Humans can integrate feedback of discrete events in their sensorimotor control of a robotic hand

Abstract

Providing functionally effective sensory feedback to users of prosthetics is a largely unsolved challenge. Traditional solutions require high band-widths for providing feedback for the control of manipulation and yet have been largely unsuccessful. In this study, we have explored a strategy that relies on temporally discrete sensory feedback that is technically simple to provide. According to the Discrete Event-driven Sensory feedback Control (DESC) policy, motor tasks in humans are organized in phases delimited by means of sensory encoded discrete mechanical events. To explore the applicability of DESC for control, we designed a paradigm in which healthy humans operated an artificial robot hand to lift and replace an instrumented object, a task that can readily be learned and mastered under visual control. Assuming that the central nervous system of humans naturally organizes motor tasks based on a strategy akin to DESC, we delivered short-lasting vibrotactile feedback related to events that are known to forcefully affect progression of the grasplift-and-hold task. After training, we determined whether the artificial feedback had been integrated with the sensorimotor control by introducing short delays and we indeed observed that Correspondence to: Christian Cipriani, ch.cipriani@sssup.it. Jacob L. Segil and Francesco Clemente have contributed equally to this work.Conflict of interest CC hold shares in Prensilia S.R.L., the company that manufactures robotic hands as the one used in this work, under the license to Scuola Superiore Sant'Anna. U.S. Department of Veterans AffairsPublic Access Author manuscript Exp Brain Res. Author manuscript; available in PMC 2015 December 01. VA Author ManuscriptVA Author Manuscript VA Author Manuscript the participants significantly delayed subsequent phases of the task. This study thus gives support to the DESC policy hypothesis. Moreover, it demonstrates that humans can integrate temporally discrete sensory feedback while controlling an artificial hand and invites further studies in which inexpensive, noninvasive technology could be used in clever ways to provide physiologically appropriate sensory feedback in upper limb prosthetics with much lower band-width requirements than with traditional solutions.

Humans Can Integrate Augmented Reality Feedback in Their Sensorimotor Control of a Robotic Hand

“…The same test object as in [19] and [25] was used in this experiment. It consisted of a rigid plastic block (55 × 40 × 50 mm; 105 g) covered by plastic plates, equipped with piezoresistive force sensors (FsG series, Honeywell, MN; 0-15 N; 0-2 kHz) able to measure the GF exerted on each plate by the thumb and index robotic digits independently.…”

“…Accordingly, in each trial, the mapping between the human and the robotic hand grip aperture differed; the exact initial position of the robotic fingers was, therefore, unpredictable to the user. As in [19], this unpredictable mapping was included in order to simulate an amputee (who lacks in proprioception) operating a myoelectric prosthesis. In fact, the random mapping impeded the participants to operate the hand by using learned digit positions.…”

“…From an engineering perspective, there are two possible ways for addressing this limitation: exploiting a low-bandwidth feedback device [13], [19] or increasing the effective information throughput using multichannel configurations (which requires specific training of subjects to learn how to reinterpret the provided stimuli) [20]. In this work, we propose a new approach based on a simple and intuitive paradigm, which exploits the visual system.…”

“…In addition, our system displayed via see-through AR glasses continuous artificial visual feedback in the form of an ellipse, by scaling its horizontal and vertical axes according to the measured grip closure (GC) and GF, respectively. Notably, the task was performed under visual control, and it was known by previous studies that it could be readily completed even without the augmented feedback [19]; hence, the AR feedback was not only artificial but also redundant. Nevertheless, because of the intuitiveness of the visual feedback provided, we expected that the participants would readily integrate it into their sensorimotor control of the robotic hand.…”

“…Nevertheless, because of the intuitiveness of the visual feedback provided, we expected that the participants would readily integrate it into their sensorimotor control of the robotic hand. To reveal such integration, we implemented a well-established protocol used in our previous studies [13], [19] as well as in the literature on adaptation in motor control [24]. We modified, unknowingly to the participants, the way we translated the GF or the GC into visual cues in blocks of catch trials after first training the participants.…”