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.
| Original language | English |
|---|---|
| Title of host publication | 2015 International Joint Conference on Neural Networks, IJCNN 2015 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Volume | 2015-September |
| ISBN (Electronic) | 9781479919604, 9781479919604, 9781479919604, 9781479919604 |
| DOIs | |
| Publication status | Published - 2015 Sep 28 |
| Event | International Joint Conference on Neural Networks, IJCNN 2015 - Killarney, Ireland Duration: 2015 Jul 12 → 2015 Jul 17 |
Other
| Other | International Joint Conference on Neural Networks, IJCNN 2015 |
|---|---|
| Country | Ireland |
| City | Killarney |
| Period | 15-07-12 → 15-07-17 |
Fingerprint
All Science Journal Classification (ASJC) codes
- Software
- Artificial Intelligence
Cite this
}
An HMM-based gait comparison : Using Alzheimer's disease patients as examples. / Wang, Wei Hsin; Wu, Hao Li; Chung, Pau-Choo; Pai, Ming-Chyi.
2015 International Joint Conference on Neural Networks, IJCNN 2015. Vol. 2015-September Institute of Electrical and Electronics Engineers Inc., 2015. 7280795.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - An HMM-based gait comparison
T2 - Using Alzheimer's disease patients as examples
AU - Wang, Wei Hsin
AU - Wu, Hao Li
AU - Chung, Pau-Choo
AU - Pai, Ming-Chyi
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
VL - 2015-September
BT - 2015 International Joint Conference on Neural Networks, IJCNN 2015
PB - Institute of Electrical and Electronics Engineers Inc.
ER -