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Authors: Mayumi Oyama-Higa 1 ; Tokihiko Niwa 2 ; Wenbiao Wang 3 and Yoshifumi Kawanabe 4

Affiliations: 1 Chaos Technology Research Laboratory, Japan ; 2 Kwansei Gakuin Senior High School, Japan ; 3 PricewaterhouseCoopers Aarata LLC, Japan ; 4 Shizuoka General Hospital, Japan

Keyword(s): Parkinson’s Disease, Sample Entropy, Border of Parkinson Entropy (BPE), Largest Lyapunov Exponent (LLE), Android Tablet for Real-Time Health Check.

Related Ontology Subjects/Areas/Topics: Biomedical Engineering ; Biomedical Signal Processing ; Cloud Computing ; Devices ; Distributed and Mobile Software Systems ; e-Health ; Health Engineering and Technology Applications ; Health Information Systems ; Human-Computer Interaction ; Mobile Technologies ; Mobile Technologies for Healthcare Applications ; Neural Rehabilitation ; Neurotechnology, Electronics and Informatics ; Physiological Computing Systems ; Platforms and Applications ; Software Engineering ; Wearable Sensors and Systems

Abstract: In this study, we identify characteristic physiological patterns of Parkinson’s disease patients, through analysis of the data of their pulse waves. We find that the sample entropy values of pulse waves, with certain parameters fix (In this case, we define the sample entropy value as “border of Parkinson entropy”, or BPE), is statistically different between Parkinson’s disease sufferers and healthy individuals. In addition, values of the largest Lyapunov exponent computed from the same data are also analysed, and significant difference between the two groups are observed. At the end, we describe an Android tablet that we developed for real-time measurement and analysis of BPE.

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Paper citation in several formats:
Oyama-Higa, M.; Niwa, T.; Wang, W. and Kawanabe, Y. (2018). Identifying Characteristic Physiological Patterns of Parkinson's Disease Sufferers using Sample Entropy of Pulse Waves. In Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2018) - HEALTHINF; ISBN 978-989-758-281-3; ISSN 2184-4305, SciTePress, pages 189-196. DOI: 10.5220/0006627801890196

@conference{healthinf18,
author={Mayumi Oyama{-}Higa. and Tokihiko Niwa. and Wenbiao Wang. and Yoshifumi Kawanabe.},
title={Identifying Characteristic Physiological Patterns of Parkinson's Disease Sufferers using Sample Entropy of Pulse Waves},
booktitle={Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2018) - HEALTHINF},
year={2018},
pages={189-196},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006627801890196},
isbn={978-989-758-281-3},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2018) - HEALTHINF
TI - Identifying Characteristic Physiological Patterns of Parkinson's Disease Sufferers using Sample Entropy of Pulse Waves
SN - 978-989-758-281-3
IS - 2184-4305
AU - Oyama-Higa, M.
AU - Niwa, T.
AU - Wang, W.
AU - Kawanabe, Y.
PY - 2018
SP - 189
EP - 196
DO - 10.5220/0006627801890196
PB - SciTePress