Detecting Huntington Patient Using Chaotic Features of Gait Time Series

Journal of Advances in Computer Research

مقاله 3، دوره 11، شماره 1 - شماره پیاپی 39، اردیبهشت 2020، صفحه 27-32   

نوع مقاله: Original Manuscript

نویسندگان

Armin Allahverdy^{* 1}؛ Mahboobeh Golchin²

¹Radiology Department, Allied Faculty, Mazandaran University of Medical Sciences, Sari, Iran

²Department of Mathematics, Tehran North Branch, Islamic Azad University, Tehran, Iran

چکیده

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 16 walking signals as control and 20 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 97.22% accuracy were obtained.

کلیدواژه‌ها

HD؛ Gait signal؛ Stride time interval؛ Fractal dimension؛ Statistical features