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Design and implementation of FPGA-based muscle conduction velocity tracker in dynamic contractions during the gait

机译:步态动态收缩中FPGA基肌传导速度跟踪器的设计与实现

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The purpose of this paper is to prove the accuracy and reliability of a novel FPGA-based tracker of the muscle conduction velocity in ordinary dynamic contractions, such as during the gait. In this work, we present the digital signal-processing unit. The system performs the acquisition of the needed bio-signal, from 4 wireless surface EMG electrodes. The acquired data undergo to a dynamic bit-stream description of the signals. The latter ones are analyzed by a fast and accurate algorithm performing the comparison of signals derived by two EMG electrodes suitably positioned on the same muscle. The entire computation system fully operates in real-time on the Altera Cyclone V FPGA. The myoelectric signals have been recorded by 2 left and 2 right electrodes placed on the Left and Right Gastrocnemius of a subject involved in 1250 dynamic contractions. The in vivo measurements show that under the same experimental conditions, in 5 days, the system reveals a MCV mean value of 7.62±0.35 m/s demonstrating a good repeatability (reliability) of the measurements in long-time estimation application. In a real-time application, one step - one MCV, the tool typically shows the 98% (Best: 100%, Worst: 88%) of probability to provide the right MCV values, comparing it with the clinical literature.
机译:本文的目的是证明在普通动态收缩中的肌肉传导速度的新型FPGA的跟踪器的准确性和可靠性,例如在步态期间。在这项工作中,我们介绍了数字信号处理单元。系统从4个无线表面EMG电极执行所需的生物信号的获取。所获取的数据经历动态比特流描述信号。通过快速和准确的算法进行分析,该算法进行比较由两个EMG电极导出的信号的比较适当定位在同一肌肉上。整个计算系统在Altera Cyclone V FPGA上完全运行。肌电信号已被2左右的2个左右电极记录在1250个动态收缩的受试者的左右胃肠肿块上。体内测量表明,在相同的实验条件下,在5天内,系统显示MCV平均值为7.62±0.35 m / s,证明了长时间估计应用中的测量的良好重复性(可靠性)。在实时应用程序中,一个步骤 - 一个MCV,该工具通常显示98 %(最佳:100 %,最差:88 %)提供右MCV值的概率,与临床文献相比。

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