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13 March 2024 Gait assessment with inertial measurement units: similarity score of walking gait on treadmill and outdoor overground reflected in lower limb angular velocity and acceleration in typically developing children
Amanrai Kahlon, Khushboo Verma, Alexander Sage, Samuel C. K. Lee, Ahad Behboodi
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Proceedings Volume PC12838, Biophotonics in Exercise Science, Sports Medicine, Health Monitoring Technologies, and Wearables V; PC128380B (2024) https://doi.org/10.1117/12.3003530
Event: SPIE BiOS, 2024, San Francisco, California, United States
Abstract
To identify optimal kinematic signals for reliable use as inputs to machine learning-based gait monitoring systems (without extensive data processing), we quantified the level of changes in two kinematic signals around three axes in four locations. Wearing inertial motion unit wearables (IMU), 30 typically developing children (8-18yrs) walked on treadmill & outdoor overground at three different speeds giving a sizable normative dataset. Primary outcome measures were curve-based similarity analysis (specifically, cosine, Euclidean distance, Poincare and a newly defined Bilateral Symmetry Dissimilarity Test, BSDT) between treadmill and outdoor over-ground walking. Similarity analysis showed a distinct previously unreported high/middle/bottom banding pattern and superior-inferior shank acceleration (SI shank Acc) and medial-lateral shank angular velocity (ML shank AV) demonstrated the least variability across the different walking conditions (as measured by the BSDT). As secondary outcomes measure, conventional spatiotemporal gait parameters (parameter-based similarity analysis) were measured and showed varying differences across walking speeds consistent with previous literature.
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(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Amanrai Kahlon, Khushboo Verma, Alexander Sage, Samuel C. K. Lee, and Ahad Behboodi "Gait assessment with inertial measurement units: similarity score of walking gait on treadmill and outdoor overground reflected in lower limb angular velocity and acceleration in typically developing children", Proc. SPIE PC12838, Biophotonics in Exercise Science, Sports Medicine, Health Monitoring Technologies, and Wearables V, PC128380B (13 March 2024); https://doi.org/10.1117/12.3003530
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KEYWORDS
Gait analysis
Kinematics
Machine learning
Angular velocity
Signal processing
Statistical analysis
Anatomy
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