Comparison of Bilateral and Unilateral Contractions and Limb Dominance on Pattern Classification Accuracy for Prosthesis Control
Authors: Kuruganti Usha , Pradhan Ashirbad , Chester Victoria 
Published: October 2017

Introduction

Powered transradial prostheses use the amplitudes of surface electromyography (EMG) signals from the forearm flexors and extensors to control the opening and closing of the hand. Users must co-contract their forearm muscles as a switch to rotate the wrist. This operation can be slow and is not intuitive, as the user is required to use the same muscle contractions to control different functions. Pattern recognition-based controllers perform movements based on EMG patterns, rather than using individual EMG from the residual muscle. This results in intuitive control and users may be successfully trained. Therapists use a series of movements to train prosthesis users to successfully operate their devices with the assumption that the intact limb is considered the dominant side while the affected limb (whether by congenital or traumatic occurrence) becomes the nondominant side. In fact, depending on the individual presentation of amputation, this may or may not be true and could impact the success of the training program. Therapists also use both unilateral and bilateral movements to train users of prosthetic devices. In terms of myoelectric control, it is possible that classification accuracy may be affected by neural deficits such as the bilateral limb deficit (BLD) phenomenon, which may also affect the success of the training program. The BLD is defined as the reduction in force production during bilateral compared with summed unilateral contractions of homologous muscles. The underlying mechanism for the BLD has been elusive to determine; however, it has been suggested that it is neural in origin and may have an impact on both maximal and submaximal contractions. The purpose of this work was to examine upper-limb movements to determine 1) if there is any decrement to pattern classification accuracy due to the type of movement (bilateral vs. unilateral), and 2) if limb dominance affects pattern classification accuracy. Understanding the impact of these movements may help to improve training protocols for upper-limb prosthesis users.

Materials and Methods

Ten able-bodied participants between the ages of 21 and 25 years (6 males, 4 females) participated in this study. A high-density EMG system (REFA; TMS International) was used to evaluate four different hand movements (“hand open,” “hand closed,” “pronation,” and “supination”) at a self-selected medium contraction level. Participants were asked to complete the movements in two conditions, bilateral (both hands together) and unilateral (one hand at a time). Participants were asked to indicate their dominant limb. Surface electrodes (n = 32) were placed over the forearm to collect high-density EMG data. Pattern classification accuracies were computed for all movements using an linear discriminant analysis pattern classifier.

Results

Analysis of variance indicated that there was no statistically significant difference in classification accuracy due to condition (bilateral vs. unilateral) or limb dominance.

Conclusions

The results suggest that high pattern classification accuracy can be achieved with both one and two hands with no evidence of BLD. In addition, limb dominance did not affect classification accuracy. This suggests that therapists may not be limited to specific actions for user training.