Citation

Abdullah, A. R. and Rahman, K. A. and Shair, E. F. and Lee, T. H. and Nazmi, N. and Fahad, Nafiz (2024) Analysis of Gait Patterns in Neurodegenerative Disorders Among Older Adults: A Ground Reaction Force Data Approach. In: Proceedings of the 10th World Congress on Electrical Engineering and Computer Systems and Sciences (EECSS'24), August 19 - 21, 2024, Barcelona, Spain.

Text ICBES_131.pdf - Published Version Restricted to Repository staff only Download (1MB)

Abstract

Increasing awareness of walking-related issues leading to falls, particularly in older adults, has highlighted this important concern. Even though walking is a fundamental human movement, studying it is difficult because it involves intricate brain, nerve, and muscle coordination. Neurodegenerative disorders like Amyotrophic Lateral Sclerosis (ALS), Parkinson's disease (PD), and Huntington's disease (HD) are frequently associated with walking limitations, highlighting the critical need for precise diagnostic tools. This study employed a comprehensive approach, delving into the intricate examination of gait patterns in individuals with neurodegenerative disorders. We used ground reaction force (GRF) step data from the Physionet public database, which converted into the time-frequency domain using continuous wavelet transform (CWT). We applied feature extraction techniques to identify unique gait characteristics for each disorder. Our findings revealed significant differences in gait among neurodegenerative diseases, with Parkinson's disease exhibiting the highest variability, ALS showing less variability, and Huntington's disease falling in between. These results illustrate the complex nature of walking issues in neurodegenerative diseases, highlighting the necessity of specific diagnostic approaches

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	Neurodegenerative disorders; gait analysis; older adults; ground reaction force; time-frequency
Subjects:	Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
Divisions:	Faculty of Information Science and Technology (FIST)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	04 Nov 2024 00:52
Last Modified:	04 Nov 2024 00:52
URII:	http://shdl.mmu.edu.my/id/eprint/13073

Downloads

Edit (login required)