Lin, Yi-Chung and Price, Kara and Carmichael, Declan S. and Maniar, Nirav and Hickey, Jack T. and Timmins, Ryan G. and Heiderscheit, Bryan C. and Blemker, Silvia S. and Opar, David A. (2023) Validity of Inertial Measurement Units to Measure Lower-Limb Kinematics and Pelvic Orientation at Submaximal and Maximal Effort Running Speeds. Sensors, 23 (23). p. 9599. ISSN 1424-8220

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Abstract

Inertial measurement units (IMUs) have been validated for measuring sagittal plane lower-limb kinematics during moderate-speed running, but their accuracy at maximal speeds remains less understood. This study aimed to assess IMU measurement accuracy during high-speed running and maximal effort sprinting on a curved non-motorized treadmill using discrete (Bland–Altman analysis) and continuous (root mean square error [RMSE], normalised RMSE, Pearson correlation, and statistical parametric mapping analysis [SPM]) metrics. The hip, knee, and ankle flexions and the pelvic orientation (tilt, obliquity, and rotation) were captured concurrently from both IMU and optical motion capture systems, as 20 participants ran steadily at 70%, 80%, 90%, and 100% of their maximal effort sprinting speed (5.36 ± 0.55, 6.02 ± 0.60, 6.66 ± 0.71, and 7.09 ± 0.73 m/s, respectively). Bland–Altman analysis indicated a systematic bias within ±1◦for the peak pelvic tilt, rotation, and lower-limb kinematics and −3.3◦ to −4.1◦ for the pelvic obliquity. The SPM analysis demonstrated a good agreement in the hip and knee flexion angles for most phases of the stride cycle, albeit with significant differences noted around the ipsilateral toe-off. The RMSE ranged from 4.3◦ (pelvic obliquity at 70% speed) to 7.8◦ (hip flexion at 100% speed). Correlation coefficients ranged from 0.44 (pelvic tilt at 90%) to 0.99 (hip and knee flexions at all speeds). Running speed minimally but significantly affected the RMSE for the hip and ankle flexions. The present IMU system is effective for measuring lower-limb kinematics during sprinting, but the pelvic orientation estimation was less accurate.

Item Type:	Article
Keywords:	gait analysis; IMU; inertial sensors; optical motion capture; running mechanics; root mean square error; Bland–Altman analysis; statistical parametric mapping; biomechanical model;
Academic Unit:	Faculty of Science and Engineering > Sports Science and Nutrition
Item ID:	18909
Identification Number:	https://doi.org/10.3390/s23239599
Depositing User:	Jack Hickey
Date Deposited:	19 Sep 2024 13:09
Journal or Publication Title:	Sensors
Publisher:	MDPI AG
Refereed:	Yes
URI:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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