An Intelligent Thermal Sensing System for Automatic, Quantitative Assessment of Motion Training in Lower-Limb Rehabilitation
开发了一套居家使用的智能热感系统，通过热成像和足底压力传感器自动分析腿部运动风格、轨迹周期性和平衡水平，帮助患者改善运动协调能力。
This paper aims to develop a home-oriented cyber-physical system to help patients improve their motion coordination capability via physical training. The measures evaluated by the system include the motion style of the legs, the periodicity of the foot trajectory, and the foot balance level, which are recommended by physical therapists. The motions of the legs and feet are recorded by thermal camera, and the plantar pressure is measured by the insole pressure sensors. We have developed innovative algorithms to extract the leg skeletons from the thermal images, and to implement motion signal auto-segmentation, recognition, and analysis for the above-mentioned measures. The experimental results have verified that the proposed system could efficiently acquire and analyze the lower-limb motion information.