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.
Abstract (translated)
构建机器人假肢需要设计一个基于传感器的接口，以便为机器手提供执行手势所需的控制。传统的肌电图（EMG）假肢和新兴替代方案常常面临肌肉激活限制、成本高昂以及复杂校准程序等问题。在这篇论文中，我们提出了一种低成本的机器人系统，该系统包括一个智能踝带，用于直观且无需校准地控制机器手，并配有一个执行与腿部动作对应的机器假手。此踝带集成了惯性测量单元（IMU）传感器和轻量级时间神经网络，可以从运动数据中推断出用户意图的腿部动作。我们的系统代表了在手臂截肢者中间增加机器人假肢使用率的一个重要步骤，因为它使人们能够通过低成本、低功耗且无需校准的方法来操作假手。 为了评估我们的研究成果，我们从10名受试者那里收集了数据，并对配备有原型踝带的机器手进行了一位上肢截肢者的测试。结果表明，该系统能够让用户更高效地完成日常任务，减少补偿性动作的需求。
URL
https://arxiv.org/abs/2503.17846
