Tactile feedback is an effective instrument for the training of grasping with a prosthesis at low- and medium-force levels
Research output: Contribution to journal › Article
Colleges, School and Institutes
- Imperial College London
- Centre of Precision Rehabilitation for Spinal Pain (CPR Spine), School of Sport, Exercise and Rehabilitation Sciences, College of Life and Environmental Sciences, University of Birmingham, Birmingham, United Kingdom.
- Neurorehabilitation Systems Research Group, Clinics for Trauma, Orthopaedic and Plastic Surgery, University Medical Center Goettingen, Georg-August University
- Department of Translational Research and Knowledge Management, Otto Bock HealthCare GmbH
- Department of Translational Research and Knowledge Management, Otto Bock HealthCare GmbH, Max-Näder-Straße 15, 37115, Duderstadt, Germany.
Grasping is a complex task routinely performed in an anticipatory (feedforward) manner, where sensory feedback is responsible for learning and updating the internal model of grasp dynamics. This study aims at evaluating whether providing a proportional tactile force feedback during the myoelectric control of a prosthesis facilitates learning a stable internal model of the prosthesis force control. Ten able-bodied subjects controlled a sensorized myoelectric prosthesis performing four blocks of consecutive grasps at three levels of target force (30, 50, and 70%), repeatedly closing the fully opened hand. In the first and third block, the subjects received tactile and visual feedback, respectively, while during the second and fourth block, the feedback was removed. The subjects also performed an additional block with no feedback 1 day after the training (Retest). The median and interquartile range of the generated forces was computed to assess the accuracy and precision of force control. The results demonstrated that the feedback was indeed an effective instrument for the training of prosthesis control. After the training, the subjects were still able to accurately generate the desired force for the low and medium target (30 and 50% of maximum force available in a prosthesis), despite the feedback being removed within the session and during the retest (low target force). However, the training was substantially less successful for high forces (70% of prosthesis maximum force), where subjects exhibited a substantial loss of accuracy as soon as the feedback was removed. The precision of control decreased with higher forces and it was consistent across conditions, determined by an intrinsic variability of repeated myoelectric grasping. This study demonstrated that the subject could rely on the tactile feedback to adjust the motor command to the prosthesis across trials. The subjects adjusted the mean level of muscle activation (accuracy), whereas the precision could not be modulated as it depends on the intrinsic myoelectric variability. They were also able to maintain the feedforward command even after the feedback was removed, demonstrating thereby a stable learning, but the retention depended on the level of the target force. This is an important insight into the role of feedback as an instrument for learning of anticipatory prosthesis force control.
|Journal||Experimental Brain Research|
|Early online date||26 May 2017|
|Publication status||Published - Aug 2017|
- Journal Article, Tactile stimulation , Visual feedback , Grasping force control , Prosthetic grasping , Myoelectric control , Feedforward control , Anticipatory mechanisms , Internal model