Application of Sample Entropy of Pulse Waves in Identifying Characteristic Physiological Patterns of Parkinson’s Disease Sufferers

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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.

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Oyama-Higa, M., Niwa, T., Ou, F., & Kawanabe, Y. (2019). Application of Sample Entropy of Pulse Waves in Identifying Characteristic Physiological Patterns of Parkinson’s Disease Sufferers. In Communications in Computer and Information Science (Vol. 1024, pp. 447–463). Springer Verlag. https://doi.org/10.1007/978-3-030-29196-9_23

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