Sensing and processing of bio-metric signals for use in low cost bio-robotic systems

Christopher Scott, G. S. Gupta, Liqiong Tang
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引用次数: 1

Abstract

Use of bio-metric signals, from muscle and neurons, to build intelligent control systems to mimic human behavior is an important area of active research. Such bio-robotic systems are finding use in rehabilitation and recovery of human organ functions. They also aid in removing the human beings from dangerous and hazardous working conditions. This paper reports the research attempts that have been undertaken to develop a cost-effective bio-driven robotic system for hand amputees, more precisely for wrist disarticulation. The system uses the EMG signals from an amputee's arm to realize a few commonly used finger and hand movements. The developed system is able to obtain the EMG signals through a specifically designed data acquisition and signal processing circuit. A specially designed finger unit has been built and the test model is able to carry out the desired functions of gripping an object. Initial outcomes are very promising and ongoing research will ensure that the entire system will be able to be driven by the amputees using their EMG signals and realize the functions of a selected finger and hand for their everyday activities.
用于低成本生物机器人系统的生物识别信号的传感和处理
利用来自肌肉和神经元的生物识别信号来构建模仿人类行为的智能控制系统是一个积极研究的重要领域。这种生物机器人系统正被用于人体器官功能的康复和恢复。他们还帮助人们远离危险和危险的工作条件。这篇论文报告了已经进行的研究尝试,以开发一种具有成本效益的生物驱动机器人系统,用于手部截肢者,更准确地说,用于腕部截肢。该系统利用截肢者手臂的肌电图信号来实现一些常用的手指和手部动作。该系统通过专门设计的数据采集和信号处理电路来获取肌电信号。建立了一个专门设计的手指单元,测试模型能够实现抓取物体的预期功能。初步结果非常有希望,正在进行的研究将确保整个系统能够由截肢者使用他们的肌电图信号来驱动,并实现他们选择的手指和手的日常活动功能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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