ArticleBioengineering (Basel, Switzerland)2024
Improving Gait Analysis Techniques with Markerless Pose Estimation Based on Smartphone Location.
Article in Bioengineering (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 14 citations in OpenAlex.
- Article
- Article
- Waveform-Level Validation of Continuous Shank-to-Vertical Angle Measurement Using a Wearable Posture Sensor with Independent Video-Based Gait Event Detection.Sensors (Basel, Switzerland) · 2026Article
- Parkinson's disease focused multimodal wearable vision based gait monitoring system with real time feedback to support mobility and caregiver well-being.Discover mental health · 2026Article
- Proprioceptive-augmented virtual reality influences the kinematic properties of movement imitation.Journal of neuroengineering and rehabilitation · 2026Article
- A Physics-Data Hybrid Framework Using Uncalibrated Consumer CMOS Vision: Pilot Study on Monocular Automatic TUG Assessment Towards Early Parkinson's Disease Risk Screening.Micromachines · 2026Article
- Evaluation of Smartphone Camera Positioning on Artificial Intelligence Pose Estimation Accuracy for Exercise Detection: Observational Study.JMIR mHealth and uHealth · 2026Observational
- Feasibility of Smartphone-Based Markerless Motion Capture for Quantitative Gait Assessment in Pediatric Guillain-Barré Syndrome: A Two-Case Proof-of-Concept Study.Bioengineering (Basel, Switzerland) · 2025Article
- Multimodal Motion Capture Toolbox for Enhanced Analysis of Intersegmental Coordination in Children with Cerebral Palsy and Typically Developing.Journal of visualized experiments : JoVE · 2025Article
- Markerless Motion Capture Parameters Associated with Fall Risk or Frailty: A Scoping Review.Sensors (Basel, Switzerland) · 2025Article
- Comparison of lower limb kinematic and kinetic estimation during athlete jumping between markerless and marker-based motion capture systems.Scientific reports · 2025Article
- Commercial vision sensors and AI-based pose estimation frameworks for markerless motion analysis in sports and exercises: a mini review.Frontiers in physiology · 2025Review
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Marker-based 3D motion capture systems, widely used for gait analysis, are accurate but have disadvantages such as cost and accessibility. Whereas markerless pose estimation has emerged as a convenient and cost-effective alternative for gait analysis, challenges remain in achieving optimal accuracy. Given the limited research on the effects of camera location and orientation on data collection accuracy, this study investigates how camera placement affects gait assessment accuracy utilizing five smartphones. This study aimed to explore the differences in data collection accuracy between marker-based systems and pose estimation, as well as to assess the impact of camera location and orientation on accuracy in pose estimation. The results showed that the differences in joint angles between pose estimation and marker-based systems are below 5°, an acceptable level for gait analysis, with a strong correlation between the two datasets supporting the effectiveness of pose estimation in gait analysis. In addition, hip and knee angles were accurately measured at the front diagonal of the subject and ankle angle at the lateral side. This research highlights the significance of careful camera placement for reliable gait analysis using pose estimation, serving as a concise reference to guide future efforts in enhancing the quantitative accuracy of gait analysis.
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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.