Unsupervised Gait Phase Estimation With Domain-Adversarial Neural Network and Adaptive Window

• Published in: IEEE journal of biomedical and health informatics Vol. 26; no. 7; pp. 3373 - 3384
• Main Authors: Choi, Wonseok, Yang, Wonseok, Na, Jaeyoung, Park, Juneil, Lee, Giuk, Nam, Woochul
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.07.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptive systems; Adaptive window; Algorithms; Classification algorithms; domain adaptation; domain-adversarial neural network; Domains; Embedding; Foot; Gait; gait phase; Legged locomotion; Machine learning; Model accuracy; Neural networks; Phase estimation; stride time; Thigh

The performanceof previous machine learning models for gait phase is only satisfactory under limited conditions. First, they produce accurate estimations only when the ground truth of the gait phase (of the target subject) is known. In contrast, when the ground truth of a target subject is not used...