ArticleScientific reports2024
Using inertial measurement units to estimate spine joint kinematics and kinetics during walking and running.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- The effect of two types of pyramidal and reverse pyramidal loading on spine and pelvis coordination variability during deadlift.BMC musculoskeletal disorders · 2026Article
- Visual-Inertial Fusion Framework for Isolating Seated Human-Body Vibration in Dynamic Vehicular Environments.Sensors (Basel, Switzerland) · 2026Article
- Deep learning based screening and regular assessment of adolescent idiopathic scoliosis using wearable IMU sensors.Frontiers in bioengineering and biotechnology · 2026Article
- Electromyography activity of posterior oblique sling muscles during high-speed running in elite soccer players: risk factors for hamstring injury.BMC sports science, medicine & rehabilitation · 2025Article
- Bioengineering Support in the Assessment and Rehabilitation of Low Back Pain.Bioengineering (Basel, Switzerland) · 2025Review
- A Machine Learning Approach for Predicting Pedaling Force Profile in Cycling.Sensors (Basel, Switzerland) · 2024Article
- A Novel Method and System Implementation for Precise Estimation of Single-Axis Rotational Angles.Sensors (Basel, Switzerland) · 2024Article
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6 authors.
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Abstract
Optical motion capture (OMC) is considered the best available method for measuring spine kinematics, yet inertial measurement units (IMU) have the potential to collect data outside the laboratory. When combined with musculoskeletal modeling, IMU technology may be used to estimate spinal loads in real-world settings. To date, IMUs have not been validated for estimates of spinal movement and loading during both walking and running. Using OpenSim Thoracolumbar Spine and Ribcage models, we compare IMU and OMC estimates of lumbosacral (L5/S1) and thoracolumbar (T12/L1) joint angles, moments, and reaction forces during gait across six speeds for five participants. For comparisons, time series are ensemble averaged over strides. Comparisons between IMU and OMC ensemble averages have low normalized root mean squared errors (< 0.3 for 81% of comparisons) and high, positive cross-correlations (> 0.5 for 91% of comparisons), suggesting signals are similar in magnitude and trend. As expected, joint moments and reaction forces are higher during running than walking for IMU and OMC. Relative to OMC, IMU overestimates joint moments and underestimates joint reaction forces by 20.9% and 15.7%, respectively. The results suggest using a combination of IMU technology and musculoskeletal modeling is a valid means for estimating spinal movement and loading.
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