ArticleSensors (Basel, Switzerland)2024
Development of a Low-Cost Markerless Optical Motion Capture System for Gait Analysis and Anthropometric Parameter Quantification.
Article in Sensors (Basel, Switzerland), 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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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
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Who cites it
8 citing papers in PubMed.
- Evaluation Protocols and Validation for Cameras in Indoor Healthcare Monitoring.Sensors (Basel, Switzerland) · 2026Article
- Enhancing Work Efficiency and Safety Culture in the Food Industry Using Behavioral Patterns: A Video-Based Case Study from Poland.Foods (Basel, Switzerland) · 2026Article
- Visual-Inertial Fusion Framework for Isolating Seated Human-Body Vibration in Dynamic Vehicular Environments.Sensors (Basel, Switzerland) · 2026Article
- Impact of Perceived Dorsiflexion and Plantarflexion in the Squat and Countermovement Jumps.Muscles (Basel, Switzerland) · 2026Article
- Challenges in Combining EMG, Joint Moments, and GRF from Marker-Less Video-Based Motion Capture Systems.Bioengineering (Basel, Switzerland) · 2025Review
- Reliability and validity of a video-based markerless motion capture system in young healthy subjects.Heliyon · 2025Article
- Evaluating the Reliability and Consistency of Treadmill Gait Analysis Using an RGB-D Camera: Effects of Assistance and No Assistance.Sensors (Basel, Switzerland) · 2025Article
- Reliability assessment of markerless technologies in biomechanical motion analysis: a performance comparison.Frontiers in sports and active living · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Technological advancements have expanded the range of methods for capturing human body motion, including solutions involving inertial sensors (IMUs) and optical alternatives. However, the rising complexity and costs associated with commercial solutions have prompted the exploration of more cost-effective alternatives. This paper presents a markerless optical motion capture system using a RealSense depth camera and intelligent computer vision algorithms. It facilitates precise posture assessment, the real-time calculation of joint angles, and acquisition of subject-specific anthropometric data for gait analysis. The proposed system stands out for its simplicity and affordability in comparison to complex commercial solutions. The gathered data are stored in comma-separated value (CSV) files, simplifying subsequent analysis and data mining. Preliminary tests, conducted in controlled laboratory environments and employing a commercial MEMS-IMU system as a reference, revealed a maximum relative error of 7.6% in anthropometric measurements, with a maximum absolute error of 4.67 cm at average height. Stride length measurements showed a maximum relative error of 11.2%. Static joint angle tests had a maximum average error of 10.2%, while dynamic joint angle tests showed a maximum average error of 9.06%. The proposed optical system offers sufficient accuracy for potential application in areas such as rehabilitation, sports analysis, and entertainment.
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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.