Continuous Prediction of Leg Kinematics During Ambulation using Peripheral Sensing of Muscle Activity and Morphology

Abstract

The advancement of robotic lower-limb assistive devices has heightened the need for accurate and continuous sensing of user intent. Surface electromyography (EMG) has been extensively used to sense muscles, and estimate locomotion modes and limb motion. Recently, sonomyography has also been investigated as a novel sensing modality. However, the fusion of multiple sensing modalities has not been explored for the continuous prediction of multiple degrees-of-freedom of the lower limb, and during multiple ambulation tasks. In the present study, nine able-bodied subjects completed level, incline, decline, stair ascent, and stair descent tasks. Motion capture data was collected during each task, as well as data from a portable ultrasound transducer (aligned in a transverse orientation) on the anterior thigh and surface EMG sensors on eight lower-limb muscles. Subject-dependent, task-independent Gaussian process regression models were implemented for continuous prediction of knee and ankle angle and angular velocity during these ambulation tasks using three feature sets: (1) surface EMG, (2) sonomyography, and (3) sensor fusion of EMG with sonomyography. Surprisingly, there were no significant differences between sonomyography and sensor fusion-based prediction of knee or ankle angle and angular velocity during all tasks. However, sonomyography and sensor fusion resulted in reduced root mean square error of knee angle prediction during all ambulation tasks and knee angular velocity prediction during most ambulation tasks compared to surface EMG. Sensor fusion improved ankle angle prediction for all walking tasks except stair ascent in comparison to surface EMG. Ankle angular velocity prediction resulted in the lowest performance, overall.Clinical Relevance—This work compares the combination of surface electromyography and sonomyography, and each modality in isolation, for the continuous prediction of kinematics of the knee and ankle during widely-varying ambulatory tasks.