Electrotactile feedback outweighs natural feedback in sensory integration during control of grasp force

Abstract

The nervous system subconsciously estimates the state of the body as a weighted average of the information from various sensory sources, where the weights reflect the perceived reliability of each source. Loss of motor functions can be partially compensated using assistive systems (e.g. prostheses), which may also restore somatosensory feedback through tactile stimulation. Whether such artificial feedback is integrated in the neural state estimation process is not known. In this study, able-bodied subjects performed a grasp force matching task with supplementary non-invasive electrotactile stimulation with a frequency proportional to grasp force magnitude. Before the task, a brief training session taught the subjects to associate the sensation of electrotactile stimulation with the generated grasp force. In some trials, the force-frequency mapping was biased to introduce an unnoticeable mismatch between natural and electrotactile force feedback, thereby provoking the subject to subconsciously estimate the force as a compromise between the two sources of information.The outcome of this compromise revealed the weights assigned to each feedback type. The grasp forces were significantly affected by the biased mappings, as indicated by the average estimated relative weights (electrotactile: 0.69 ± 0.29; natural: 0.31±0.29). Across subjects, this weight was correlated (𝑟 2 = 0.75) with the improvement in force matching precision when adding the unbiased electrotactile feedback to the natural force feedback, as predicted by maximum likelihood estimation. This shows that even after minimal training the nervous system adopts electrotactile stimulation as a highly reliable source of information that can improve the precision in the estimation of the grip force. This result has important implications for the restoration of sensory feedback in upper limb prostheses as it indicates that even non-invasive stimulation can be integrated naturally (i.e., subconsciously and effectively) in the motor control loop.

Task-Dependent Adaptations in Closed-Loop Motor Control Based on Electrotactile Feedback

“…The tracking performance was variable across subjects, especially when the task was performed using electrotactile feedback, where the across-subject variability seems to be larger for PCM than VCM. This is in line with the higher difficulty of that task as well as with the recent observation that the subjects can differ substantially in how well they can integrate the electrotactile feedback [34].…”

Combined spatial and frequency encoding for electrotactile feedback of myoelectric signals

“…Nevertheless, it remains to be investigated how the use of such feedback in a more practical task (e.g., including a prosthesis in the loop), when the subjects need to divide their attention, would affect the feedback interpretation and cognitive effort as well as if the latter could be decreased with training. As shown in a recent study by Gholinezhad et al (2021), humans can subconsciously process electrotactile stimulation. Not only did the presence of electrotactile stimulation not impair the perception of natural feedback, but it actually enhanced the task-relevant natural input and improved the overall state estimate.…”

“…One approach to activate the tactile sense externally is to use electrotactile stimulation, which involves the application of electrical current over the skin surface (Szeto and Saunders 1982;Szeto and Riso 1990;Clemente et al 2016;Štrbac et al 2016). This method has been tested in a wide range of practical applications, from telemanipulation and prosthetics to virtual reality (Kourtesis et al 2022), and has been translated into commercial systems (BrainPort 2022;MyLeg 2022;Teslasuit 2022) and shown to integrate naturally into the motor control loop (Lewis et al 2012;Akhtar et al 2018;Gholinezhad et al 2021). Importantly, designing an effective feedback interface requires defining an appropriate encoding scheme to map a feedback variable into a stimulation profile delivered to the skin.…”

An Embodied Sonification Model for Sit-to-Stand Transfers

“…The results from this assessment may not be generalizable to a motor feedback application, which is “closed-loop”. It will be necessary to perform human experiments to assess the model in a closed-loop feedback setting (such as the protocol employed by Gholinezhad et al, 2021 ). A potential pitfall in the experiment design was the fact that a forced-choice paradigm may have made elimination strategies possible, although more continuous measures of movement quality such as those used by Danna et al ( 2015 ) are subject to individual variability.…”