Research on Human Gait Phase Recognition Algorithm Based on Multi-Source Information Fusion

Gait phase detection is of great significance in the field motion analysis and exoskeleton-assisted walking, can realize accurate control exoskeleton robots. Therefore, order to obtain gait information ensure good accuracy, a recognition framework based on New Hidden Markov Model (NHMM) proposed improve accuracy detection. A multi-sensor data acquisition system was developed used collect training eight healthy subjects measure acceleration plantar pressure human body. Accuracy framework, filtering algorithm window selection, missing validation generalization performance method were evaluated. The experimental results show that overall NHMM 94.7%, which better than all other algorithms. 84.3%. this study provide theoretical basis for design exoskeleton.