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Detecting Huntington Patient Using Chaotic Features of Gait Time Series

عنوان مقاله: Detecting Huntington Patient Using Chaotic Features of Gait Time Series
شناسه ملی مقاله: JR_JACR-11-1_003
منتشر شده در در سال 1399
مشخصات نویسندگان مقاله:

Armin Allahverdy - Radiology Department, Allied Faculty, Mazandaran University of Medical Sciences, Sari, Iran
Mahboobeh Golchin - Department of Mathematics, Tehran North Branch, Islamic Azad University, Tehran, Iran

خلاصه مقاله:
Huntington's disease (HD) is a congenital, progressive, neurodegenerative disorder characterized by cognitive, motor, and psychological disorders. Clinical diagnosis of HD relies on the manifestation of movement abnormalities. In this study, we introduce a mathematical method for HD detection using step spacing. We used ۱۶ walking signals as control and ۲۰ walking signals as HD. We took a step back from the walking distance signals. Then, using fractal dimensions and statistical features, the control was classified and HD and ۹۷.۲۲% accuracy were obtained.

کلمات کلیدی:
HD, Gait signal, Stride time interval, fractal dimension, Statistical features

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/1194354/