Detecting Huntington Patient Using Chaotic Features of Gait Time Series
Subject Areas : B. Computer Systems Organization
Armin Allahverdy
1
(Radiology Department, Allied Faculty, Mazandaran University of Medical Sciences, Sari, Iran)
Mahboobeh Golchin
2
(Department of Mathematics, Tehran North Branch, Islamic Azad University, Tehran, Iran)
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.