Adaptive clustering of IMU-based gait models for personalized clinical gait analysis

Zhimin Zheng; Chen Gong; Tongchao Lu; Lifang Zhang; Lin Meng; Chunfeng Cui; Feng He

doi:10.1117/12.3044649

27 August 2024 Adaptive clustering of IMU-based gait models for personalized clinical gait analysis

Zhimin Zheng, Chen Gong, Tongchao Lu, Lifang Zhang, Lin Meng, Chunfeng Cui, Feng He

Proceedings Volume 13252, Fourth International Conference on Biomedicine and Bioinformatics Engineering (ICBBE 2024); 132522B (2024) https://doi.org/10.1117/12.3044649
Event: 2024 Fourth International Conference on Biomedicine and Bioinformatics Engineering (ICBBE 2024), 2024, Kaifeng, China

Abstract

Real-time home healthcare, enabled by future sixth-generation (6G) communication technology, offers a promising application for advanced clinical gait analysis. Utilization of dynamic sensors in clinical gait analysis presents a definitive approach for quantifying variances in gait patterns between patient cohorts and healthy populations. However, variations in demographic and anthropometric parameters, including gender, age, height, and Body Mass Index, among these groups, may result in inaccurate clinical evaluations. This study introduces an innovative clustering methodology that incorporates custom-weighted distances based on demographic and anthropometric parameters. This approach is designed to establish a dynamic, normative gait framework pertinent to healthy individuals. It facilitates the classification of individuals into distinct categories grounded on their demographic and anthropometric parameters, enabling the provision of a customized normative gait model appropriate for each category.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Zhimin Zheng, Chen Gong, Tongchao Lu, Lifang Zhang, Lin Meng, Chunfeng Cui, and Feng He "Adaptive clustering of IMU-based gait models for personalized clinical gait analysis", Proc. SPIE 13252, Fourth International Conference on Biomedicine and Bioinformatics Engineering (ICBBE 2024), 132522B (27 August 2024); https://doi.org/10.1117/12.3044649

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