Addressing unpredictability may be the key to improving performance with current clinically prescribed myoelectric prostheses

Abstract

The efferent control chain for an upper-limb myoelectric prosthesis can be separated into 3 key areas: signal generation, signal acquisition, and device response. Data were collected from twenty trans-radial myoelectric prosthesis users using their own clinically prescribed devices, to establish the relative impact of these potential control factors on user performance (user functionality and everyday prosthesis usage). By identifying the key factor(s), we can guide future developments to ensure clinical impact. Skill in generating muscle signals was assessed via reaction times and signal tracking. To assess the predictability of signal acquisition, we inspected reaction time spread and undesired hand activations. As a measure of device response, we recorded the electromechanical delay between electrode stimulation and the onset of hand movement. Results suggest abstract measures of skill in controlling muscle signals are poorly correlated with performance. Undesired activations of the hand or incorrect responses were correlated with almost all kinematics and gaze measures suggesting unpredictability is a key factor. Significant correlations were also found between several measures of performance and the electromechanical delay; however, unexpectedly, longer electromechanical delays correlated with better performance. Future research should focus on exploring causes of unpredictability, their relative impacts on performance and interventions to address this.

A scoping review of the application of motor learning principles to optimize myoelectric prosthetic hand control

“…Unlike rigid 'tools' that have fixed intrinsic properties, the reliability of prosthesis responsiveness can fluctuate as a result of EMG signal artefact arising from sweating, poor fitting and/or fatigue 58 . Indeed, recent evidence has shown that prosthesis users who experience a greater frequency of undesired activations (hand accidentally opening/closing, no prosthesis response, or incorrect prosthesis response) during a shoulder flexion task are also more likely to exhibit decreased functionality and an increased time watching the prosthesis during a multi-stage functional task 59 . This tentatively suggests that the expectation of an undesired prosthesis response (i.e., users do not trust their device) drives both poor performance and the over-reliance on gaze to visually monitor prosthesis control and safeguard against (the possibility of) task failure.…”

“…This tentatively suggests that the expectation of an undesired prosthesis response (i.e., users do not trust their device) drives both poor performance and the over-reliance on gaze to visually monitor prosthesis control and safeguard against (the possibility of) task failure. Addressing the issue of prosthesis unpredictability could therefore be crucial to the development of effective prosthesis visuomotor control and the alleviation of cognitive resources dedicated to continuous prosthesis monitoring 59 .…”

“…Addressing the issue of prosthesis unpredictability could therefore be crucial to the development of effective prosthesis visuomotor control and the alleviation of cognitive resources dedicated to continuous prosthesis monitoring. 59 While the influence of prosthesis unpredictability cannot be overlooked, Parr et al 19 provided evidence that the gaze strategies used to control a prosthesis can also be strongly influenced by the nature of training instructions. Specifically, Parr et al administered 1 week of gaze training designed to encourage learners to adopt a target-focused gaze strategy and avoid visually fixating the prosthesis, a method shown to expedite the acquisition of laparoscopic surgical skills.…”

First Demonstration of Functional Task Performance Using a Sonomyographic Prosthesis: A Case Study

“…Even minor changes to the imaging angle can drastically affect an acquired ultrasound image and cause the classifier to misidentify the user’s intended hand gesture. Unintended hand movements due to misclassification may lead to reduced task completion rates, slower task performance, increased temporal variability, and increased cognitive load ( Chadwell et al, 2021 ). Thus, grasp classification must be sufficiently stable under varying arm positions and loading conditions for the user to consistently achieve their desired hand grasps throughout the reachable workspace.…”

First-in-human demonstration of functional task performance using a sonomyographic prosthesis

“…Even minor changes to the imaging angle can drastically affect an acquired ultrasound image and cause the classi er to misidentify the user's intended hand gesture. Unintended hand movements due to misclassi cation may lead to reduced task completion rates, slower task performance, increased temporal variability, and increased cognitive load (Chadwell et al, 2021). Thus, grasp classi cation must be su ciently stable under varying arm positions and loading conditions for the user to consistently achieve their desired hand grasps throughout the reachable workspace.…”