Title of article :
Detecting Huntington Patient Using Chaotic Features of Gait Time Series
Author/Authors :
Allahverdy, Armin Radiology Department - Allied Faculty - Mazandaran University of Medical Sciences, Sari , Golchin, Mahboobeh Department of Mathematics - Tehran North Branch - Islamic Azad University, Tehran
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.
Keywords :
HD , Gait Signal , Stride Time Interval , Fractal Dimension , Statistical Features
Journal title :
Journal of Advances in Computer Research
