Gait phase recognition of lower limb exoskeleton system based on the integrated network model

[Display omitted] •A new gait recognition method based on integrated network model is proposed for identifying four phases in the gait cycle, including heel strike, foot flat, heel off and swing phase.•This paper adopts sparse autoencoder into the model to extract key features of gait information an...

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Veröffentlicht in:	Biomedical signal processing and control Jg. 76; S. 103693
Hauptverfasser:	Zhang, Zaifang, Wang, Zhaoyang, Lei, Han, Gu, Wenquan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.07.2022
Schlagworte:	Bidirectional long short-term memory Deep neural network Exoskeleton robot Gait phase recognition Sparse autoencoder Deep neural network Sparse autoencoder Gait phase recognition Bidirectional long short-term memory Exoskeleton robot
ISSN:	1746-8094, 1746-8108
Online-Zugang:	Volltext
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