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声学步态:基于脚步声的步态分析

Acoustic Gaits: Gait Analysis With Footstep Sounds.

作者信息

Altaf M Umair Bin, Butko Taras, Juang Biing-Hwang Fred

出版信息

IEEE Trans Biomed Eng. 2015 Aug;62(8):2001-11. doi: 10.1109/TBME.2015.2410142. Epub 2015 Mar 5.

Abstract

We describe the acoustic gaits-the natural human gait quantitative characteristics derived from the sound of footsteps as the person walks normally. We introduce the acoustic gait profile, which is obtained from temporal signal analysis of sound of footsteps collected by microphones and illustrate some of the spatio-temporal gait parameters that can be extracted from the acoustic gait profile by using three temporal signal analysis methods-the squared energy estimate, Hilbert transform and Teager-Kaiser energy operator. Based on the statistical analysis of the parameter estimates, we show that the spatio-temporal parameters and gait characteristics obtained using the acoustic gait profile can consistently and reliably estimate a subset of clinical and biometric gait parameters currently in use for standardized gait assessments. We conclude that the Teager-Kaiser energy operator provides the most consistent gait parameter estimates showing the least variation across different sessions and zones. Acoustic gaits use an inexpensive set of microphones with a computing device as an accurate and unintrusive gait analysis system. This is in contrast to the expensive and intrusive systems currently used in laboratory gait analysis such as the force plates, pressure mats and wearable sensors, some of which may change the gait parameters that are being measured.

摘要

我们描述了声学步态——即人正常行走时从脚步声中获取的自然人类步态定量特征。我们引入了声学步态轮廓,它是通过对麦克风收集的脚步声的时间信号分析获得的,并说明了一些时空步态参数,这些参数可以通过三种时间信号分析方法——平方能量估计、希尔伯特变换和蒂杰 - 凯泽能量算子从声学步态轮廓中提取。基于对参数估计的统计分析,我们表明,使用声学步态轮廓获得的时空参数和步态特征能够一致且可靠地估计当前用于标准化步态评估的一部分临床和生物特征步态参数。我们得出结论,蒂杰 - 凯泽能量算子提供了最一致的步态参数估计,在不同会话和区域中显示出最小的变化。声学步态使用一组带有计算设备的廉价麦克风作为准确且非侵入性的步态分析系统。这与目前实验室步态分析中使用的昂贵且侵入性的系统形成对比,如测力板、压力垫和可穿戴传感器,其中一些可能会改变正在测量的步态参数。

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