Abstract:

In recent years, the inertial measurement units (IMUs) have been widely utilized in gait analysis and research due to their convenience. To address the issues of low accuracy and limited applicability in the current gait estimation algorithm, a gait feature estimation method based on inertial sensors is proposed. Two IMUs are fixed above the ankles of a subject, the collected data are transformed into the global coordinate system, and the gait events are identified. Double integration of linear acceleration is performed to obtain spatial pose information, and a zero-speed discrimination method and an error compensation method tailored to the gait cycle characteristics are introduced to mitigate integral drift, enabling extraction of corresponding gait variables. The data collected by optical motion capture system is taken as the gold standard, and the proposed method is compared with it. The average measurement accuracy (± standard deviation) for stride lengths in healthy gait and simulated abnormal gait is -0.035±0.023m and -0.022±0.020m, respectively. Pearson correlation coefficients between the estimated results and the gait standard are all greater than 0.9, and the simulation of abnormal gait demonstrates the adaptability of the proposed method in different populations. The research findings indicate that the proposed method excels in estimating the ankle joint-related gait parameters, with consistent measurement accuracy observed between normal and simulated abnormal gaits, offering a user-friendly alternative optical motion capture method.

Key words: gait analysis, inertial measurementunit, gait event, ergonomics