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