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
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: |
|
| 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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