Human Gait Phase Recognition using a Hidden Markov Model Framework
Ferhat Attal,Yacine Amirat,Abdelghani Chibani,Samer Mohammed,Ferhat Attal,Yacine Amirat,Abdelghani Chibani,Samer Mohammed
Analysis of human daily living activities, particularly walking activity, is essential for health-care applications such as fall prevention, physical rehabilitation exercises, and gait monitoring. Studying the evolution of the gait cycle using wearable sensors is beneficial for the detection of any abnormal walking pattern. This paper proposes a novel discrete/continuous unsupervised Hidden Markov...
