Wearable Sensing for Breaststroke Phase Monitoring With Lower Limb Muscle-Joint Synergy

Motivated by the need for underwater exoskeleton control, swimming phase monitoring is critical to adjust robotic assistance to human motions. However, harsh underwater environments bring in challenges of poor robustness and serious disturbances to the few available sensing methods leading to coarse phase segmentation. Given skeletal muscle activation for limb joint motions, this article proposes a muscle-joint synergy method to combine muscle mechanics captured by a novel capacitive sensor with joint kinematics by traditional inertial measurements. Development of the wearable sensing system is provided with details on design, fabrication, and assembly. The muscle-joint synergy model is rigorously formulated and experimentally validated with breaststroke data for the first time. Immediate applications are illustrated with discrete mode identification and continuous phase monitoring, justifying the robustness of the proposed method to various artificial intelligent algorithms and different tested subjects. This work is anticipated to be valuable to unveil the mechanism of human natural motions for human-centered robotics, sport science, and rehabilitation engineering in the future.