Human Gait phases recognition based on multi-source data fusion and BILSTM attention neural network

• Published in: Measurement : journal of the International Measurement Confederation Vol. 238; p. 115396
• Main Authors: Zhan, Haoran, Kou, Jiange, Cao, Yuanchao, Guo, Qing, Zhang, Jiyu, Shi, Yan
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.10.2024
• Subjects: BILSTM attention neural network; Gait recognition; Lightweight gait acquisition device; Lower limb exoskeleton; Multi-source data fusion; Lower limb exoskeleton; Lightweight gait acquisition device; Gait recognition; BILSTM attention neural network; Multi-source data fusion

A human gait recognition algorithm with deep learning based on multi-source data fusion is proposed to assist exoskeleton realizing complex human-exoskeleton cooperative motion. A lightweight gait acquisition device simultaneously acquires three different types of sensor signals, i.e., thigh surface...