SynthesisJMIR aging2024
Markerless Motion Capture to Quantify Functional Performance in Neurodegeneration: Systematic Review.
Synthesis in JMIR aging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
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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.
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Who cites it
13 citing papers in PubMed.
- Validation of a Deep Learning-Based Markerless Video System for Gait Speed Assessment During the 10-Meter Walk Test in Outdoor Clinical Settings.Journal of functional morphology and kinesiology · 2026Article
- Review
- Passive sensing of gait and medication-related fluctuations in Parkinson's disease.Journal of neuroengineering and rehabilitation · 2026Article
- Development, Reliability, and Validity Assessment of a Portable 3D Camera-Based System for Quantifying Postural Sway and Balance.Sensors (Basel, Switzerland) · 2026Article
- Walking as a Window to the Brain: Redefining Gait in Neurology.Medical sciences (Basel, Switzerland) · 2026Review
- Development of novel biomechanical outcomes using motion capture to characterize hand function in multiple sclerosis.Multiple sclerosis and related disorders · 2026Article
- Spatio-temporal graph autoencoder for automated evaluation of human actions in 3D in immersive VR-based training for archaeologists.Scientific reports · 2026Article
- Smartphone-Based Markerless Motion Capture for Spatiotemporal Gait Assessment: Applied Within-Session Reliability and Comparability of OpenCap Versus OptoGait.Sensors (Basel, Switzerland) · 2026Article
- Validation of a markerless motion capture app for automated scoring of sit-to-stand, timed up and go, and short physical performance battery tests in adults with chronic disease.PLOS digital health · 2026Article
- Indicator analysis of the footwork in the world's top badminton athletes based on markerless motion measurement.Frontiers in sports and active living · 2026Article
- Sensors in Multiple Sclerosis.Current neurology and neuroscience reports · 2025Review
- Markerless Motion Capture Parameters Associated with Fall Risk or Frailty: A Scoping Review.Sensors (Basel, Switzerland) · 2025Article
- Automated Remote Detection of Falls Using Direct Reconstruction of Optical Flow Principal Motion Parameters.Sensors (Basel, Switzerland) · 2025Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMarkerless motion capture (MMC) uses video cameras or depth sensors for full body tracking and presents a promising approach for objectively and unobtrusively monitoring functional performance within community settings, to aid clinical decision-making in neurodegenerative diseases such as dementia.
objectiveThe primary objective of this systematic review was to investigate the application of MMC using full-body tracking, to quantify functional performance in people with dementia, mild cognitive impairment, and Parkinson disease.
methodsA systematic search of the Embase, MEDLINE, CINAHL, and Scopus databases was conducted between November 2022 and February 2023, which yielded a total of 1595 results. The inclusion criteria were MMC and full-body tracking. A total of 157 studies were included for full-text screening, out of which 26 eligible studies that met the selection criteria were included in the review. .
resultsPrimarily, the selected studies focused on gait analysis (n=24), while other functional tasks, such as sit to stand (n=5) and stepping in place (n=1), were also explored. However, activities of daily living were not evaluated in any of the included studies. MMC models varied across the studies, encompassing depth cameras (n=18) versus standard video cameras (n=5) or mobile phone cameras (n=2) with postprocessing using deep learning models. However, only 6 studies conducted rigorous comparisons with established gold-standard motion capture models.
conclusionsDespite its potential as an effective tool for analyzing movement and posture in individuals with dementia, mild cognitive impairment, and Parkinson disease, further research is required to establish the clinical usefulness of MMC in quantifying mobility and functional performance in the real world.
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