Profile

Name

 

 
藤原 幸一 / Koichi FUJIWARA

Greeting

We see the term artificial intelligence (AI) everywhere. Also called the third AI boom, current AIs employ a framework in which machines are made to learn a large amount of correct answer data in order to identify unknown data that were not used for learning. This assumes that a large amount of correct answer data can be obtained at a low cost. For example, there are numerous images of cats on the Internet, and many people append correct answer labels thereto in blogs and social media––that these images are of "cats"––using hashtags. If a large amount of data appended with such correct answer labels are collected from the Internet and a machine is made to learn them, the machine would be able to automatically find cats in images. This is called "collective intelligence," and it is touted that by allowing the learning of a large amount of data, AI performance would transcend human intelligence in the future, and steal work from many people. But, is this true?
 
Big data research is already a red ocean. In the AI industry, those who possess a large amount of data, high-speed computers, and numerous skilled engineers, inevitably win. That is, the AI industry is already a device industry, and a game won according to capital strength. In Japan, where we have not heretofore amply invested in human resources or facilities, it is not possible to catch up with GAFA in the big data realm.

The world of small data is a different story. Small data refers to data whose occurrence itself is rare, such as failure data of a particular device, or whose collection is difficult for ethical reasons, such as clinical data on a particular disease. Furthermore, with small data, there are many cases where the interpretation of the data is difficult for anyone but a limited number of experts, and labeling is also high-cost; only skilled medical doctors and specialist technicians can accurately label abnormal brainwaves.  Therefore, in a research targeting small data, there is great value in cleaning the data, aligning formats, and constructing datasets that can be analyzed. In small data analysis, it is necessary to proactively incorporate, into the modeling, causal relationships behind the data, knowledge on physics and physiology, various case studies, and know-how and tacit knowledge of experts. Considering that such knowledge is created by a small number of experts, it can be seen that AI performance cannot exceed humans in the field of small data, but, at most, approximate the abilities of a small number of experts.

This kind of small data analysis may seem to be ad hoc and unsystematic from the point of view of theoretical research. However, real-world complex problems cannot be solved only with theory, and requires trial and error. In the process of trial and error, known-how on small data analysis is accumulated, and such know-how would becomes systematized together with knowledge from various other domains. Therefore, research on small data is still a wide open blue ocean. 

In our lab, we collect clinical data on patients of epilepsy, sleep disorder, stroke, heat stroke, etc., in collaboration with numerous hospitals and research institutes. From Hokkaido to the north and Okinawa to the south, a network of hospitals and specialists built across Japan, straddling various departments, is our greatest asset. Data that are still lacking are collected by conducting animal and human subject experiments ourselves, and, through their analyses, we are developing diagnostic algorithms and medical devices. Furthermore, through these data analyses, we aim to contribute to basic medicine and physiology, such as elucidating the mechanisms of various diseases.

BIOGRAPHY

March 2004

Graduated from Undergraduate School of Industrial Chemistry, Kyoto University
March 2006

Completed Master's Program in Chemical Engineering, Graduate School of Engineering, Kyoto University
April 2006

Joined Toyota Motor Corporation
April 2007

Started Doctoral Program in Chemical Engineering, Graduate School of Engineering, Kyoto University
April 2008

JSPS Research Fellow, DC2
March 2009

Kyoto University Doctorate (Engineering)
April 2009

JSPS Research Fellow, PD
October 2009

Visiting Researcher, Curtin University, Australia
April 2010

NTT Communication Science Laboratories
July 2012

Assistant Professor, Department of Systems Science, Graduate School of Informatics, Kyoto University
October 2018

JST Sakigake Researcher (Social Systems)
November 2018

Associate Professor, Nagoya University, Graduate School of Engineering, Department of Materials Process Engineering
Part-time lecturer, Tokyo Medical and Dental University; visiting associate professor, Shiga Medical University; visiting associate professor, University of Tokyo; researcher, Kyoto University

Field of Study

Machine learning, biomedical engineering, epileptology, sleep medicine, process systems engineering 

2019 Courses

Linear algebra I (undergraduate) / Control Engineering (undergraduate) / Advanced Process Information Engineering (Graduate)

Affiliated Societies

Japanese Society for Artificial Intelligence・ Japan Epilepsy Society・ The Japanese Society of Sleep Research・ The Society of Instrument and Control Engineers・ The Society of Chemical Engineers, Japan・ IEEE

Achievements

Academic Papers
  1. *C.Nakayama, K.Fujiwara, Y. Sumi, M. Matsuo, M. Kano and H. Kadotani: Obstructive sleep apnea screening by heart rate variability-based apnea/normal respiration discriminant model, Physiological Measurement, https://doi.org/10.1088/1361-6579/ab57be (2019)
  2. M. Katayama, T. Kubo, T. Yamakawa, K. Fujiwara, K. Nomoto, K. Ikeda, K. Mogi, M. Nagasawa and T. Kikusui: Emotional Contagion From Humans to Dogs Is Facilitated by Duration of Ownership, Frontiers in Psychology, https://doi.org/10.3389/fpsyg.2019.01678 (2019)
  3. *K. Fujiwara, E. Abe, K. Kamata, C. Nakayama, Y. Suzuki, T. Yamakawa, T. Hiraoka, M. Kano, Y. Sumi, F. Masuda, M. Matsuo, H. Kadotani: Heart Rate Variability-based Driver Drowsiness Detection and its Validation with EEG, IEEE Transactions on Biomedical Engineering, 66(6), 1769-1778 (2019)
  4. *K. Hata, K. Fujiwara, T. Inoue, T. Abe, T. Kubo, T. Yamakawa, S. Nomura, H. Imoto, M. Suzuki, M. Kano, Epileptic Seizure Suppression by Focal Brain Cooling with Recirculating Coolant Cooling System: Modeling and Simulation, IEEE Transactions on Neural Systems & Rehabilitation Engineering, 27(2), 162-171, 2019
  5. *K. Kamata, K. Fujiwara, T. Kinoshita, M. Kano: Missing RRI Interpolation Algorithm based on Locally Weighted Partial Least Squares for Precise Heart Rate Variability Analysis, Sensors 18(11), 3870 (2018)
  6. T. Hamasaki, M. Morioka, K. Fujiwara, C. Nakayama, M. Harada, K. Sakata, Y. Hasegawa, T. Yamakawa, K. Yamada: A. Mukasa: Is hemifacial spasm affected by changes in the heart rate? - A study using heart rate variability analysis, Clinical Neurophysiology, 129(10), 2205-2214 (2018)
  7. *T. Kodama, K. Kamata, *K. Fujiwara, M. Kano, T. Yamakawa, I. Yuki. Y. Murayama: Schemic stroke detection by analyzing heart rate variability in rat middle cerebral artery occlusion model, IEEE Transactions on Neural Systems & Rehabilitation Engineering, 26(6), 1152-1160, (2018)
  8. *K. Fujiwara and M. Kano: Nearest Correlation-Based Input Variable Weighting for Soft-sensor Design, Frontiers in Chemistry, 6(171), doi:10.3389/fchem.2018.00171 (2018)
  9. 伊部達郎，平岡敏洋，阿部恵里花，藤原幸一，山川俊貴: 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,自動車技術会論文集,48(2), 463-469 (2017)
  10. M. Matsuo, F. Masuda, Y. Sumi, M. Takahashi, N. Yamada, M. H. Ohira, K. Fujiwara, T. Kanemura and H. Kadotani: Comparisons of Portable Sleep Monitors of Different Modalities: Potential as Naturalistic Sleep Recorders, Frontiers in Neurology, 7(110), doi: 10.3389/fneur.2016.00110 (2016)
  11. *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: Epileptic Seizure Prediction Based on Multivariate Statistical Process Control of Heart Rate Variability Features, IEEE Transactions on Biomedical Engineering, 63(6), 1321-1332 (2016)
  12. T. Kanemura, H. Kadotani, M. Matsuo, F. Masuda, K. Fujiwara , M. Ohira and N. Yamada: Evaluation of a Portable Two-channel Electroencephalogram Monitoring System to Analyze Sleep Stages, Journal of Oral and Sleep Medicine, 2(2), 101-108 (2016)
  13. *E. Abe, K. Fujiwara, T. Hiraoka, T. Yamakawa and M. Kano: Development of Drowsiness Detection Method by Integrating Heart Rate Variability Analysis and Multivariate Statistical Process Control, SICE Journal of Control, Measurement, and System Integration, 9(1), 10-17 (2016)
  14. *K. Fujiwara and M. Kano: Efficient Input Variable Selection for Soft-senor Design based on Nearest Correlation Spectral Clustering and Group Lasso, ISA Transactions, 58(9), 367-369 (2015)
  15. T. Miyano, K. Fujiwara, M. Kano, H. Tanabe, H. Nakagawa, T. Watanabe and H. Minami: Efficient wavenumber selection based on spectral fluctuation dividing and correlation-based clustering for calibration modeling, Chemometrics and Intelligent Laboratory Systems, 148(15), 85-94 (2015)
  16. H. Chigira, A. Maeda, M. Kobayashi, K. Fujiwara, T. Hiraoka, A. Tanaka, T. Tanaka: A Study on Heart Rate Monitoring in Daily Life by Using a Surface-Type Sensor, SICE Journal of Control, Measurement, and System Integration, 8(1), 74-78 (2015)
  17. M. Kano and K. Fujiwara: Virtual Sensing Technology in Process Industries: Trends and Challenges Revealed by Recent Industrial Applications, Journal of Chemical Engineering of Japan, 46(1), 1-17 (2013)
  18. *K. Fujiwara, H. Sawada and M. Kano: Input Variable Selection for PLS Modeling Using Nearest Correlation Spectral Clustering, Chemometrics and Intelligent Laboratory Systems, 118(15), 109-119 (2012)
  19. K. Fujiwara, M. Kano and S. Hasebe: Development of Correlation-Based Pattern Recognition Algorithm and Adaptive Soft-Sensor Design, Control Engineering Practice, 20(4), 371-378 (2012)
  20. K. Fujiwara, M. Kano and S. Hasebe: Correlation-based Spectral Clustering for Flexible Process Monitoring, Journal of Process Control, 21(10), 1438-1448 (2011)
  21. K. Fujiwara, M. Kano, and S. Hasebe: Development of Correlation-based Clustering Method and Its Application to Software Sensing, Chemometrics and Intelligent Laboratory Systems, 101(2), 130-138 (2010)
  22. K. Fujiwara, M. Kano and S. Hasebe: Soft-Sensor Development using Correlation-Based Just-In-Time modeling, AIChE Journal, 55(7), 1754-1765 (2009)
  23. 藤原幸一, 加納学, 長谷部伸治:相関型Just-In-Timeモデリングによるソフトセンサの設計, 計測自動制御学会論文集, 44(4), 317-324 (2008)
  24. 藤原幸一, 加納学, 長谷部伸治, 大野弘: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, 計測自動制御学会論文集, 42(10), 1143-1149 (2006)
  25. 藤原幸一, 加納学, 長谷部伸治, 大野弘: 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, 計測自動制御学会論文集, 42(8), 909-915 (2006)
  26. 加納学, 藤原幸一, 長谷部伸治, 大野弘: 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, 計測自動制御学会論文集, 42, 902/908 (2006)

＊Corresponding Author

Conference Proceedings
  1. A. Iwasaki, C. Nakaysma, K. Fujiwara, Y. Sumi, M. Matsuo, M. Kano, H. Kadotani: Development of a Sleep Apnea Detection Algorithm Using Long Short-Term Memory and Heart Rate Variability, IEEE EMBC 2019, Jul 23-27, Berlin (2019)
  1. T. Uchida, K. Fujiwara, T. Inoue, Y. Maruta, M. Kano, and M. Suzuki: Analysis of VNS Effect on EEG Connectivity with Granger Causality and Graph Theory, APSIPA ASC 2018, Nov. 12-15 (2018)
  2. S. Miyatani, K. Fujiwara, and M. Kano: Deniosing Autoencoder-based Modification of RRI data with Premature Ventricular Contraction for Precise Heart Rate Variability Analysis, IEEE EMBC, Jul 17-21, Hawaii (2018)
  3. K. Hata, T. Abe, T. Inoue, K. Fujiwara, T. Kubo, T. Yamakawa, S. Nomura, H. Imoto, M. Suzuki, and M. Kano: CFD-Based Design of Focal Brain Cooling System for Suppressing Epileptic Seizures, PSE World Congress, Jul 1-5, San Diego (2018)
  4. S. Ogawa, K. Fujiwara, E. Abe, T. Yamakawa, and M. Kano: Design of False Heart Rate Feedback System for Improving Game Experience, IEEE ICCE2018, Jan. 12-14, Las Vegas (2018)
  5. R. Sato, K. Fujiwara, M. Tani,J. Mori, J. Ise, K. Harada, and M. Kano: Causal Analysis based onNon-time-series Kernel Granger Causality in a Steelmaking Process, IEEE ASCC2017, Dec.17-20,Gold Coast (2017)
  6. T. Kodama, K. Kamata, K. Fujiwara, M. Kano, T. Yamakawa, I. Yuki, Y. Murayama: A New Infarction Detection Method Based on Heart Rate Variability in Rat Middle Cerebral Artery Occlusion Model, IEEE EMBC2017, Jul. 10-15, Jeju, Korea (2017)
  7. K. Hata, K. Fujiwara, M. Kano, T. Inoue, S. Nomura, H. Imoto, M. Suzuki: Design of Focal Brain Cooling System for Suppressing Epileptic Seizures, IEEE EMBC2017, July. 10-15, Jeju, Korea (2017)
  8. K. Fujiwara, and M. Kano: Development of Correlation-based Process Characteristics Visualization Method and Its Application to Fault Detection, IEEE ICCA2017, Jul. 3-5, Ohrid, Macedonia (2017)
  9. K. Kamata, K. Fujiwara, T. Yamakawa, and M. Kano: Missing RRI interpolation for HRV analysis using Locally-Weighted Partial Least Squares Regression, IEEE EMBC 2016, Aug. 16-20,Orlando, FL (2016)
  10. K. Hata, K. Fujiwara, M. Kano, T. Inoue, S. Nomura, H. Imoto, and M. Suzuki: CFD-based Design of Focal Brain Cooling Device for Preventing Epileptic Seizures, PSE Asia 2016, Jul. 25-27, Tokyo (2016)
  11. Y. Satoyama, K. Fujiwara, and M. Kano: Variable Elimination-based Fault Identification, PSE Asia 2016, Jul. 25-27, Tokyo (2016)
  12. Y. Satoyama, K. Fujiwara, and M. Kano: Variable Elimination-Based Contribution for Accurate Fault Identification, DYCOPS-CAB 2016, Jun. 6-8, Norway (2016)
  13. E. Abe, H. Chigira, K. Fujiwara, T. Yamakawa, and M. Kano: Development of Photoplethysmogram Sensor-embedded Video Game Controller, IEEE ICCE 2016, Jan. 8-11, Las Vegas (2016)
  14. K. Kamata, K. Fujiwara, T. Kodama, M. Kano, T. Yamakawa, N. Kobayashi, and F. Shimizu: Development of Stroke Detection Method by Heart Rate Variability Analysis and Support Vector Machine, APSIPA ASC 2015, Dec. 17-19, Hong Kong (2015)
  15. E. Abe, K. Fujiwara, H. Chigira, T. Yamakawa, K. Kano: Heart Rate Monitoring by Pulse Sensor Embedded Game Controller, APSIPA ASC 2015, Dec. 17-19, Hong Kong (2015)
  16. T. Yamakawa, R. Kinishita, K. Fujiwara, M. Kano, M. Miyajima, T. Sakata, Y. Ueda: Accuracy Comparison of Two Microcontroller-embedded R-wave Detection Methods for Heart-rate Variability Analysis, APSIPA ASC 2015, Dec. 17-19, Hong Kong (2015)
  17. H. Chigira, T. Hori, K. Fujiwara, T. Hiraoka and T. Tanaka: Heart rate monitoring on steering wheel using surface type sensor, ITS World Congress 2015, Bordeaux, France, Oct. 5-9 (2015)
  18. C. Nakayama, K. Fujiwara, M. Matsuo, M. Kano, and H. Kodotani: Development of sleep apnea syndrome screening method by using heart rate variability analysis and support vector machine, IEEE EMBC2015, Aug. 25-19, Milan, Italy (2015)
  19. T. Uchimaru, K. Hazama, K. Fujiwara and M.Kano: Correlation-based Group-wise Selection of Input Variables for PLS Regression and Its Applications to Chemical Processes, SICE Annual Conference 2015, Hangzhou, China, Jul. 28-30 (2015)
  20. T. Uchimaru, K. Hazama, K. Fujiwara and M. Kano: Nearest Correlation Louvain Method for Fast and Good Selection of Input Variables of Statistical Model, ADCHEM 2015, Jun 7-10, Whistler, Canada (2015)
  21. K. Fujiwara and M. Kano: Calibration Model Design based on Weighted Nearest Correlation Spectral Clustering, ASCC2015, May 31-Jun. 3, Kota Kinabalu, Malaysia (2015)
  22. T. Uchimaru, K. Hazama, K. Fujiwara and M. Kano: Efficient Wavenumber Selection Based on Nearest Correlation Louvain Method for NIR Calibration Modeling, ASCC2015, May 31-Jun. 3, Kota Kinabalu, Malaysia (2015)
  23. K. Fujiwara, E. Abe, Y. Suzuki, M. Miyajima, T. Yamakawa, M. Kano, T. Maehara, K. Ohta and T. Sasano: Epileptic Seizure Monitoring by One-Class Support Vector Machine, APSIPA ASC 2014, Dec. 9-12, Siem Reap, Cambodia (2014)
  24. E. Abe, K. Fujiwara, T. Hiraoka, T. Yamakawa, and M. Kano: Development of Drowsy Driving Accident Prediction by Heart Rate Variability Analysis, APSIPA ASC 2014, Dec. 9-12, Siem Reap, Cambodia (2014)
  25. T. Yamakawa, K. Fujiwara, M. Miyajima, E. Abe, M. Kano, and Y. Ueda: Real-Time Heart Rate Variability Monitoring Employing a Wearable Telemeter and a Smartphone, APSIPA ASC 2014, Dec. 9-12, Siem Reap, Cambodia (2014)
  26. H. Hashimoto, K. Fujiwara, S. Yoko, M. Miyajima, T. Yamakawa, M. Kano, T. Maehara, K. Ohta, T. Sasano, M. Matsuura, E. Matsushima: Epileptic Seizure Monitoring by Using Multivariate Statistical Process Control, CAB2013, Mumbai, India, Dec 15-17 (2013)
  27. T. Yamakawa, K. Fujiwara, M. Kano, M. Miyajima, Y. Suzuki, T. Maehara, K. Ohta, T. Sasano, M. Matsuura, E. Matsushima: Development of a Wearable HRV Telemetry System to Be Operated by Non-Experts in Daily Life, APSIPA ASC 2013, Kaohsiung, Taiwan, Oct 29-Nov 1 (2013)
  28. H. Hashimoto, K. Fujiwara, S. Yoko, M. Miyajima, T. Yamakawa, M. Kano, T. Maehara, K. Ohta, T. Sasano, M. Matsuura, E. Matsushima: Heart Rate Variability Features for Epilepsy Seizure Prediction, APSIPA ASC 2013, Kaohsiung, Taiwan, Oct 29-Nov 1 (2013)
  29. K. Fujiwara and M. Kano: Efficient Input Variable Selection for Calibration Model Design, ASCC2013, Istanbul, Turkey, Jun 23-26 (2013)
  30. K. Fujiwara and M. Kano: Input Variable Selection based on the Correlation-based Variable Clustering, IFPAC2013, Baltimore, Maryland, Jan 22-25 (2013)
  31. K. Fujiwara, M. Kano, and S. Hasebe: Correlation-based Spectral Clustering for Flexible Soft-Sensor Design, DYCOPS 2010, Leuven, Belgium, July 5-7 (2010)
  32. K. Fujiwara, M. Kano, and S. Hasebe: Development and Application of a New Spectral Clustering Algorithm, AIChE Annual Meeting, Nashville, US, Nov. 8-13 (2009)
  33. K. Fujiwara, M. Kano, and S. Hasebe: Development of Correlation-Based Pattern Recognition and Its Application to Adaptive Soft-Sensor Design, ICROS-SICE International Joint Conference 2009, Fukuoka, Japan, August 18-21 (2009)
  34. K. Fujiwara, M. Kano and S. Hasebe: Correlation-Based Pattern Recognition and Its Application to Adaptive Soft-Sensor Design, ADCHEM 2009, Istanbul, Turkey, July 12-15 (2009)
  35. K. Fujiwara, Y. Mukai, M. Kano and S. Hasebe: Development of a New Pattern Recognition Method and Its Application to Just-In-Time Modeling, AIChE Annual Meeting, paper688b, Philadelphia, PA, Nov. 16-21 (2008)
  36. K. Fujiwara, M. Kano and S. Hasebe: Soft-sensor design for time-varying processes through correlation-based Just-In-Time modeling, FOCAPO 2008 , Boston, Massachusetts June 29-July 2 (2008)
  37. K. Fujiwara, M. Kano and S. Hasebe: Correlation-based Just-In-Time modeling for soft-sensor design, ESCAPE18, Lyon, France, June 1-4 (2008)
  38. Y. Mukai, K. Tasaka, K. Fujiwara, M. Kano and S. Hasebe: Batch Process Modeling and Optimization through Wavelet Coefficient Regression, PSE Asia 2007, Xi’an, China, Aug. 15-18 (2007)
  39. M. Kano, K. Fujiwara, S. Hasebe and H. Ohno: Modeling and Optimization of Batch Process through Wavelet Analysis and Multivariate Analysis, DYCOPS 8, Cancun, Mexico, June 6-8 (2007)
  40. M. Kano, K. Fujiwara, S. Hasebe and H. Ohno: Modeling and Optimization of Batch Process Operation through Wavelet Analysis and Multivariate Analysis, AIChE2006 Annual Meeting, San Francisco, CA, Nov. 13-17 (2006)
  41. M. Kano, K. Fujiwara, S. Hasebe, and H. Ohno:Operation Profile Optimization for Batch Process through Wavelet Analysis and Multivariate Analysis, SICE-ICASE International Joint Conference 2006, Oct. 18-21, Busan, Korea (2006)
  42. K. Fujiwara, M. Kano, S. Lee, S. Hasebe, and H. Ohno: Hierarchical Control and Monitoring System for Product Quality Improvement, PSE Asia 2005, Seoul, Korea, Aug. 17-19 (2005)
  43. M. Kano, K. Fujiwara, S. Hasebe, and H. Ohno: Product Quality Improvement Using Multivariate Data Analysis, the 16th IFAC World Congress, Prague, Czech Republic, Jul. 3-8 (2005)
  44. M. Kano, K. Fujiwara, S. Hasebe, and H. Ohno: Data-Driven Approach for Product Quality/Yield Improvement: How to Specify Target of Qualitative Quality Variables, AIChE Annual Meeting, Austin, TX, Nov. 7-12 (2004)
  45. M. Kano, K. Fujiwara, S. Hasebe, and H. Ohno: Data-Driven Approach for Product Quality/Yield Improvement: How to Specify Target of Qualitative Quality Variables, the 10th APPChE, Kitakyushu, Japan, Oct. 17-21 (2004)
  46. M. Kano, K. Fujiwara, S. Hasebe, and H. Ohno: Data-Driven Quality Improvement Handling Qualitative Variables, DYCOPS 7, Cambridge, July 5-7 (2004)
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