ReviewSensors (Basel, Switzerland)2020
Motion Capture Technology in Industrial Applications: A Systematic Review.
Review 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 49 papers, 4 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
49 citing papers in PubMed, 4 syntheses or guidelines pooled it, 287 citations in OpenAlex.
- Intention Prediction for Active Upper-Limb Exoskeletons in Industrial Applications: A Systematic Literature Review.Sensors (Basel, Switzerland) · 2025Pooled it
- Intraoperative Angle Measurement of Anatomical Structures: A Systematic Review.Sensors (Basel, Switzerland) · 2024Pooled it
- Transparency as a Means to Analyse the Impact of Inertial Sensors on Users during the Occupational Ergonomic Assessment: A Systematic Review.Sensors (Basel, Switzerland) · 2024Pooled it
- Sensing Technology Applications in the Mining Industry-A Systematic Review.International journal of environmental research and public health · 2022Pooled it
- The case study of prosthetic foot alignment on amputee gait kinematics using IMU-based motion capture system.International biomechanics · 2026Article
- Synchrony Vision: An RGB-D Sensor-Based System for Real-Time Monitoring and Event-Level Analysis of Interpersonal Motion Synchrony.Sensors (Basel, Switzerland) · 2026Article
- Motion capture dataset of 137 post-operative total hip replacement patients performing activities of daily living.Scientific data · 2026Article
- Gait assessment using a 2D video-based pose estimation app in comparison to a markerless motion capture system in subjects with osteoarthritis of the knee - a pilot study.Frontiers in bioengineering and biotechnology · 2026Article
- AI-Driven Motion Capture Data Recovery: A Comprehensive Review and Future Outlook.Sensors (Basel, Switzerland) · 2025Review
- Motion Capture Technologies for Athletic Performance Enhancement and Injury Risk Assessment: A Review for Multi-Sport Organizations.Sensors (Basel, Switzerland) · 2025Review
- Validated low-cost standardized VICON configuration as a practical approach to estimating the minimal accuracy of a specific setup.Scientific reports · 2025Article
- GCN-Transformer: Graph Convolutional Network and Transformer for Multi-Person Pose Forecasting Using Sensor-Based Motion Data.Sensors (Basel, Switzerland) · 2025Article
- A multi-method framework for establishing an angular acceleration reference in sensor calibration and uncertainty quantification.Communications engineering · 2025Article
- Assessment of Pelvic Motion During Single-Leg Weight-Bearing Tasks Using Smartphone Sensors: Validity Study.JMIR rehabilitation and assistive technologies · 2025Article
- Smile analysis in dentistry and orthodontics - a review.Journal of the Royal Society of New Zealand · 2025Review
- Gait assessment using a 2D video-based motion analysis app in healthy subjects and subjects with lower limb amputation - A pilot study.PloS one · 2025Article
- A Real-Time Approach for Assessing Rodent Engagement in a Nose-Poking Go/No-Go Behavioral Task Using ArUco Markers.Bio-protocol · 2024Article
- Localization and recognition of human action in 3D using transformers.Communications engineering · 2024Article
- Machine Learning Based Abnormal Gait Classification with IMU Considering Joint Impairment.Sensors (Basel, Switzerland) · 2024Article
- Embedding textile capacitive sensing into smart wearables as a versatile solution for human motion capturing.Scientific reports · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
The rapid technological advancements of Industry 4.0 have opened up new vectors for novel industrial processes that require advanced sensing solutions for their realization. Motion capture (MoCap) sensors, such as visual cameras and inertial measurement units (IMUs), are frequently adopted in industrial settings to support solutions in robotics, additive manufacturing, teleworking and human safety. This review synthesizes and evaluates studies investigating the use of MoCap technologies in industry-related research. A search was performed in the Embase, Scopus, Web of Science and Google Scholar. Only studies in English, from 2015 onwards, on primary and secondary industrial applications were considered. The quality of the articles was appraised with the AXIS tool. Studies were categorized based on type of used sensors, beneficiary industry sector, and type of application. Study characteristics, key methods and findings were also summarized. In total, 1682 records were identified, and 59 were included in this review. Twenty-one and 38 studies were assessed as being prone to medium and low risks of bias, respectively. Camera-based sensors and IMUs were used in 40% and 70% of the studies, respectively. Construction (30.5%), robotics (15.3%) and automotive (10.2%) were the most researched industry sectors, whilst health and safety (64.4%) and the improvement of industrial processes or products (17%) were the most targeted applications. Inertial sensors were the first choice for industrial MoCap applications. Camera-based MoCap systems performed better in robotic applications, but camera obstructions caused by workers and machinery was the most challenging issue. Advancements in machine learning algorithms have been shown to increase the capabilities of MoCap systems in applications such as activity and fatigue detection as well as tool condition monitoring and object recognition.
Indexed as
Identifiers
What OpenQuestion holds
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.