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Article

Appropriate Mother Wavelets for Continuous Gait Event Detection Based on Time-Frequency Analysis for Hemiplegic and Healthy Individuals

1
College of Medicine and Biological Information Engineering, Northeastern University, Shenyang 110819, China
2
CAS Key Lab of Human-Machine Intelligence-Synergy Systems of Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences (CAS), Shenzhen 518055, China
3
School of Automation, Nanjing University of Science and Technology, Nanjing 210094, China
4
Panyu Central Hospital, Guangzhou 511400, China
*
Authors to whom correspondence should be addressed.
Received: 20 May 2019 / Revised: 24 June 2019 / Accepted: 2 July 2019 / Published: 8 August 2019
(This article belongs to the Special Issue Sensors for Gait, Posture, and Health Monitoring)
Gait event detection is a crucial step towards the effective assessment and rehabilitation of motor dysfunctions. Recently, the continuous wavelet transform (CWT) based methods have been increasingly proposed for gait event detection due to their robustness. However, few investigations on determining the appropriate mother wavelet with proper selection criteria have been performed, especially for hemiplegic patients. In this study, the performances of commonly used mother wavelets in detecting gait events were systematically investigated. The acceleration signals from the tibialis anterior muscle of both healthy and hemiplegic subjects were recorded during ground walking and the two core gait events of heel strike (HS) and toe off (TO) were detected from the signal recordings by a CWT algorithm with different mother wavelets. Our results showed that the overall performance of the CWT algorithm in detecting the two gait events was significantly different when using various mother wavelets. By using different wavelet selection criteria, we also found that the accuracy criteria based on time-error minimization and F1-score maximization could provide the appropriate mother wavelet for gait event detection. The findings from this study will provide an insight on the selection of an appropriate mother wavelet for gait event detection and facilitate the development of adequate rehabilitation aids. View Full-Text
Keywords: gait event detection; hemiplegic gait; appropriate mother wavelet; acceleration signal; wavelet-selection criteria gait event detection; hemiplegic gait; appropriate mother wavelet; acceleration signal; wavelet-selection criteria
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MDPI and ACS Style

Ji, N.; Zhou, H.; Guo, K.; Samuel, O.W.; Huang, Z.; Xu, L.; Li, G. Appropriate Mother Wavelets for Continuous Gait Event Detection Based on Time-Frequency Analysis for Hemiplegic and Healthy Individuals. Sensors 2019, 19, 3462. https://0-doi-org.brum.beds.ac.uk/10.3390/s19163462

AMA Style

Ji N, Zhou H, Guo K, Samuel OW, Huang Z, Xu L, Li G. Appropriate Mother Wavelets for Continuous Gait Event Detection Based on Time-Frequency Analysis for Hemiplegic and Healthy Individuals. Sensors. 2019; 19(16):3462. https://0-doi-org.brum.beds.ac.uk/10.3390/s19163462

Chicago/Turabian Style

Ji, Ning, Hui Zhou, Kaifeng Guo, Oluwarotimi W. Samuel, Zhen Huang, Lisheng Xu, and Guanglin Li. 2019. "Appropriate Mother Wavelets for Continuous Gait Event Detection Based on Time-Frequency Analysis for Hemiplegic and Healthy Individuals" Sensors 19, no. 16: 3462. https://0-doi-org.brum.beds.ac.uk/10.3390/s19163462

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