A wearable capacitive sensing system with phase-dependent classifier for locomotion mode recognition

Locomotion mode recognition is one of the most important aspects for the control of motion rehabilitation systems, e.g. lower-limb prostheses and exoskeletons. In this paper, we propose a capacitance based sensing system for recognizing human locomotion modes. The proposed system includes two rings as sensing front-ends of body capacitance, two sensing circuits for processing the signals and the gait event detection system. The deformation of muscles can be reflected by the changes of capacitance signals. To validate the developed prototype, nine locomotion modes are monitored and ten channels of capacitance signals are collected for locomotion mode recognition. With the combination of capacitive sensing approach and phase-dependent classification method, satisfactory recognition results are obtained.