Paper Info
Title
Application of Sample Entropy of Pulse Waves in Identifying Characteristic Physiological Patterns of Parkinson's Disease Sufferers.
Abstract
While there are plenty of studies on clinical diagnosis of Parkinson's disease, little literature is available on the possibility of simple tests that can help distinguish Parkinson's disease sufferers from healthy individuals. In our study, by making use of pulse wave data, we identify physiological patterns characteristic of Parkinson's disease patients. We observe that the sample entropy values of pulse waves, with certain parameters fixed, is statistically different between Parkinson's disease sufferers and healthy individuals. We also find significant difference between the two groups in values of the largest Lyapunov exponent computed from the same pulse wave data. In addition, we introduce an Android tablet that in which the real-time measurement and analysis functions are incorporated. With this device, it takes only 5 s to produce a test result.
Year
DOI
Venue
2018
10.1007/978-3-030-29196-9_23
BIOMEDICAL ENGINEERING SYSTEMS AND TECHNOLOGIES, BIOSTEC 2018
Keywords
Field
DocType
Parkinson's disease,Sample entropy,Border of Parkinson Entropy (BPE),Largest Lyapunov Exponent (LLE),Android tablet for real-time health check
Parkinson's disease,Sample entropy,Pattern recognition,Computer science,Pulse wave,Pulse (signal processing),Clinical diagnosis,Artificial intelligence,Lyapunov exponent,Machine learning
Conference
Volume
ISSN
Citations 
1024
1865-0929
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Mayumi Oyama-Higa13315.63
Tokihiko Niwa200.68
Fumitake Ou300.34
Yoshifumi Kawanabe400.34