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Sensors 2016, 16(12), 2167; doi:10.3390/s16122167

Estimation of Temporal Gait Parameters Using a Wearable Microphone-Sensor-Based System

1,2,3,* , 1,3
,
1,2,3
,
1,2,3
,
1,3
and
3
1
Pervasive Computing Research Center, Institute of Computing Technology (ICT), Chinese Academy of Sciences (CAS), Beijing 100190, China
2
University of Chinese Academy of Sciences, Beijing 100049, China
3
Beijing Key Laboratory of Mobile Computing and Pervasive Devices, Beijing 100190, China
*
Author to whom correspondence should be addressed.
Academic Editor: Vittorio M. N. Passaro
Received: 7 November 2016 / Revised: 2 December 2016 / Accepted: 14 December 2016 / Published: 17 December 2016
(This article belongs to the Section Physical Sensors)
View Full-Text   |   Download PDF [4327 KB, uploaded 17 December 2016]   |  

Abstract

Most existing wearable gait analysis methods focus on the analysis of data obtained from inertial sensors. This paper proposes a novel, low-cost, wireless and wearable gait analysis system which uses microphone sensors to collect footstep sound signals during walking. This is the first time a microphone sensor is used as a wearable gait analysis device as far as we know. Based on this system, a gait analysis algorithm for estimating the temporal parameters of gait is presented. The algorithm fully uses the fusion of two feet footstep sound signals and includes three stages: footstep detection, heel-strike event and toe-on event detection, and calculation of gait temporal parameters. Experimental results show that with a total of 240 data sequences and 1732 steps collected using three different gait data collection strategies from 15 healthy subjects, the proposed system achieves an average 0.955 F1-measure for footstep detection, an average 94.52% accuracy rate for heel-strike detection and 94.25% accuracy rate for toe-on detection. Using these detection results, nine temporal related gait parameters are calculated and these parameters are consistent with their corresponding normal gait temporal parameters and labeled data calculation results. The results verify the effectiveness of our proposed system and algorithm for temporal gait parameter estimation. View Full-Text
Keywords: gait analysis; temporal parameter estimation; footstep sound; microphone sensor; wearable device gait analysis; temporal parameter estimation; footstep sound; microphone sensor; wearable device
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Wang, C.; Wang, X.; Long, Z.; Yuan, J.; Qian, Y.; Li, J. Estimation of Temporal Gait Parameters Using a Wearable Microphone-Sensor-Based System. Sensors 2016, 16, 2167.

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