Short- and Long-Term Learning of Feedforward Control of a Myoelectric Prosthesis with Sensory Feedback by Amputees.

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Abstract

Human motor control relies on a combination of feedback and feedforward strategies. The aim of this study was to longitudinally investigate artificial somatosensory feedback and feedforward control in the context of grasping with myoelectric prosthesis. Nine amputee subjects performed routine grasping trials, with the aim to produce four levels of force during four blocks of 60 trials across five days. The electrotactile force feedback was provided in the second and third block using multipad electrode and spatial coding. The first baseline and last validation block (open-loop control) evaluated the effects of long- (across sessions) and short-term (within session) learning, respectively. The outcome measures were the absolute error between the generated and target force, and the number of force saturations. The results demonstrated that the electrotactile feedback improved the performance both within and across sessions. In the validation block, the performance did not significantly decrease and the quality of open-loop control (baseline) improved across days, converging to the performance characterizing closed-loop control. This paper provides important insights into the feedback and feedforward processes in prosthesis control, contributing to the better understanding of the role and design of feedback in prosthetic systems.

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Restoring natural sensory feedback in real-time bidirectional hand prostheses.

Stanisa Raspopovic, Marco Capogrosso, Francesco Petrini … (2014)

Hand loss is a highly disabling event that markedly affects the quality of life. To achieve a close to natural replacement for the lost hand, the user should be provided with the rich sensations that we naturally perceive when grasping or manipulating an object. Ideal bidirectional hand prostheses should involve both a reliable decoding of the user's intentions and the delivery of nearly "natural" sensory feedback through remnant afferent pathways, simultaneously and in real time. However, current hand prostheses fail to achieve these requirements, particularly because they lack any sensory feedback. We show that by stimulating the median and ulnar nerve fascicles using transversal multichannel intrafascicular electrodes, according to the information provided by the artificial sensors from a hand prosthesis, physiologically appropriate (near-natural) sensory information can be provided to an amputee during the real-time decoding of different grasping tasks to control a dexterous hand prosthesis. This feedback enabled the participant to effectively modulate the grasping force of the prosthesis with no visual or auditory feedback. Three different force levels were distinguished and consistently used by the subject. The results also demonstrate that a high complexity of perception can be obtained, allowing the subject to identify the stiffness and shape of three different objects by exploiting different characteristics of the elicited sensations. This approach could improve the efficacy and "life-like" quality of hand prostheses, resulting in a keystone strategy for the near-natural replacement of missing hands.

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Computational mechanisms of sensorimotor control.

David W. Franklin, Daniel M. Wolpert (2011)

In order to generate skilled and efficient actions, the motor system must find solutions to several problems inherent in sensorimotor control, including nonlinearity, nonstationarity, delays, redundancy, uncertainty, and noise. We review these problems and five computational mechanisms that the brain may use to limit their deleterious effects: optimal feedback control, impedance control, predictive control, Bayesian decision theory, and sensorimotor learning. Together, these computational mechanisms allow skilled and fluent sensorimotor behavior. Copyright © 2011 Elsevier Inc. All rights reserved.

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Electrotactile and vibrotactile displays for sensory substitution systems.

K Kaczmarek, J Webster, P. BACH-Y-RITA … (1991)

Sensory substitution systems provide their users with environmental information through a human sensory channel (eye, ear, or skin) different from that normally used, or with the information processed in some useful way. We review the methods used to present visual, auditory, and modified tactile information to the skin. First, we discuss present and potential future applications of sensory substitution, including tactile vision substitution (TVS), tactile auditory substitution, and remote tactile sensing or feedback (teletouch). Next, we review the relevant sensory physiology of the skin, including both the mechanisms of normal touch and the mechanisms and sensations associated with electrical stimulation of the skin using surface electrodes (electrotactile (also called electrocutaneous) stimulation). We briefly summarize the information-processing ability of the tactile sense and its relevance to sensory substitution. Finally, we discuss the limitations of current tactile display technologies and suggest areas requiring further research for sensory substitution systems to become more practical.