, which enables the patients to lead ordinary daily life. The system cools the epileptic focus, where the excessive neuronal activities begin, by delivering cold saline to a cranially implanted cooling device. In this research, we developed a whole system model through the first principles and animal experiments. The results of system design have shown that a cooling device with more complex channel structure achieves higher temperature uniformity in the brain with lower flow rate of saline. The optimal structure was derived by taking account of the trade-off between pressure drop and temperature uniformity. In addition, the results have demonstrated that the cooling duration is less than 10 minutes for the average temperature 2 mm below the cooling device (inside the brain) to reach 25 °C; it is short enough to cool the brain after seizure is predicted by existing electroencephalogram (EEG)-based algorithms. Moreover, the frequency of battery charging would be once in several days for most patients.

    DOI: 10.1016/B978-0-444-64241-7.50343-8

    Scopus

  17. Nearest Correlation-Based Input Variable Weighting for Soft-Sensor Design. Reviewed

    Fujiwara K, Kano M

    Frontiers in chemistry   Vol. 6   page: 171   2018

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    DOI: 10.3389/fchem.2018.00171

    PubMed

  18. Generalized epileptic seizure prediction based on HRV analysis and its mechanism consideration International journal

    SAKANE FUMIYA, Fujiwara Koichi, Miyajima Miho, Suzuki Yoko, Yamakawa Toshitaka, Kano Manabu, Maehara Taketoshi

    Transactions of Japanese Society for Medical and Biological Engineering   Vol. 56 ( 0 ) page: S59 - S59   2018

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    Language:Japanese   Publishing type:Article, review, commentary, editorial, etc. (international conference proceedings)   Publisher:Japanese Society for Medical and Biological Engineering  

    &lt;p&gt;The present study aims to predict generalized seizures based on heart rate variability (HRV) analysis and multivariate statistical process control (MSPC). We applied the existing anomaly monitoring algorithm, i.e. HRV-based MSPC developed by Fujiwara et al. to 17 pre-ictal episodes and 74 inter-ictal episodes whose total length were about 63 hours. Consequently, the sensitivity and the false positive rate were 76.5% and 1.39 times per hour respectively, and the proportion of duration under false alarms was 5.96%. These results suggest that generalized seizures may be predicted by analyzing HRV. Based on the previous research, we hypothesize that the change in the autonomic nervous activity induce generalized epileptic seizures.&lt;/p&gt;

    CiNii Article

  19. 中大脳動脈閉塞ラットモデルを用いた心拍変動解析による脳卒中早期検知システム実現性の検証 International journal

    藤原幸一, 鎌田啓輔, 児玉智信, 加納学, 村山雄一, 結城一郎

    計測自動制御学会システム・情報部門学術講演会講演論文集(CD-ROM)   Vol. 2017   page: ROMBUNNO.SS05‐9   2017.11

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    J-GLOBAL

  20. 心拍変動解析と多変量統計的プロセス管理による全般性てんかん発作予測 International journal

    坂根史弥, 藤原幸一, 宮島美穂, 鈴木陽子, 山川俊貴, 加納学, 前原健寿

    計測自動制御学会システム・情報部門学術講演会講演論文集(CD-ROM)   Vol. 2017   page: ROMBUNNO.SS05‐7   2017.11

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  21. 次第に速くなる心拍音提示によるゲーム体験の向上 International journal

    小川紗也加, 藤原幸一, 山川俊貴, 阿部恵里花, 加納学

    計測自動制御学会システム・情報部門学術講演会講演論文集(CD-ROM)   Vol. 2017   page: ROMBUNNO.SS05‐12   2017.11

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  22. 睡眠時無呼吸症候群患者における持続陽圧呼吸療法の心拍への短期的効果 International journal

    藤原幸一, 仲山千佳夫, 松尾雅博, 加納学, 角谷寛

    計測自動制御学会システム・情報部門学術講演会講演論文集(CD-ROM)   Vol. 2017   page: ROMBUNNO.SS05‐8   2017.11

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    J-GLOBAL

  23. Validation of HRV-Based Drowsy-Driving Detection Method with EEG Sleep Stage Classification Reviewed International journal

    T. Yamakawa, K. Fujiwara, T. Hiraoka, M. Kano, Y. Sumi, F. Masuda, M. Matsuo, H. Kadotani

    Proc. of World Sleep Congress     2017.10

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  24. てんかん発作抑制を目指した局所脳冷却システムの設計 International journal

    畑啓, 藤原幸一, 加納学, 井上貴雄, 野村貞宏, 井本浩哉, 鈴木倫保

    化学工学会秋季大会研究発表講演要旨集(CD-ROM)   Vol. 49th   page: ROMBUNNO.S307   2017.9

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  25. A new infarction detection method based on heart rate variability in rat middle cerebral artery occlusion model Reviewed International journal

    Tomonobu Kodata, Keisuke Kamata, Koichi Fujiwara, Manabu Kano, Toshiki Yamakawa, Ichiro Yuki, Yuichi Murayama

    Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS   Vol. 2017   page: 3061 - 3064   2017.9

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    © 2017 IEEE. Objective: The present study proposes a cerebral infarction detection algorithm based on heart rate variability (HRV). Methods: It has been reported that infarction affects HRV. Therefore, infarction could be detected at an acute stage by monitoring HRV. This study uses multivariate statistical process control (MSPC), which is a well-known anomaly monitoring method. HRV data shortly after infarction onsets are collected by using the middle cerebral artery occlusion (MCAO) model in rats. This study prepares 11 MCAO-operated rats and 11 sham-operated rats. Three sham-operated rats' data are used for model construction of MSPC, and the other 19 rats' data are used for its validation. Results: The sensitivity and specificity of the proposed algorithm were 82 % and 75 %, respectively. Conclusion: An infarction onset could be detected at an acute stage by monitoring HRV.

    DOI: 10.1109/EMBC.2017.8037503

    Scopus

    PubMed

  26. Design of focal brain cooling system for suppressing epileptic seizures Reviewed International journal

    Kei Hata, Koichi Fujiwara, Manabu Kano, Takao Inoue, Sadahiro Nomura, Hirochika Imoto, Michiyasu Suzuki

    Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS   Vol. 2017   page: 283 - 286   2017.9

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    © 2017 IEEE. Epilepsy is a group of diseases caused by excessive neuronal activities, and one-quarter of the patients do not become seizure-free by the existing treatments. The potential treatments include focal brain cooling, which aims to cool the region where the excessive neuronal activities begin. We are developing a focal brain cooling system. The system delivers cold saline to a cranially implanted cooling device. The outflow is cooled by a Peltier device and pumped for circulation. The Peltier device and the pump are activated only when a seizure is predicted. In this research, the length of time for cooling the brain was calculated with a computational fluid dynamics (CFD)-based model of the focal brain cooling system. As a result, it takes less than 10 minutes for the average temperature 2 mm below the cooling device to reach 25.0 °C. It is much shorter than the time from seizure prediction to seizure onset when an existing algorithm for prediction is used.

    DOI: 10.1109/EMBC.2017.8036817

    Scopus

    PubMed

  27. Development of correlation-based process characteristics visualization method and its application to fault detection Reviewed International journal

    Koichi Fujiwara, Manabu Kano

    IEEE International Conference on Control and Automation, ICCA     page: 940 - 945   2017.8

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    © 2017 IEEE. Although process monitoring is important for maintaining safety and product quality, it is difficult to understand process characteristics particularly when they are changing. Since the correlation among variables changes due to changes in process characteristics, process data visualization based on the correlation among variables helps process characteristic understanding. In the present work, a new correlation-based data visualization method is proposed by integrating joint decorrelation (JD) and stochastic proximity embedding (SPE). JD is a blind source separation (BSS) method that can separates sample based on the correlation, and SPE is a self-organizing algorithm that can map high-dimensional data to a two-dimensional plane. The proposed method, referred to as JD-SPE, separates samples based on the correlation using JD and the separated samples are visualized in the two-dimensional plane by SPE. Correlation matrices have to be constructed before sample separation for JD; however how to construct them is not clear. The present work also proposes a correlation matrix construction method for JD by using nearest correlation spectral clustering (NCSC), which is a correlation-based clustering method. In addition, a new process monitoring method based on multivariate statistical process control (MSPC) which is a well-known process monitoring algorithm and JD-SPE. This monitoring method is referred to as JD-SPE-r2. The proposed JD-SPE-Γ2 can detect a fault that can not detected by the conventional MSPC. The usefulness of the proposed methods is demonstrated through numerical examples.

    DOI: 10.1109/ICCA.2017.8003187

    Scopus

  28. 心拍変動解析と多変量統計的プロセス管理に基づく全般性てんかん発作予測 International journal

    坂根史弥, 藤原幸一, 宮島美穂, 鈴木陽子, 山川俊貴, 加納学, 前原健寿

    システム制御情報学会研究発表講演会講演論文集(CD-ROM)   Vol. 61st   page: ROMBUNNO.134‐2   2017.5

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Presentations 23

  1. 医学と工学の垣根を越えた医療AI開発 Invited

    藤原幸一

    マイクロソフトDeep Learning Lab Healthcare Day 2021 ~医療 x AI への参入障壁を乗り越える~  2021.2.20 

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  2. AI/IoTによるソーシャルディスンス社会におけるヒトのセンシング Invited

    藤原幸一

    名古屋大学高等研究院ウェビナー  2020.6.2 

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    Language:English   Presentation type:Public lecture, seminar, tutorial, course, or other speech  

  3. IoTシステム設計において考慮すべきこと Invited

    藤原幸一

    化学工学会第51回Continuing Educationシリーズ講習  2020.1.21 

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  4. 新たなてんかんケアの可能性~てんかん発作予知システムの開発 Invited

    藤原 幸一

    名古屋大学医学部市民公開講座  2019.12.1 

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    Language:Japanese   Presentation type:Oral presentation (invited, special)  

  5. 医療AI開発とその活用 〜てんかん発作予知を例に Invited

    藤原 幸一

    第39回医療情報学連合大会企画カンファレンス  2019.11.22 

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    Language:English   Presentation type:Symposium, workshop panel (nominated)  

  6. 人工知能で測れないものを測る Invited

    藤原 幸一

    天白高校・出前授業  2019.11.7 

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  7. 心拍変動解析を用いたてんかん発作予知・検知技術の開発 Invited

    藤原 幸一

    名古屋大・聖隷浜松合同カンファレンス  2019.10.5 

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  8. Closed-Loop てんかんケアの実現に向けたてんかん発作予知アルゴリズムの開発 Invited

    藤原 幸一

    電子情報通信学会ソサイエティ大会  2019.9.12 

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    Language:Japanese   Presentation type:Public lecture, seminar, tutorial, course, or other speech  

  9. AI/IoT を活用した新たなてんかん治療法の開発 Invited

    藤原 幸一

    名古屋大学医学部脳とこころの研究センタ・サマースクール  2019.7.17 

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    Language:Japanese   Presentation type:Public lecture, seminar, tutorial, course, or other speech  

  10. 医学における AI の活用てんかん・睡眠障害を例に Invited

    藤原 幸一

    東京医科歯科大学脳機能外科セミナー  2019.7.2 

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    Language:Japanese   Presentation type:Public lecture, seminar, tutorial, course, or other speech  

  11. 医療AI人材とか何か〜てんかん・睡眠障害のモニタリングAIの開発を例に Invited

    藤原 幸一

    日本睡眠学会医師向けセミナー  2019.6.27 

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  12. MATLABを用いた医療機器ソフトウェア開発心拍変動解析とてんかん発作予知 Invited

    藤原 幸一

    MATALB Expo 2019  2019.5.28 

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  13. 若手研究者による講演 Invited

    藤原 幸一

    JSPS卓越研究員事業説明会  2019.3.2 

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    Language:Japanese   Presentation type:Public lecture, seminar, tutorial, course, or other speech  

  14. 医療×AIシンポジウム -医療×AI推進人材を考える Invited

    藤原 幸一

    日本マイクロソフトDeep Learning Lab  2019.2.10 

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    Language:English   Presentation type:Public lecture, seminar, tutorial, course, or other speech  

  15. スモールデータ解析でAIに勝つ〜データ解析を活用した医療機器開発 Invited

    藤原 幸一

    ものづくり企業に役立つ応用数理手法の研究会  2018.12.12 

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    Language:Japanese   Presentation type:Public lecture, seminar, tutorial, course, or other speech  

  16. ウェアラブル心拍変動センサを用いたてんかん発作予測システムの開発 Invited

    藤原 幸一

    第52回日本てんかん学会学術集会  2018.10.27 

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    Language:English   Presentation type:Symposium, workshop panel (nominated)  

  17. スモールデータでAIに勝つ~てんかん発作予知を例に Invited

    藤原 幸一

    鉄鋼協会産学若手交流セミナー  2018.9.8 

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    Language:English   Presentation type:Public lecture, seminar, tutorial, course, or other speech  

  18. リアルタイム心拍変動解析を用いたヘルスモニタリング Invited

    藤原 幸一

    京都大学テックフォーラム  2017.11.6 

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    Language:English   Presentation type:Public lecture, seminar, tutorial, course, or other speech  

  19. 心拍変動を用いた入眠検出 Invited

    藤原 幸一

    第24回日本時間生物学会学術大会シンポジウム  2017.10.29 

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    Language:Japanese   Presentation type:Symposium, workshop panel (nominated)  

  20. 心拍変動解析と機械学習を用いたてんかんアラーム〜スモールデータ解析でAIに勝つ, Invited

    藤原 幸一

    市村学術賞受賞記念講演  2017.9.6 

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    Language:English   Presentation type:Oral presentation (invited, special)  

  21. 人と人をつなぐテクノロジ Invited

    藤原 幸一

    七尾市青年会議所公開授業  2017.9.5 

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    Language:Japanese   Presentation type:Public lecture, seminar, tutorial, course, or other speech  

  22. 熱中症アラーム開発の取り組み - 2020年に向けて Invited

    藤原 幸一

    鹿児島県西之表市「スマートエコアイランド種子島」シンポジウム  2017.3.8 

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    Language:Japanese   Presentation type:Public lecture, seminar, tutorial, course, or other speech  

  23. 報道と研究 - 現場から

    藤原 幸一

    新聞労連研修会  2017.1.21 

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    Language:Japanese   Presentation type:Symposium, workshop panel (nominated)  

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Research Project for Joint Research, Competitive Funding, etc. 18

  1. 非専門医によるてんかん診療質向上のための診療支援AI基盤の創出

    2018.10 - 2022.9

    さきがけ 

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    Grant type:Competitive

  2. 牧誠記念研究助成

    2020.6

  3. てんかん発作オンデマンド介入のための発作予測システムの開発

    2018.12 - 2019.3

    平成30年度第2回医療分野の研究開発関連の調整費 

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    Grant type:Competitive

  4. 卓越研究員研究費

    2018.11 - 2020.3

    卓越研究員制度 

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    Grant type:Competitive

  5. 非専門医のてんかん診療の質改善のためのてんかん診療支援クラウドAIの開発

    2018.1 - 2018.12

    国内共同研究 

  6. 保健医療用人工知能の技術革新と国際競争力向上に資する人材育成に関する研究

    2017.10 - 2019.3

    厚生労働省科学研究費補助金 

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    Grant type:Competitive

  7. ロバスト主成分分析を用いたてんかん発作予知システムの実用化研究

    2017.10 - 2018.9

    国内共同研究 

  8. てんかん発作オンデマンド介入のための発作予測システムの開発

    2017.8 - 2020.3

    先端計測分析技術・機器開発プログラム 

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    Grant type:Competitive

  9. クラウド型てんかん発作診療支援AIの開発

    2017.8 - 2018.7

    国内共同研究 

  10. ウェアラブルセンシングと人工知能の融合によるクラウドてんかん発作診療支援システムの開発

    2017.4 - 2020.3

    国内共同研究 

  11. 夜間・休日を含む小児救急医療体制の最適化及び情報発信方法に関する研究

    2017.4 - 2019.3

    厚生労働省科学研究費補助金 

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    Grant type:Competitive

  12. 心拍変動解析と機械学習の融合による脳卒中検知システムの基盤技術開発

    2017.4 - 2019.3

    国内共同研究 

  13. 心拍変動解析と機械学習に基づいた熱中症発症予測アルゴリズム構築

    2016.4 - 2017.3

    国内共同研究 

  14. PLSと構造正則化に基づいた高精度溶銑温度予測モデルの開発

    2015.12 - 2017.11

    国内共同研究 

  15. 自動車運転中に特化したてんかん発作兆候監視システム開発およびインタフェース設計

    2014.10 - 2016.9

    国内共同研究 

  16. 心拍変動解析によるてんかん発作早期予知デバイスの開発

    2014.4 - 2015.3

    国内共同研究 

  17. 心拍変動に基づくてんかん発作兆候検知システムの構築

    2014.1 - 2014.12

    国内共同研究 

  18. ネックレス型心拍数ワイヤレス計測デバイスを用いた小型・低コストな車載用居眠り検知システムの基盤技術開発

    2012.10 - 2014.3

    A-Step シーズ顕在化タイプ 

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    Grant type:Competitive

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KAKENHI (Grants-in-Aid for Scientific Research) 10

  1. Fundamental development of physiological measurement and analysis platform toward 2nd-generation healthcare IoT technology

    Grant number:21H03855  2021.4 - 2025.3

    Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (B)

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    Authorship:Coinvestigator(s) 

  2. Identifying modifiable factors for cognitive decline: using multimodal biological data.

    Grant number:21H03851  2021.4 - 2025.3

    Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (B)

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    Authorship:Coinvestigator(s) 

  3. Development of Heat Stroke Alert System by Wearable Device

    Grant number:19H04501  2019.4 - 2023.3

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    Authorship:Principal investigator 

    Grant amount:\15990000 ( Direct Cost: \12300000 、 Indirect Cost:\3690000 )

  4. Wide-band ECoG analysis for establishing epilepsy detection and prediction system based on ECG algorithm

    Grant number:19K09475  2019.4 - 2022.3

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    Authorship:Coinvestigator(s) 

  5. AIによる、教育と医療で共有可能なADHDスクリーニング及び治療適正化方法の開発

    Grant number:18K10960  2018.4 - 2022.3

    阪上 由子

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    Authorship:Coinvestigator(s) 

    ADHD(注意欠陥多動性障害)の症状評価は質問票を用いた評価が主であるが、質問閾値の捉え方が評価者により異なり、過大評価に不必要な薬物治療や過小評価による対応不全を招く恐れがあり、教育現場と家庭・医療を単一に客観的指標の構築が急務となっている。単一の客観的指標は治療開始後の効果判定にも有用であり、薬剤の適正使用がより容易となることが期待される。また、ADHD患児の半数で、睡眠に関する問題を認める、特に多動性・衝動性優位型および混合型のサプタイプにおいて器質的な要因による睡眠障害を伴いやすいとの既報はADHDがサブタプごとに異なる病理背景をもち、治療戦略が異なることを示唆するものであり、より適正な治療戦略作成にむけ、行動だけでなく睡眠を含めた客観的評価ツールが必要である。本研究においては学年ごとに活動量の標準化を行うことで個々の集団での特性性を定量化し、より普遍的でエビデンスに基づくADHDスクリーニング法を作成する。
    <BR>
    上記目的のために、今年度は昼夜を問わず行動を記録し、「行動量」「睡眠時間」などを客観的に定量可能であることが研究分担者の穿孔研究により実証されているウエラブル小型行動計測計を購入した。ADHDの診断を補助するアルゴリズムの開発にむけ、学童期の一般標準データの作成に向けた準備を行った。
    具体的には上記研究目的やその方法(小学校の各学年30名、合計360名を対象に同計測計を1週間連続装着することで行動・睡眠記録を行う)について、協力校を確保し、今年度の実施に向け、学内倫理員会の承認を得た。
    研究協力校を確保し、今年度中の実施に向けて学内倫理委員会で研究計画の承認も得たが、開始直前にコロナの流行拡大による長期の臨時休校となり、実施開始時期の目途が立たない状態となっているため。
    学校再開のめどがたち次第、学童期の一般標準データの作成に向け、対象児童のリクルートを行い、ウエアラブル小型行動計測計を用いた「行動量」「睡眠行動」に関するデータの蓄積・評価を行う。また、それと併行して当院小児科(発達外来)に通院中の注意欠陥多動性障害を対象に同計測計による「行動量」「睡眠行動」に関するデータ緒蓄積し、学童期の一般標準データと複数の特徴量の比較から行動・睡眠特性を網羅的に把握し、ADHD診断を補助するアルゴリズムの開発を行う。

  6. マルチモダリティ生体信号計測によるてんかん発作自動検出および重症度評価技術の確立

    Grant number:18K12141  2018.4 - 2021.3

    宮島 美穂

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    Authorship:Coinvestigator(s) 

    ①心拍変動解析とニューラルネットワークを用いたてんかん発作検知アルゴリズムの構築
    発作予測には心拍変動データが有効であったため、本年は単モダリティであるが有用性が見込まれる心拍変動に基づくアルゴリズムの構築を進めた。
    66名の焦点てんかん患者(男性45名、女性21名、年齢13-67歳)の長時間ビデオ脳波モニタリングデータより、44名の患者における85回の発作を含む、計約270時間分の心拍データを抽出した。約78時間分の発作間欠期データを用いてニューラルネットワークの一種である自己符号化器を学習させ、てんかん発作の事後検出を試みた。発作起始後60秒までの区間における発作検出の性能は、全患者平均で感度は77.6%、誤検出頻度は1.52回/時であった。受信者動作特性(ROC)曲線による曲線下面積(AUC)は0.92と良好であった。なお、同様の手法による、発作15分~発作起始の区間における予知結果は感度75.3%、誤検出頻度は2.49回/時であり、予知と検知を比較すると、感度は同等であるが、検知では誤検出率が低減された。
    ②ウェアラブル心拍モニタリングシステムの開発およびてんかん患者への実装試験
    ソフトウェアとハードウェアを組み合わせた発作検出システムの実装試験を行うてんかん患者を対象とした結合試験については、ミツフジ性の従来型のシャツ型電極で15名、独自開発した多極シャツとアプリを組み合わせたシステムで27名分を実施した。さらに多極コネクタ搭載シャツを用いたプロトタイプ試験を患者9名において実施した。
    心拍以外のモダリティに関するデータ収集、解析について、コロナ禍の影響による多施設連携や患者実装試験の困難さから遅れており、発作の発生自体を検出するアルゴリズムは構築したが、発作型や重症度の診断機能の付加については実施できていない。
    引き続きコロナ禍の影響による多施設連携や患者接触の制限が予想され、2-3年度目に予定していた研究目的の新規計測によるデータ収集や患者実装試験は困難である。診療目的のビデオ脳波モニタリングで得られる検査データの二次利用による発作検知、診断アルゴリズム構築までを中心に行っていく方針である。

  7. Development of Early Lewy Detection and Estimation Report System (ELDER System)

    Grant number:17H00872  2017.4 - 2021.3

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    Authorship:Coinvestigator(s) 

  8. Analysis of regional healthcare-management-system based on monitoring technology

    Grant number:17K01245  2017.4 - 2020.3

    Shimono Ryoko

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    Authorship:Coinvestigator(s) 

    We aim a development of healthcare-management-system for preventing lifestyle related diseases and analyze the plural aspects for effectiveness of implementing monitoring technology and health promotion projects. We proceeded research activities through collaboration with regional player such as medical institutes and local governments for increasing feasibility. In actual, we delivered the analyzed results contributing for project implementation for Specific health checkups and Specific health guidance, for health promotion event, incentive point earning for health behavior and so on.

  9. Microvascular decompression of the rostral ventrolateral medulla for drug-resistant neurogenic hypertension

    Grant number:16K10789  2016.4 - 2020.3

    Hamasaki Tadashi

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    Authorship:Coinvestigator(s) 

    Advances in our understanding of human brain physiology have expanded application of neuromodulation therapy to treat disease symptoms. We constructed an in-house system to investigate whether there is a specific area in the human brain where neurosurgical manipulation may exert an effect on autonomic activities and thereby cause changes in systemic circulation. Forty-one surgeries were recorded and analyzed. Statistical analysis demonstrated sympathetic hyperactivity, hypertension, and tachycardia when the area of the lateral aspect of the ponto-medullary junction in the human brain stem was continuously electrically stimulated for the purpose of monitoring a cranial nerve function during tumor removal. These findings provided physiological evidence showing that there is an autonomic center in the lower brain stem of the human brain. We suggest that the area is a possible target of neuromodulation for disorders with autonomic imbalance including drug-resistant hypertension.

  10. Development of method for predicting effect of VNS on epileptic seizure alleviation

    Grant number:26870314  2014.4 - 2018.3

    Fujiwara Koichi

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    Authorship:Principal investigator 

    Grant amount:\3900000 ( Direct Cost: \3000000 、 Indirect Cost:\900000 )

    Vagus Nerve Stimulation (VNS) is treatment of refractory epilepsy; however, its physiological mechanism has not been fully understood. The mechanism of VNS needs to be investigated in order to avoid ineffective operations. Because an epileptic seizure is caused by the spread of excessive discharge from neurons in the cerebrum, analyzing effects of VNS on EEG would be useful for VNS mechanism investigation. The EEG data of epileptic patients with VNS were analyzed by using Granger Causality (GC) and the graph theory. In addition, a directed graph constructed from those GC values would express neural connection. The result supported the existing hypothesis indicating the bilateral asymmetry of the VNS effect on the brain, and furthermore, it suggested that VNS would increase neural connection between the frontal lobe and other brain regions, and that should control epileptic seizures by keeping patients awake.

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Industrial property rights 13

  1. 熱中症発症検知装置

    藤原幸一, 太田鴻志, 山川俊貴, 久保孝富

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    Applicant:名古屋大学

    Application no:2020-097152  Date applied:2020.6

    Country of applicant:Domestic  

  2. 睡眠時無呼吸症候群判定装置、睡眠時無呼吸症候群判定方法、及び、睡眠時無呼吸症候群判定プログラム

    藤原幸一,仲山千佳夫,岩崎絢子

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    Applicant:国立大学法人京都大学

    Application no:2019-23217  Date applied:2019.6

    Country of applicant:Domestic  

  3. 睡眠時無呼吸症候群判定装置、睡眠時無呼吸症候群判定方法、及び、睡眠 時無呼吸症候群判定プログラム

    藤原 幸一, 仲山 千佳夫, 岩崎 絢子

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    Application no:特願2019-023217  Date applied:2019.2

  4. てんかん発作予測装置、心電指標データの分析方法、発作予測コンピュー タプログラム、モデル構築装置、モデル構築方法、モデル構築コンピュータプログラム

    藤原幸一, 坂根史弥

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    Applicant:京都大学

    Application no:特願2018-181414  Date applied:2018.9

  5. 演算装置、検知装置、演算方法、及び、コンピュータプログラム

    藤原幸一, 宮谷将太

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    Applicant:京都大学

    Application no:特願2018-90592  Date applied:2018.5

  6. 無呼吸識別システム及びコンピュータプログラム

    藤原幸一, 仲山千佳夫, 加納学

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    Applicant:京都大学

    Application no:特願2015-101782  Date applied:2015.5

    Announcement no:特開2016-214491  Date announced:2016.12

    Patent/Registration no:特許6691334  Date registered:2020.4  Date issued:2020.4

  7. 眠気検出方法及び眠気検出装置

    山川俊貴, 藤原幸一, 平岡敏洋, 阿部恵里花

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    Applicant:京都大学

    Application no:特願2014-114093  Date applied:2014.6

    Announcement no:特開2015-226696  Date announced:2015.12

    Patent/Registration no:特許6375496  Date registered:2018.8  Date issued:2018.8

  8. てんかん性発作兆候検知装置、てんかん性発作兆候検知モデル生成装置、てんかん性発作兆候検知方法、てんかん性発作兆候検知モデル生成方法、てんかん性発作兆候検知プログラムおよびてんかん性発作兆候検知モデル生成プログラム

    加納 学, 藤原 幸一

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    Applicant:京都大学

    Application no:特願2013-258494  Date applied:2013.12

    Announcement no:特開2015-112423  Date announced:2015.6

    Patent/Registration no:特許6344912  Date registered:2018.6  Date issued:2018.6

  9. センサ情報解析装置、携帯情報端末間通信制御装置、方法、及びプログラム

    藤原 幸一,竹内考

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    Applicant:日本電信電話株式会社

    Application no:特願2012-152618  Date applied:2012.7

    Announcement no:特開2014-17605  Date announced:2014.1

    Country of applicant:Domestic  

  10. 予測モデル構築装置、方法、及びプログラム、並びに発電量予測装置、及び方法

    藤原 幸一,須山敬之

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    Applicant:日本電信電話株式会社

    Application no:特願2011-240543  Date applied:2011.11

    Announcement no:特開2013-99143  Date announced:2013.5

    Patent/Registration no:特許5661594  Date registered:2014.12 

    Country of applicant:Domestic  

  11. プラント制御情報生成装置及び方法、並びにそのためのコンピュータプログラム

    加納学, 藤原幸一

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    Applicant:京都大学

    Application no:特願2009-151745  Date applied:2009.6

    Announcement no:特開2011-008562  Date announced:2011.1

    Patent/Registration no:特許5457737  Date registered:2014.1 

    Country of applicant:Domestic  

  12. 操作変数選択装置,操作変数選択方法,操作変数選択プログラムおよびそれを記録したコンピュータ読み取り可能な記録媒体

    加納学, 藤原幸一

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    Announcement no:特開2006-323523  Date announced:2006.11

    Country of applicant:Domestic  

  13. 変数決定方法、変数決定装置、プログラム及び記録媒体

    加納学, 藤原幸一

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    Applicant:京都大学

    Announcement no:特開2008-517936  Date announced:2007.5

    Country of applicant:Domestic  

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Teaching Experience (On-campus) 3

  1. 先進プロセス情報学

    2020

  2. 線形代数学1

    2020

  3. システム制御

    2020

Teaching Experience (Off-campus) 4

  1. Programming Practice

    2020.10 Nagoya University)

  2. 先進プロセス情報論

    2019.4 Nagoya University)

  3. Linear Algebra

    2019.4 Nagoya University)

  4. システム制御

    2015.10 名古屋大学,同志社大学)

 

Social Contribution 3

  1. 七尾市鵬学園高校 出前授業

    Role(s):Lecturer

    七尾市青年会議所  2017.9

  2. 京都市立衣笠小学校 出前授業

    Role(s):Lecturer

    京都新聞  ソフィアがやってきた  2016.10

  3. 鹿児島県立種子島高校 出前授業

    Role(s):Lecturer

    西之表市  2016.10

Media Coverage 20

  1. てんかん発作予知AIシステムについて Newspaper, magazine

    日刊ゲンダイ・ヘルスケア  2021.6

  2. てんかん発作予知について TV or radio program

    NHK  NHK World  2020.5

  3. てんかん発作予知について TV or radio program

    NHK  おはよう日本  2020.4

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    Author:Myself 

  4. てんかん発作予知について TV or radio program

    NHK京都局  ニュース 630 京いちにち  2020.3

  5. てんかん発作予知システム開発について Newspaper, magazine

    日本経済新聞  日経新聞夕刊  ライフサポート面  2019.7

  6. イヌがヒトと共感する能力を有していることを実証した研究について Newspaper, magazine

    朝日新聞  朝日新聞夕刊  朝日新聞夕刊  2019.7

  7. 第53回人工知能学会における睡眠時無呼吸症候群スクリーニングアルゴリズムの開発についての発表について Internet

    m3.com  m3.com  2019.6

  8. 日本マイクロソフトDeep Learning Lab 医療×AIシンポジウム 講演紹介 Internet

    m3.com  m3.com  2019.3

  9. スモールデータ解析とてんかん発作予知について Newspaper, magazine

    日本経済新聞  日本経済新聞  かがくアゴラ  2019.2

  10. てんかん発作予知システム開発の紹介 Promotional material

    AMED  AMED事業紹介パンフレット  2019.2

  11. hamonを用いたてんかん発作予知について TV or radio program

    NHK大阪局  NHK関西「ルソンの壺」  2019.1

  12. てんかん学会でのスペシャルセッションでの招待講演について Newspaper, magazine

    CLINIC magazine  CLINIC magazine  2019.1

  13. てんかん発作予知システム開発について Newspaper, magazine

    読売新聞社  読売新聞  社会面  2018.12

  14. 第32回人工知能学会全国大会医療AIセッションのシンポジウムについて Internet

    m3.com  m3.com  2018.6

  15. てんかん発作予知システムについて Newspaper, magazine

    Hello! Docto  Hello! Docto  2018.5

  16. てんかん発作予知システムについて Newspaper, magazine

    日経BP  日経メディカル  2017.12

  17. てんかん発作予知システムに係るAMED班会議について

    京都新聞社  京都新聞  2017.11

  18. てんかん発作予知システムについて Newspaper, magazine

    日経新聞社  日経産業新聞  2017.10

  19. 公益法人新技術開発財団市村賞について Newspaper, magazine

    日経新聞社  日経新聞  2017.4

  20. ニッポンのジレンマ出演 TV or radio program

    NHK  ニッポンのジレンマ  2016.10

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