Ankle Positions Classification using Force Myography: An Exploratory Investigation

Xianta Jiang • Hon Tang Chu • Zhen Gang Xiao • Lukas-Karim Merhi • Carlo Menon

12:00 - 14:00 | Thursday 10 November 2016 | Maya Ballroom Foyer


Monitoring the movements of the ankle may be highly relevant for applications such as sport injury prevention, rehabilitation, and gait analysis. This paper explores the feasibility of employing force myography (FMG) on the distal end of the lower leg to detect ankle position. FMG signals corresponding to 7 different ankle positions were recorded from three healthy volunteers. Using a linear discriminant analysis (LDA) classifier, the system achieved averaged prediction accuracies of 94% and 85% in cross validation and cross-trial evaluation, respectively. The results of this proof-of-concept study demonstrate the feasibility of using FMG to detect ankle position and its consequent potential use for acquiring information relevant to leg movement and gait.