Motor noise removal for determining gait events over treadmill walking using wavelet filter.

Ho Jun Yeom, Brian P Selgrade, Young Hui Chang, Jung Lae Kim
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引用次数: 2

Abstract

The conventional method for filtering force plate data, low-pass filtering, does not always give accurate results when applied to force data from a custom-made, instrumented treadmill. Therefore, this study compares low-pass filtered data to the same data passed through a wavelet filter. We collected data with the treadmill running. However these include motor noise with ground reaction force at two force plates. We found that he proposed wavelet method eliminated motor noise to result in more accurate force plate data than the conventional low-pass filter, particularly at high speed motor operation. In this study we suggested the convolution wavelet (CNW) which was compared to that of a low-pass filter. The CNW showed better performance as compared to band-pass filtering particularly for low signal-to-noise ratios, and a lower computational load.
基于小波滤波的跑步机步态事件的运动噪声去除。
传统的过滤力板数据的方法,低通滤波,当应用于定制的仪器跑步机的力数据时,并不总是给出准确的结果。因此,本研究将低通滤波后的数据与通过小波滤波器的相同数据进行比较。我们在跑步机上收集数据。然而,这些包括电机噪声与地面反作用力在两个力板。我们发现,他提出的小波方法消除了电机噪声,得到的力板数据比传统的低通滤波器更准确,特别是在高速电机运行时。在这项研究中,我们提出了卷积小波(CNW),并将其与低通滤波器进行了比较。与带通滤波相比,CNW表现出更好的性能,特别是在低信噪比和更低的计算负荷方面。
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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