TY - GEN
T1 - An HMM-based gait comparison
T2 - International Joint Conference on Neural Networks, IJCNN 2015
AU - Wang, Wei Hsin
AU - Wu, Hao Li
AU - Chung, Pau Choo
AU - Pai, Ming Chyi
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/9/28
Y1 - 2015/9/28
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84950977235&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84950977235&partnerID=8YFLogxK
U2 - 10.1109/IJCNN.2015.7280795
DO - 10.1109/IJCNN.2015.7280795
M3 - Conference contribution
AN - SCOPUS:84950977235
T3 - Proceedings of the International Joint Conference on Neural Networks
BT - 2015 International Joint Conference on Neural Networks, IJCNN 2015
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 12 July 2015 through 17 July 2015
ER -