Comparison of gait phase detection using traditional machine learning and deep learning techniques

arXiv:2403.05595v1 Announce Type: cross
Abstract: Human walking is a complex activity with a high level of cooperation and interaction between different systems in the body. Accurate detection of the phases of the gait in real-time is crucial to control lower-limb assistive devices like exoskeletons and prostheses. There are several ways to detect the walking gait phase, ranging from cameras and depth sensors to the sensors attached to the device itself or the human body. Electromyography (EMG) is one of the …

abstract arxiv comparison control cs.cv cs.hc cs.lg deep learning deep learning techniques detection devices eess.sp exoskeletons human machine machine learning real-time systems traditional machine learning type walking