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Utilisation of skewness of wavelet-based approximate coefficient in walking speed assessment

机译:基于小波近似系数的偏度在步行速度评估中的利用

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This study explores wavelet decomposition based skewness analysis for walking speed assessment. This has been achieved by using four force sensing resistors attached beneath the foot and one flex sensor attached on ankle. Experimentation is carried out on walking pattern of able individuals and data are collected using data acquiescing set-up and de-noised using Savitzky-Golay filter. De-noised data are then decomposed at different discrete wavelet transform (DWT) levels from where skewness values of approximate coefficient are assessed. Variation of skewness with respect to walking speed has been observed which shows that skewness values are having definite relations with walking speeds at certain DWT levels. Based on these, an algorithm is proposed for walking speed assessment. Experimentation is again carried out to validate the proposed algorithm. Satisfactory result is achieved indicating that assessment of wavelet decomposition based skewness of approximate coefficients may be very useful for walking speed measurement.
机译:本研究探索基于小波分解的偏度分析,以评估步行速度。这是通过使用四个安装在脚下的力感测电阻器和一个安装在脚踝上的挠曲传感器来实现的。对有能力的个人的行走方式进行实验,并使用默认的数据收集数据,并使用Savitzky-Golay滤波器对数据进行降噪。然后,在不同的离散小波变换(DWT)级别上对降噪后的数据进行分解,从中评估近似系数的偏度值。已经观察到偏斜度相对于步行速度的变化,这表明偏斜度值在某些DWT水平下与步行速度具有确定的关系。在此基础上,提出了一种步行速度评估算法。再次进行实验以验证所提出的算法。获得了令人满意的结果,表明基于小波分解的近似系数偏度的评估对于步行速度测量可能非常有用。

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