A Learning‐Based Sensor Array for Untethered Soft Prosthetic Hand Aiming at Restoring Tactile Sensation

Author:

Xu Haipeng12,Rong Yu12,Ren Jieji12,Zhang Ningbin12,Zhao Yi12,Yang Xinyu12,Zhu Zhenpu12,Gu Guoying12ORCID

Affiliation:

1. Robotics Institute School of Mechanical Engineering Shanghai Jiao Tong University Shanghai 200240 China

2. State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong University Shanghai 200240 China

Abstract

Endowing tactile feedback for prosthetic hands is profound for upper‐limb amputees. However, existing prosthetic hands are generally not in possession of the embedded sensory feedback. Herein, a flexible tactile sensor array which can be integrated into an untethered soft prosthetic hand to achieve static and dynamic discrimination tasks is presented. The flexible piezoresistive sensory arrays with 25 sensor units which can be arranged on five fingers of the soft prosthetic hand are fabricated. According to the collected large‐scale tactile dataset (including pressure distribution and pressure magnitude) during different grasping tasks, a learning‐based classification model that can reveal the correspondences between tactile information and object attributes while interacting with touched objects is developed. To transfer tactile information extracted from tactile sensor arrays, a wearable vibrotactile feedback band with a spatial coding feedback strategy is implemented by selectively activating vibrotactile motors located on the skin of the upper arm. In a set of tests performed by an individual with transradial amputation and eight able‐bodied subjects, the soft prosthetic hand integrated with tactile sensor arrays can help the users regain finger tactile sensation, discriminate grasped objects, and achieve real‐time dynamic rolling detection.

Funder

National Natural Science Foundation of China

Science and Technology Commission of Shanghai Municipality

Publisher

Wiley

Subject

General Medicine

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