ArticleSensors (Basel, Switzerland)2015
Pose estimation with a Kinect for ergonomic studies: evaluation of the accuracy using a virtual mannequin.
Article in Sensors (Basel, Switzerland), 2015. 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.
- A Simple Method to Optimally Select Upper-Limb Joint Angle Trajectories from Two Kinect Sensors during the Twisting Task for Posture Analysis.Sensors (Basel, Switzerland) · 2022Article
- Accuracy Assessment of Joint Angles Estimated from 2D and 3D Camera Measurements.Sensors (Basel, Switzerland) · 2022Article
- Implementation of Kinetic and Kinematic Variables in Ergonomic Risk Assessment Using Motion Capture Simulation: A Review.International journal of environmental research and public health · 2021Review
- Detection of Postural Control in Young and Elderly Adults Using Deep and Machine Learning Methods with Joint-Node Plots.Sensors (Basel, Switzerland) · 2021Article
- Musculoskeletal Risks: RULA Bibliometric Review.International journal of environmental research and public health · 2020Review
- DeepMoCap: Deep Optical Motion Capture Using Multiple Depth Sensors and Retro-Reflectors.Sensors (Basel, Switzerland) · 2019Article
- Efficient Depth Enhancement Using a Combination of Color and Depth Information.Sensors (Basel, Switzerland) · 2017Article
- Filtered pose graph for efficient kinect pose reconstruction.Multimedia tools and applications · 2017Article
- A New Multi-Sensor Fusion Scheme to Improve the Accuracy of Knee Flexion Kinematics for Functional Rehabilitation Movements.Sensors (Basel, Switzerland) · 2016Article
- Articulated Non-Rigid Point Set Registration for Human Pose Estimation from 3D Sensors.Sensors (Basel, Switzerland) · 2015Article
- Tracking systems for virtual rehabilitation: objective performance vs. subjective experience. A practical scenario.Sensors (Basel, Switzerland) · 2015Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Analyzing human poses with a Kinect is a promising method to evaluate potentials risks of musculoskeletal disorders at workstations. In ecological situations, complex 3D poses and constraints imposed by the environment make it difficult to obtain reliable kinematic information. Thus, being able to predict the potential accuracy of the measurement for such complex 3D poses and sensor placements is challenging in classical experimental setups. To tackle this problem, we propose a new evaluation method based on a virtual mannequin. In this study, we apply this method to the evaluation of joint positions (shoulder, elbow, and wrist), joint angles (shoulder and elbow), and the corresponding RULA (a popular ergonomics assessment grid) upper-limb score for a large set of poses and sensor placements. Thanks to this evaluation method, more than 500,000 configurations have been automatically tested, which would be almost impossible to evaluate with classical protocols. The results show that the kinematic information obtained by the Kinect software is generally accurate enough to fill in ergonomic assessment grids. However inaccuracy strongly increases for some specific poses and sensor positions. Using this evaluation method enabled us to report configurations that could lead to these high inaccuracies. As a supplementary material, we provide a software tool to help designers to evaluate the expected accuracy of this sensor for a set of upper-limb configurations. Results obtained with the virtual mannequin are in accordance with those obtained from a real subject for a limited set of poses and sensor placements.
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