FSR based Force Myography (FMG) Stability Throughout Non-Stationary Upper Extremity Tasks

Abstract

Force Myography (FMG) is a method of tracking movement and functional activity that is based on the volumetric changes that occur in a limb during muscle contraction. There are several advantages of FMG over other myographic modalities that support its implementation in rehabilitative and assistive technology to track upper extremity movement during activities of daily living. The aim of the current work is to explore the stability of FMG sensors during non-static upper extremity activities. Twenty-one participants with varying age and gender were recruited to perform a set of tasks while wearing a custom FMG band. The participants were required to move between two extremes of range of motion (wrist flexion/extension and forearm pronation/supination) or between two extremes of grasp force (squeeze and relax). FMG presented low variability (<6%) and demonstrated little to no drift with ongoing task duration (Spearman’s |R| < 0.3). FMG variability did not present any relationship to differences in anthropometry or grip strength (Spearman’s |R| < 0.3), suggesting that FMG wearers will present a stable FMG signal despite differing musculoskeletal characteristics. Finally, variability in FMG presented no significant relationship between user variables and the testing accuracies of machine learning models trained on FMG data. The results of this study demonstrate the stability of FMG signals during non-stationary tasks and support the potential of implementing FMG into user-machine interface technology.