Acquisition and processing of electromyographic signals for the control of a virtual vehicle in real time

Respuestas Pub Date : 2020-01-01 DOI:10.22463/0122820X.2402
José Luis Carrero-Carrero, L. Mendoza, Z. C. Nieto-Sánchez
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Abstract

espanolEste trabajo, se presenta el registro y clasificacion de las senales electromiograficas (EMG) de las extremidades inferiores, especificamente del musculo basto, con el fin de controlar un vehiculo virtual disenado en Blender. El sistema tiene de 4 canales, con una interfaz grafica, que permite el control de un vehiculo virtual. Para el procesamiento de las senales, se utilizaron diferentes herramientas matematicas tales como: analisis de Fourier y analisis wavelet. Estas tecnicas se usaron con el objetivo de comprimir datos, obtener patrones caracteristicos en cada conjunto de senales y realizar un filtrado digital. El control del automovil consta de 4 comandos como: acelerar, detenerse, giro derecha y giro izquierda, las cuales son las instrucciones basicas para el manejo real de un automovil. Los resultados mostraron que es posible usar senales biologicas para realizar controles virtuales (video juego). Asi mismo, se verifico que la parametrizar encontrada de cada grupo de senales EMG, fue satisfactoria, ya que el porcentaje de errores de las 4 variables estudiadas fue del 0.04% para un total de 400 ejecuciones. Este porcentaje de error corrobora que el sistema tiene gran potencialidad para posibles aplicaciones futuras. EnglishThis work presents the registration and classification of the electromyographic (EMG) signals of the lower extremities, specifically of the gross muscle, in order to control a virtual vehicle designed in Blender. The system has 4 channels, with a graphic interface, which allows the control of a virtual vehicle. For the processing of the signals, different mathematical tools were used such as: Fourier analysis and wavelet analysis. These techniques were used in order to compress data, obtain characteristic patterns in each set of signals and perform digital filtering. The control of the car consists of 4 commands such as: accelerate, stop, right turn and left turn, which are the basic instructions for the real operation of a car. The results showed that it is possible to use biological signals to perform virtual controls (video game). Likewise, it was verified that the parameterization found for each group of EMG signals was satisfactory, since the percentage of errors of the 4 variables studied was 0.04% for a total of 400 executions. This error percentage corroborates that the system has great potential for possible future applications.
肌电信号的采集与处理,用于虚拟车辆的实时控制
本文介绍了下肢肌电图信号(EMG)的记录和分类,特别是肌肉,以控制在Blender中设计的虚拟车辆。该系统有4个通道,带有图形界面,可以控制虚拟车辆。对于信号处理,使用了不同的数学工具,如傅里叶分析和小波分析。这些技术被用于压缩数据,获得每个信号集的特征模式,并执行数字滤波。汽车控制包括4个命令,如:加速,停止,右转和左转,这是真正驾驶汽车的基本指令。结果表明,利用生物信号进行虚拟控制(电子游戏)是可能的。此外,我们发现每组肌电信号的参数化是令人满意的,因为4个变量的错误率为0.04%,总共400次执行。这个错误率证实了该系统在未来可能的应用中具有巨大的潜力。本文介绍了下肢,特别是大肌肉的肌电图(EMG)信号的登记和分类,以控制在Blender中设计的虚拟车辆。该系统有4个通道,带有图形界面,允许控制虚拟车辆。= =地理= =根据美国人口普查,这个县的面积为。= =地理= =根据美国人口普查,这个县的面积为,其中土地面积为,其中土地面积为。The control of The car包含4 commands,如:accelerate, stop right turn and left turn, which are The basic实际说明for The operation of a car。结果表明,利用生物信号进行虚拟控制(电子游戏)是可能的。同样,对每组肌电信号的参数化发现是令人满意的,因为在总共400次执行中,所研究的4个变量的错误率为0.04%。这个误差百分比证实了该系统在未来可能的应用中具有巨大的潜力。
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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