SynthesisSensors (Basel, Switzerland)2020
Inertial Sensor-Based Lower Limb Joint Kinematics: A Methodological Systematic Review.
Synthesis in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 69 papers, 2 of them syntheses that pooled it.
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
69 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Inertial Motion Capture-Based Wearable Systems for Estimation of Joint Kinetics: A Systematic Review.Sensors (Basel, Switzerland) · 2022Pooled it
- Sensor-to-Segment Calibration Methodologies for Lower-Body Kinematic Analysis with Inertial Sensors: A Systematic Review.Sensors (Basel, Switzerland) · 2020Pooled it
- Effects of Quadriceps Strengthening Exercise with Blood Flow Restriction on Knee Angular Velocity, Strength, and Balance in Fencers.Journal of sports science & medicine · 2026Trial
- Trial
- IMU- and Vision-Based Measurement Techniques for Joint Kinematics: A Narrative Review.Sensors (Basel, Switzerland) · 2026Review
- Artificial intelligence for gait and balance in neurological disorders: a scoping review of clinical applications and technologies.Journal of neurology · 2026Article
- Estimating Magnetic Field at Joint Centers Reduces Kinematic Errors in Inertial Motion Capture.Research square · 2026Article
- Validity, Reliability and Interpretability of an IMU-Based System to Measure 3D Lower Limb Kinematics of Patients with Heterogeneous Gait Disorders.Sensors (Basel, Switzerland) · 2026Article
- Prediction of Three-Dimensional Ground Reaction Forces in the Golf Swing Using Wearable Inertial Measurement Units and Biomimetic Deep Learning Models.Biomimetics (Basel, Switzerland) · 2026Article
- Comparative Analysis of Robotic Assistive Devices on Paretic Knee Motion in Post-Stroke Patients: An IMU-Based Pilot Study.Journal of functional morphology and kinesiology · 2025Article
- Biomechanics of Human Motion and Its Clinical Applications: Instrumented Gait Analysis.Bioengineering (Basel, Switzerland) · 2025Article
- Bridging the Methodological Gap Between Inertial Sensors and Optical Motion Capture: Deep Learning as the Path to Accurate Joint Kinematic Modelling Using Inertial Sensors.Sensors (Basel, Switzerland) · 2025Article
- Quantification of 3D Kinematic Measurements for Knee Flexion and Tibial Rotation Using an IMU-Based Sensor and Ultrasound Imaging System: A Cadaveric Study.Sensors (Basel, Switzerland) · 2025Article
- Use of Technologies for the Acquisition and Processing Strategies for Motion Data Analysis.Biomimetics (Basel, Switzerland) · 2025Review
- Relationship Between Lower-Extremity Co-Contraction and Jerk During Gait.Sensors (Basel, Switzerland) · 2025Article
- Optimization of MIMU Mounting Position on Shank in Posture Estimation Considering Muscle Protuberance.Sensors (Basel, Switzerland) · 2025Article
- Gait Speed and Task Specificity in Predicting Lower-Limb Kinematics: A Deep Learning Approach Using Inertial Sensors.Mayo Clinic proceedings. Digital health · 2025Article
- Utilising Inertial Measurement Units and Force-Velocity Profiling to Explore the Relationship Between Hamstring Strain Injury and Running Biomechanics.Sensors (Basel, Switzerland) · 2025Article
- Learning based lower limb joint kinematic estimation using open source IMU data.Scientific reports · 2025Article
- Validation of Markerless Motion Capture for Soldier Movement Patterns Assessment Under Varying Body-Borne Loads.Annals of biomedical engineering · 2025Article
9 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
The use of inertial measurement units (IMUs) has gained popularity for the estimation of lower limb kinematics. However, implementations in clinical practice are still lacking. The aim of this review is twofold-to evaluate the methodological requirements for IMU-based joint kinematic estimation to be applicable in a clinical setting, and to suggest future research directions. Studies within the PubMed, Web Of Science and EMBASE databases were screened for eligibility, based on the following inclusion criteria: (1) studies must include a methodological description of how kinematic variables were obtained for the lower limb, (2) kinematic data must have been acquired by means of IMUs, (3) studies must have validated the implemented method against a golden standard reference system. Information on study characteristics, signal processing characteristics and study results was assessed and discussed. This review shows that methods for lower limb joint kinematics are inherently application dependent. Sensor restrictions are generally compensated with biomechanically inspired assumptions and prior information. Awareness of the possible adaptations in the IMU-based kinematic estimates by incorporating such prior information and assumptions is necessary, before drawing clinical decisions. Future research should focus on alternative validation methods, subject-specific IMU-based biomechanical joint models and disturbed movement patterns in real-world settings.
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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.