When Less Is More – Discrete Tactile Feedback Dominates Continuous Audio Biofeedback in the Integrated Percept While Controlling a Myoelectric Prosthetic Hand

Abstract

State of the art myoelectric hand prostheses can restore some feedforward motor function to their users, but they cannot yet restore sensory feedback. It has been shown, using psychophysical tests, that multi-modal sensory feedback is readily used in the formation of the users’ representation of the control task in their central nervous system – their internal model. Hence, to fully describe the effect of providing feedback to prosthesis users, not only should functional outcomes be assessed, but so should the internal model. In this study, we compare the complex interactions between two different feedback types, as well as a combination of the two, on the internal model, and the functional performance of naïve participants without limb difference. We show that adding complementary audio biofeedback to visual feedback enables the development of a significantly stronger internal model for controlling a myoelectric hand compared to visual feedback alone, but adding discrete vibrotactile feedback to vision does not. Both types of feedback, however, improved the functional grasping abilities to a similar degree. Contrary to our expectations, when both types of feedback are combined, the discrete vibrotactile feedback seems to dominate the continuous audio feedback. This finding indicates that simply adding sensory information may not necessarily enhance the formation of the internal model in the short term. In fact, it could even degrade it. These results support our argument that assessment of the internal model is crucial to understanding the effects of any type of feedback, although we cannot be sure that the metrics used here describe the internal model exhaustively. Furthermore, all the feedback types tested herein have been proven to provide significant functional benefits to the participants using a myoelectrically controlled robotic hand. This article, therefore, proposes a crucial conceptual and methodological addition to the evaluation of sensory feedback for upper limb prostheses – the internal model – as well as new types of feedback that promise to significantly and considerably improve functional prosthesis control.

A Modular Adjustable Transhumeral Prosthetic Socket for Evaluating Myoelectric Control

“…Surprisingly, performance as perceived by the participant was lower with the MAPS compared to the suction socket and was reported to require higher mental effort despite similar completion times and completion rates between the two sockets. The discrepancy between objective and perceived measures of performance reflects previous findings where changes in the participant’s understanding of a task due to external factors are not represented by objective performance outcomes [37] . In the context of this experiment, the factor likely attributable to this change in task perception is the participants’ unfamiliarity with the new system, compounded with a delay between the first and second testing sessions.…”

A Review of Sensory Feedback in Upper-Limb Prostheses From the Perspective of Human Motor Control

“…However, in these studies, the individual effects of these modalities on performance were not investigated. A recent study has explored the interaction between discrete tactile feedback and continuous audio biofeedback focusing on the impact that they have on the formation of internal models (Engels et al, 2019). Contrary to expectations, the results seem to imply that when the two modalities were combined, discrete feedback dominated the continuous information.…”

Mechanotactile Sensory Feedback Improves Embodiment of a Prosthetic Hand During Active Use

“…Simulated upper-limb prosthesis systems are commonly used as an approximation to prostheses used by persons with upper-limb amputation, as a method of allowing able-bodied participants to actively control a prosthetic hand in a situation more similar to actual prosthesis use. Researchers have used various versions of simulated prostheses to investigate the performance of commercial prosthetic hands (Kyberd, 2011), performance of novel control strategies (Johansen et al, 2016;Shehata et al, 2018a), kinematic movement trajectories when using prosthetic hands (Williams et al, 2019), and, recently, the effect of providing sensory feedback to users on performance in functional tasks (Wilson et al, 2017;Engels et al, 2019). In this work, we used a sensorized simulated prosthesis to investigate the contribution of sensory feedback to the embodiment phenomenon during active motor control of the prosthesis, utilizing a common methodology in the literature, namely the RHI (Longo et al, 2008).…”