A Conceptual Framework for Drift-Aware IMU-Based Gait Analysis Using Motion Capture References.

Authors

Eugene Rezk

Published in

Sensors (Basel, Switzerland). Volume 26. Issue 20. Oct 21, 2026. Epub Oct 21, 2026.

Abstract

Inertial measurement unit (IMU)-based gait analysis represents a promising modality for telemedical assessment; however, integration drift remains a fundamental limitation for reliable long-term motion estimation. In this perspective, we propose a conceptual framework for drift-aware IMU-based gait reconstruction that combines established drift-mitigation techniques with phase-dependent analysis of reconstruction residuals. The framework envisages comparing IMU-derived trajectories with motion-capture-derived reference trajectories to quantify reconstruction errors and characterize their temporal and gait-phase-dependent structure in future validation studies. It is hypothesized that these residuals may exhibit structured, gait-phase-dependent patterns arising from multiple sources, including sensor-related errors and biomechanical variability. Drift is therefore treated primarily as a technical error source, while any association between residual error patterns and gait stability or motor-control characteristics remains a hypothesis requiring future validation. The framework outlines a potential approach for integrating wearable inertial sensing, motion-capture-based reference data, and probabilistic filtering techniques. It may provide a conceptual foundation for future telemedical gait assessment systems incorporating phase-dependent analysis of reconstruction errors.

PMID:
42944520
Bibliographic data and abstract were imported from PubMed on 27 Oct 2026.

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