Smart Ankleband for Plug-and-Play Hand-Prosthetic Control

Dean Zadok, Oren salzman, Alon Wolf, Alex M. Bronstein

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Keywords: Prosthetic Arms, Wearable Robotics, Deep Learning Methods.

TL;DR: A novel, low-cost robotic system, enabling intuitive control of a robotic prosthetic hand through leg gestures via a smart ankleband.

Abstract: Building robotic prostheses requires a sensor-based interface designed to provide the robotic hand with the control required to perform hand gestures. Traditional Electromyography (EMG) based prosthetics and emerging alternatives often face limitations such as muscle-activation limitations, high cost, and complex calibrations. In this paper, we present a low-cost robotic system composed of a smart ankleband for intuitive, calibration-free control of a robotic hand, and a robotic prosthetic hand that executes actions corresponding to leg gestures. The ankleband integrates an Inertial Measurement Unit (IMU) sensor with a lightweight neural network to infer user-intended leg gestures from motion data. Our system represents a significant step towards higher adoption rates of robotic prostheses among arm amputees, as it enables one to operate a prosthetic hand using a low-cost, low-power, and calibration-free solution. To evaluate our work, we collected data from 10 subjects and tested our prototype ankleband with a robotic hand on an individual with an upper-limb amputation. Our results demonstrate that this system empowers users to perform daily tasks more efficiently, requiring few compensatory movements.

Track: 2. Sensors and systems for digital health, wellness, and athletics

NominateReviewer: Dean Zadok

Submission Number: 99