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Neurorobotic fusion of prosthetic touch, kinesthesia, and movement in bionic upper limbs promotes intrinsic brain behaviors

Paul D. Marasco, Jacqueline S. Hebert, Jonathon W. Sensinger, Dylan T. Beckler, Zachary C. Thumser, Ahmed W. Shehata, Heather E. Williams, Kathleen R. Wilson

2021Science Robotics126 citationsDOI

Abstract

Bionic prostheses have restorative potential. However, the complex interplay between intuitive motor control, proprioception, and touch that represents the hallmark of human upper limb function has not been revealed. Here, we show that the neurorobotic fusion of touch, grip kinesthesia, and intuitive motor control promotes levels of behavioral performance that are stratified toward able-bodied function and away from standard-of-care prosthetic users. This was achieved through targeted motor and sensory reinnervation, a closed-loop neural-machine interface, coupled to a noninvasive robotic architecture. Adding touch to motor control improves the ability to reach intended target grasp forces, find target durometers among distractors, and promote prosthetic ownership. Touch, kinesthesia, and motor control restore balanced decision strategies when identifying target durometers and intrinsic visuomotor behaviors that reduce the need to watch the prosthetic hand during object interactions, which frees the eyes to look ahead to the next planned action. The combination of these three modalities also enhances error correction performance. We applied our unified theoretical, functional, and clinical analyses, enabling us to define the relative contributions of the sensory and motor modalities operating simultaneously in this neural-machine interface. This multiperspective framework provides the necessary evidence to show that bionic prostheses attain more human-like function with effective sensory-motor restoration.

Topics & Concepts

ProprioceptionGRASPStimulus modalitySensory systemModalitiesMotor controlProsthetic handComputer scienceNeuroprostheticsInterface (matter)Physical medicine and rehabilitationNeurosciencePsychologyHuman–computer interactionArtificial intelligenceMedicineBubbleParallel computingProgramming languageSocial scienceSociologyMaximum bubble pressure methodMuscle activation and electromyography studiesNeuroscience and Neural EngineeringEEG and Brain-Computer Interfaces