A Synchronized Orthogonal Gait Phase Estimation Method Based on the Interthigh Angle

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Authors: Xiaoguang Wu, Zhihui Dong, Xiaochen Niu, Jintao Shang, Yuhan Jiang, Hongbin Lin, Yihao Du
Cited by: 0
References: 49

Abstract

The continuous real-time estimation of gait phase is a critical element for achieving natural synchronization between the user and the powered prosthesis. Traditional phase variable methods based on the unilateral thigh angle and its derivative or integral exhibit inherent limitations in nonlevel terrains (e.g., inclines and stairs), mainly attributed to the unequal positive and negative part area of single-leg angle curves and the phase shift between these curves and the standard cosine function. To address these limitations, this paper proposes a synchronized orthogonal gait phase estimation method based on inter-thigh angle. Based on the symmetry inherent in the synergistic locomotion of two legs, this study uses the inter-thigh angle as a phase variable candidate, whose intrinsic symmetry compensation mechanism directly eliminates the limitation of unequal positive and negative part area of the single-leg angle curve. By further implementing a zero-crossing-aligned gait cycle partitioning strategy, the proposed framework effectively overcomes the phase shift problem prevalent in conventional methods. Additionally, this study generates orthogonal cosine signals based on the inter-thigh angle, fundamentally circumventing the noise sensitivity inherent in thigh angle differential while suppressing drift errors associated with thigh angle integral, thereby improving the accuracy of gait phase estimation. Experimental results across various locomotion scenarios, including inclines, stairs, and speed variations, demonstrate that compared to time-based estimations and traditional phase variable methods, the proposed method reduces gait phase estimation errors by 33.88% and 65.09% respectively through symmetry compensation and phase correction.

Fields of Study & Subjects

Prosthetics and Rehabilitation Robotics Gait Recognition and Analysis Robotic Locomotion and Control

Publication details

Journal / source
IEEE Transactions on Instrumentation and Measurement
Volume
75
Pages
1–12
Publication date
1 January 2026
Language
EN