title: 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 grasp-lift-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 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.
authors.affiliation: The BioRobotics Institute, Scuola Superiore Sant'Anna, V.le Piaggio 34, 56025, Pontedera (PI), Italy, ch.cipriani@sssup.it.
authors.forename: Christian
authors.initials: C
authors.lastname: Cipriani
authors.forename: Jacob L
authors.initials: JL
authors.lastname: Segil
authors.forename: Francesco
authors.initials: F
authors.lastname: Clemente
authors.forename: Richard F
authors.initials: RF
authors.lastname: ff Weir
authors.forename: Benoni
authors.initials: B
authors.lastname: Edin
mesh_terms: D000328:Adult; D056228:Feedback, Sensory / Q000502:physiology*; D005260:Female; D006225:Hand / Q000502:physiology*; D018737:Hand Strength / Q000502:physiology*; D006801:Humans; D007858:Learning; D008297:Male; D009068:Movement; D053580:Muscle Strength / Q000502:physiology; D011597:Psychomotor Performance / Q000502:physiology*; D012371:Robotics; D013997:Time Factors; D014110:Touch / Q000502:physiology; D055815:Young Adult