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

• Published in: Sensors (Basel, Switzerland) Vol. 19; no. 16; p. 3462
• Main Authors: Ji, Ning, Zhou, Hui, Guo, Kaifeng, Samuel, Oluwarotimi Williams, Huang, Zhen, Xu, Lisheng, Li, Guanglin
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 08.08.2019; MDPI
• Subjects: acceleration signal; Accelerometry; Adult; Algorithms; appropriate mother wavelet; Artificial intelligence; Female; Gait; Gait - physiology; gait event detection; Hemiplegia - physiopathology; hemiplegic gait; Humans; Machine learning; Male; Middle Aged; Paralysis; Posture; Sensors; Signal processing; Stroke; Time Factors; Wavelet Analysis; Wavelet transforms; wavelet-selection criteria; Young Adult; China; hemiplegic gait; acceleration signal; gait event detection; wavelet-selection criteria; appropriate mother wavelet

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 determinin...