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首页> 外文期刊>IEEE transactions on rehabilitation engineering >A low-cost instrumented glove for monitoring forces during object manipulation
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A low-cost instrumented glove for monitoring forces during object manipulation

机译:一种低成本的仪器手套,用于在物体操纵过程中监控力

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摘要

A rehabilitation program toward restoring upper limb movements based on neuromuscular electrical stimulation (NMES) depends on closed-loop control performance, which has been limited by the development of sensors for practical daily use. This work proposes a system to obtain force feedback. The system is comprised of a Lycra commercial glove with force sensing resistors (FSRs) attached to the distal phalanxes of the thumb, index and long fingers. After amplification and filtering, the signal is digitized through an analog-to-digital (A/D) converter. The polynomial fitting coefficients for the characteristic curves, obtained during the sensor calibration process, were inserted in the software thus enabling the reading of forces exerted during object manipulation. The system was applied to 30 normal subjects in order to verify its feasibility and to acquire knowledge of the normal hand function. Different ways of grasping have been detected according to the Force versus Time curve pattern and to the fingers predominantly used in grasping. Results have also shown the influence of parameters such as gender, age, hand size, and object weight in the normal function. The system did show efficacy. It was able to determine grasp forces during object manipulation for up to 73% of the studied sample. This is significant since a single glove was used in a wide range of subjects. For best results in medical applications, the glove should be tailored to the particular characteristics of an individual user.
机译:基于神经肌肉电刺激(NMES)来恢复上肢运动的康复计划取决于闭环控制性能,该性能已受到日常实用传感器的开发的限制。这项工作提出了一种获得力反馈的系统。该系统由Lycra商用手套组成,其力感测电阻器(FSR)连接到拇指,食指和长手指的远端指骨。经过放大和滤波后,信号将通过模数(A / D)转换器进行数字化。在传感器校准过程中获得的特性曲线的多项式拟合系数被插入到软件中,从而能够读取物体操纵过程中施加的力。该系统已应用于30名正常受试者,以验证其可行性并获得有关正常手功能的知识。根据力对时间曲线图和主要用于抓握的手指,已检测到不同的抓握方式。结果还显示了诸如性别,年龄,手掌大小和物体重量等参数对正常功能的影响。该系统确实显示出功效。它能够确定多达73%的研究样本在物体操纵过程中的抓握力。这是很重要的,因为单个手套被用于广泛的对象。为了在医疗应用中获得最佳效果,手套应根据个人使用者的特定特征进行定制。

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