Early Prediction of Lower Limb Prostheses Locomotion Mode Transition Based on Terrain Recognition

• Published in: IEEE sensors journal Vol. 23; no. 22; pp. 27941 - 27948
• Main Authors: Luo, Shengli, Shu, Xiaolong, Zhu, Hexiang, Yu, Hongliu
• Format: Journal Article
• Language: English
• Published: New York IEEE 15.11.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Amputation; Classification; Data integration; Distance measurement; Electromyography; Feature recognition; Inertial platforms; Inertial sensing devices; Legged locomotion; Locomotion; Locomotion mode transition; lower limb prostheses; Multisensor fusion; Parameter identification; Prostheses; Prosthetics; Sensor systems; Sensors; Stairs; Terrain; terrain classification; terrain recognition; terrain reconstruction
• ISSN: 1530-437X; 1558-1748
• DOI: 10.1109/JSEN.2023.3320274

Terrain classification and feature recognition are key to the locomotion mode switching of lower limb prosthesis and also help to improve the unnatural gait of amputees. This article aims to propose a terrain early recognition system for lower limb prostheses. Laser range sensors and inertial measurement units (IMUs) were fixed on the lower limb, and a multi-sensor information fusion and geometric classification method for a priori identification of terrain transformations and estimation of key terrain feature parameters, including slope, height, and width. Ten healthy subjects and two hip amputees participated in the classification experiments with five terrains. The classification accuracy of the system for five terrains was 98.67% indoor and 95.33% outdoor, and the terrain classification accuracy of amputees remained consistent with that of healthy subjects. The average error of terrain feature recognition was 4.37%, including 4.52% in the amputation group, which was only 0.17% higher than that in the healthy. The system can be fixed to the lower limbs and recognize five terrains and terrain features before a gait cycle.