ArticleSensors (Basel, Switzerland)2021
Real-Time Musculoskeletal Kinematics and Dynamics Analysis Using Marker- and IMU-Based Solutions in Rehabilitation.
Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed.
- Musculoskeletal Inverse Kinematics Tool for Inertial Motion Capture Data Based on the Adaptive Unscented Kalman Smoother: An Implementation for OpenSim.Annals of biomedical engineering · 2025Article
- Use of Technologies for the Acquisition and Processing Strategies for Motion Data Analysis.Biomimetics (Basel, Switzerland) · 2025Review
- AI Revolution in Orthopedic Biomechanics: From Fracture Classification to Real-Time Simulations.The archives of bone and joint surgery · 2025Article
- Role of joint interactions in upper limb joint movements: a disability simulation study using wearable inertial sensors for 3D motion capture.Journal of neuroengineering and rehabilitation · 2024Article
- Surface Electromyography Data Analysis for Evaluation of Physical Exercise Habits between Athletes and Non-Athletes during Indoor Rowing.Sensors (Basel, Switzerland) · 2024Article
- IMU-Based Energy Expenditure Estimation for Various Walking Conditions Using a Hybrid CNN-LSTM Model.Sensors (Basel, Switzerland) · 2024Article
- A review of combined functional neuroimaging and motion capture for motor rehabilitation.Journal of neuroengineering and rehabilitation · 2024Review
- Method for Using IMU-Based Experimental Motion Data in BVH Format for Musculoskeletal Simulations via OpenSim.Sensors (Basel, Switzerland) · 2023Article
- Ten steps to becoming a musculoskeletal simulation expert: A half-century of progress and outlook for the future.Journal of biomechanics · 2023Review
- A Wearable Real-time Kinematic and Kinetic Measurement Sensor Setup for Human Locomotion.Wearable technologies · 2023Article
- Article
- Predictive simulation of single-leg landing scenarios for ACL injury risk factors evaluation.PloS one · 2023Article
- Fusion of Wearable Kinetic and Kinematic Sensors to Estimate Triceps Surae Work during Outdoor Locomotion on Slopes.Sensors (Basel, Switzerland) · 2022Article
- Editorial: Neuromechanics of Hip Osteoarthritis.Frontiers in sports and active living · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
This study aims to explore the possibility of estimating a multitude of kinematic and dynamic quantities using subject-specific musculoskeletal models in real-time. The framework was designed to operate with marker-based and inertial measurement units enabling extensions far beyond dedicated motion capture laboratories. We present the technical details for calculating the kinematics, generalized forces, muscle forces, joint reaction loads, and predicting ground reaction wrenches during walking. Emphasis was given to reduce computational latency while maintaining accuracy as compared to the offline counterpart. Notably, we highlight the influence of adequate filtering and differentiation under noisy conditions and its importance for consequent dynamic calculations. Real-time estimates of the joint moments, muscle forces, and reaction loads closely resemble OpenSim's offline analyses. Model-based estimation of ground reaction wrenches demonstrates that even a small error can negatively affect other estimated quantities. An application of the developed system is demonstrated in the context of rehabilitation and gait retraining. We expect that such a system will find numerous applications in laboratory settings and outdoor conditions with the advent of predicting or sensing environment interactions. Therefore, we hope that this open-source framework will be a significant milestone for solving this grand challenge.
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What OpenQuestion holds
Registered trials
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.