Tactile feedback is an effective instrument for the training of grasping with a prosthesis at low- and medium-force levels

Abstract

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.

Joint Speed Discrimination and Augmentation For Prosthesis Feedback

“…Because sensory feedback is merged inversely proportional to each modality's uncertainty 23 , sensory feedback encoding position will likely not significantly augment proprioception of a prosthetic limb unless it matches or exceeds vision's 1% uncertainty 24 or encodes information in a novel way, such as tactile sensation 11,18 or discrete events in grasping 9 . However, our study suggests that sensory feedback encoding prosthetic joint speed may more significantly augment proprioception of a prosthetic limb due to higher uncertainty in visual estimates of limb joint speed.…”

“…Sensory feedback remains a research priority for prosthesis users 6 . Several feedback methods have been proposed over the past decades, including vibrotactile [7][8][9][10][11] , electrotactile 8 , skin stretch 7 , audio [12][13][14] and visual 15 modalities 16,17 . More complex feedback modalities like peripheral nerve stimulation 18 and vibration-induced illusory kinesthesia 19 have also been introduced to great effect.…”

“…More complex feedback modalities like peripheral nerve stimulation 18 and vibration-induced illusory kinesthesia 19 have also been introduced to great effect. Sensory feedback typically falls into two categories: tactile feedback of grasping force 9,11,18 , and proprioceptive feedback of limb movement 7,8,10,[12][13][14][15]19 . Vision is capable of estimating grasping force similarly to tactile feedback 20 , though several grasping force feedback studies have still shown significant benefit to prosthesis control with vision present.…”

Long-Term Home-Use of Sensory-Motor-Integrated Bidirectional Bionic Prosthetic Arms Promotes Functional, Perceptual, and Cognitive Changes

“…Addressing the challenges associated with the absence of sensation is a highly active field of study, and attempts to provide prosthesis users with sensory feedback have been reported as early as the 1950s (Siehlow, 1951). More recently, the use of mechanotactile and vibrotactile feedback has been used to provide sensations of proportional tactile force (Marasco et al, 2011;Antfolk et al, 2013;Rombokas et al, 2013;Cipriani et al, 2014;Hebert et al, 2014;De Nunzio et al, 2017), and movement sensation (Sharma et al, 2014;Witteveen et al, 2014;Hasson and Manczurowsky, 2015;Marasco et al, 2018) in both amputee and able-bodied populations. These methods have proven effective in patient performance of tasks such as precise force generation (De Nunzio et al, 2017), force discrimination , stiffness discrimination Witteveen et al, 2014), stimuli localization (Antfolk et al, 2013), and multi-site sensory discrimination (Antfolk et al, 2013).…”

“…More recently, the use of mechanotactile and vibrotactile feedback has been used to provide sensations of proportional tactile force (Marasco et al, 2011;Antfolk et al, 2013;Rombokas et al, 2013;Cipriani et al, 2014;Hebert et al, 2014;De Nunzio et al, 2017), and movement sensation (Sharma et al, 2014;Witteveen et al, 2014;Hasson and Manczurowsky, 2015;Marasco et al, 2018) in both amputee and able-bodied populations. These methods have proven effective in patient performance of tasks such as precise force generation (De Nunzio et al, 2017), force discrimination , stiffness discrimination Witteveen et al, 2014), stimuli localization (Antfolk et al, 2013), and multi-site sensory discrimination (Antfolk et al, 2013). Other approaches are also being pursued, including electrical stimulation of peripheral nerves (e.g., Christie et al, 2017), electrocutaneous stimulation (e.g., Paredes et al, 2015), and direct cortical stimulation of the primary somatosensory cortex (e.g., Tabot et al, 2013;Hiremath et al, 2017).…”