ArticleSensors (Basel, Switzerland)2020
Marker-Based Movement Analysis of Human Body Parts in Therapeutic Procedure.
Article 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 11 papers.
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Who cites it
11 citing papers in PubMed.
- Three-dimensional trunk adjustment based on surface markers in treating mild to moderate adolescent idiopathic scoliosis.Frontiers in pediatrics · 2026Article
- A Holistic Approach Towards Evaluating Upper Limb Function in Children with Unilateral Cerebral Palsy: A Narrative Review of Clinical Tools and Promising Technologies for Comprehensive Assessment.Journal of clinical medicine · 2025Review
- Validation of Smartphones in Arbitrary Positions Against Force Plate Standard for Balance Assessment.Sensors (Basel, Switzerland) · 2025Article
- Text to Blind Motion.Advances in neural information processing systems · 2024Article
- Feasibility of 3D Body Tracking from Monocular 2D Video Feeds in Musculoskeletal Telerehabilitation.Sensors (Basel, Switzerland) · 2023Article
- Azure Kinect performance evaluation for human motion and upper limb biomechanical analysis.Heliyon · 2023Article
- Changes in the Complexity of Limb Movements during the First Year of Life across Different Tasks.Entropy (Basel, Switzerland) · 2022Article
- Design, Development, and Testing of an Intelligent Wearable Robotic Exoskeleton Prototype for Upper Limb Rehabilitation.Sensors (Basel, Switzerland) · 2021Article
- Estimation of Motion and Respiratory Characteristics during the Meditation Practice Based on Video Analysis.Sensors (Basel, Switzerland) · 2021Article
- Syntactic model-based human body 3D reconstruction and event classification via association based features mining and deep learning.PeerJ. Computer science · 2021Article
- Automatic Recognition of Human Interaction via Hybrid Descriptors and Maximum Entropy Markov Model Using Depth Sensors.Entropy (Basel, Switzerland) · 2020Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Movement analysis of human body parts is momentous in several applications including clinical diagnosis and rehabilitation programs. The objective of this research is to present a low-cost 3D visual tracking system to analyze the movement of various body parts during therapeutic procedures. Specifically, a marker based motion tracking system is proposed in this paper to capture the movement information in home-based rehabilitation. Different color markers are attached to the desired joints' locations and they are detected and tracked in the video to encode their motion information. The availability of this motion information of different body parts during the therapy can be exploited to achieve more accurate results with better clinical insight, which in turn can help improve the therapeutic decision making. The proposed framework is an automated and inexpensive motion tracking system with execution speed close to real time. The performance of the proposed method is evaluated on a dataset of 10 patients using two challenging matrices that measure the average accuracy by estimating the joints' locations and rotations. The experimental evaluation and its comparison with the existing state-of-the-art techniques reveals the efficiency of the proposed method.
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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.