Detecting Huntington Patient Using Chaotic Features of Gait Time Series

Subject Areas : B. Computer Systems Organization

Armin Allahverdy ¹ , Mahboobeh Golchin ²

1 - Radiology Department, Allied Faculty, Mazandaran University of Medical Sciences, Sari, Iran
2 - Department of Mathematics, Tehran North Branch, Islamic Azad University, Tehran, Iran

Received: 2020-09-13 Accepted : 2020-09-13 Published : 2020-02-01

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

Abstract :

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.