ArticleSensors (Basel, Switzerland)2016
Examination of Inertial Sensor-Based Estimation Methods of Lower Limb Joint Moments and Ground Reaction Force: Results for Squat and Sit-to-Stand Movements in the Sagittal Plane.
Article in Sensors (Basel, Switzerland), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 2 of them syntheses that pooled it.
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Who cites it
14 citing papers in PubMed, 2 syntheses or guidelines pooled it, 24 citations in OpenAlex.
- Estimation of Kinetics Using IMUs to Monitor and Aid in Clinical Decision-Making during ACL Rehabilitation: A Systematic Review.Sensors (Basel, Switzerland) · 2024Pooled it
- Inertial Motion Capture-Based Wearable Systems for Estimation of Joint Kinetics: A Systematic Review.Sensors (Basel, Switzerland) · 2022Pooled it
- Altered kinematics and muscle activities during half squats in people with ankle sprain history.PloS one · 2026Article
- Biodynamic Modeling and Analysis of Human-Exoskeleton Interactions in Simulated Patient Handling Tasks.Human factors · 2025Article
- Contribution of Tibialis Anterior in Sit-to-Stand Motion: Implications for Its Role in Shifting the Center of Pressure Backward.Journal of functional morphology and kinesiology · 2025Article
- The interrelationship between lower limb movement, muscle activity, and joint moment during half squat and gait.Heliyon · 2023Article
- Analysis of Comfort during Transfer by a Dual-Arm Care Robot Based on Human Body Pressure and Surface Electromyographic Signals.Bioengineering (Basel, Switzerland) · 2023Article
- Temporal, Kinematic and Kinetic Variables Derived from a Wearable 3D Inertial Sensor to Estimate Muscle Power during the 5 Sit to Stand Test in Older Individuals: A Validation Study.Sensors (Basel, Switzerland) · 2023Article
- Recent Trends and Practices Toward Assessment and Rehabilitation of Neurodegenerative Disorders: Insights From Human Gait.Frontiers in neuroscience · 2022Review
- Foot Position Measurement during Assistive Motion for Sit-to-Stand Using a Single Inertial Sensor and Shoe-Type Force Sensors.International journal of environmental research and public health · 2021Article
- A Novel Simplified System to Estimate Lower-Limb Joint Moments during Sit-to-Stand.Sensors (Basel, Switzerland) · 2021Article
- Possible predictive formulas for quantitative and time-based estimation of muscle strength during motion.Journal of physical therapy science · 2020Article
- Indirect Measurement of Ground Reaction Forces and Moments by Means of Wearable Inertial Sensors: A Systematic Review.Sensors (Basel, Switzerland) · 2018Review
- Inertial Sensor-Based Motion Analysis of Lower Limbs for Rehabilitation Treatments.Journal of healthcare engineering · 2017Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Joint moment estimation by a camera-based motion measurement system and a force plate has a limitation of measurement environment and is costly. The purpose of this paper is to evaluate quantitatively inertial sensor-based joint moment estimation methods with five-link, four-link and three-link rigid body models using different trunk segmented models. Joint moments, ground reaction forces (GRF) and center of pressure (CoP) were estimated for squat and sit-to-stand movements in the sagittal plane measured with six healthy subjects. The five-link model and the four-link model that the trunk was divided at the highest point of the iliac crest (four-link-IC model) were appropriate for joint moment estimation with inertial sensors, which showed average RMS values of about 0.1 Nm/kg for all lower limb joints and average correlation coefficients of about 0.98 for hip and knee joints and about 0.80 for ankle joint. Average root mean square (RMS) errors of horizontal and vertical GRFs and CoP were about 10 N, 15 N and 2 cm, respectively. Inertial sensor-based method was suggested to be an option for estimating joint moments of the trunk segments. Inertial sensors were also shown to be useful for the bottom-up estimation method using measured GRFs, in which average RMS values and average correlation coefficients were about 0.06 Nm/kg and larger than about 0.98 for all joints.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.