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

2025-03-22

AI Summary

Traditional myoelectric prostheses suffer from reliance on residual limb muscle activation, high cost, and complex user-specific calibration. To address these limitations, this work proposes a low-cost, calibration-free ankle-band control paradigm that substitutes hand electromyographic (EMG) signals with inertial motion of the ankle for intuitive five-finger robotic hand control. Our method integrates a miniature inertial measurement unit (IMU) with a lightweight temporal neural network to decode real-time lower-limb pose sequences and directly map them to predefined hand gestures—eliminating the need for user adaptation or individualized calibration. This study presents the first demonstration of using lower-limb inertial signals for upper-limb prosthesis control, enabling plug-and-play operation, ultra-low power consumption, and zero-calibration deployment. Experimental evaluation shows an average gesture recognition accuracy of 96.2% across ten able-bodied participants; additionally, one upper-limb amputee successfully completed multiple activities of daily living, exhibiting a 42% reduction in compensatory movements and significantly improved operational efficiency.

Technology Category

• Intelligent Robots: Manipulation
• Computer Vision: Biometrics, Face, Gesture & Pose
• Machine Learning: Calibration & Uncertainty Quantification

Application Category

• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments

Abstract

Building robotic prostheses requires the creation of 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-calibration procedures. 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 temporal 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 upper-limb amputations. Our results demonstrate that this system empowers users to perform daily tasks more efficiently, requiring few compensatory movements.

Problem

• Develops calibration-free prosthetic control via ankle gestures
• Addresses cost and complexity in traditional EMG prosthetics
• Enables intuitive hand-prosthetic operation for arm amputees

Innovation

• Smart ankleband controls robotic hand
• IMU sensor with neural network
• Low-cost calibration-free prosthetic solution