DocumentCode :
3661481
Title :
An HMM-based gait comparison: Using Alzheimer´s disease patients as examples
Author :
Wei-Hsin Wang;Hao-Li Wu;Pau-Choo Chung;Ming-Chyi Pai
Author_Institution :
Dept. of Electrical Engineering, National Cheng Kung University, Tainan, Taiwan (R.O.C.)
fYear :
2015
fDate :
7/1/2015 12:00:00 AM
Firstpage :
1
Lastpage :
6
Abstract :
The similarity comparisons between single-task walking and dual-task walking on Alzheimer´s disease (AD) patients has been commonly performed for cognitive declination measurement. This paper presents a personalized gait similarity measurement approach based on Hidden Markov model for the self-comparison between the single-task walking and dual-task walking. Compared with traditional approaches which use statistics parameters comparison on normal group and AD group, the proposed personalized HMM-based self-comparison approach can avoid the dilemma resulted from personal differences such as walking habits and physical conditions such as height and weight. In this paper, two groups, 42 AD patients and 64 healthy control (HC) people, participate the experiments. The results show the promising of the proposed approach in comparing the AD from the normal people.
Keywords :
"Hidden Markov models","Legged locomotion","Education"
Publisher :
ieee
Conference_Titel :
Neural Networks (IJCNN), 2015 International Joint Conference on
Electronic_ISBN :
2161-4407
Type :
conf
DOI :
10.1109/IJCNN.2015.7280795
Filename :
7280795
Link To Document :
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