Physically Consistent Whole-Body Kinematics Assessment Based on an RGB-D Sensor. Application to Simple Rehabilitation Exercises

This work proposes to improve the accuracy of joint angle estimates obtained from an RGB-D sensor. It is based on a constrained extended Kalman Filter that tracks inputted measured joint centers. Since the proposed approach uses a biomechanical model, it allows physically consistent constrained join...

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Veröffentlicht in:Sensors (Basel, Switzerland) Jg. 20; H. 10; S. 2848
Hauptverfasser: Colombel, Jessica, Bonnet, Vincent, Daney, David, Dumas, Raphael, Seilles, Antoine, Charpillet, François
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Switzerland MDPI 17.05.2020
MDPI AG
Schlagworte:
Algorithms
Biomechanical Phenomena
Biomechanics
Engineering Sciences
Exercise Therapy
extended Kalman filter and rehabilitation
Healthy Volunteers
Humans
markerless human motion analysis
Mechanics
Photogrammetry
Rehabilitation
markerless human motion analysis
extended Kalman filter and rehabilitation
Markerless human motion analysis
Extended Kalman filter and rehabilitation
ISSN:1424-8220, 1424-8220
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Zusammenfassung:This work proposes to improve the accuracy of joint angle estimates obtained from an RGB-D sensor. It is based on a constrained extended Kalman Filter that tracks inputted measured joint centers. Since the proposed approach uses a biomechanical model, it allows physically consistent constrained joint angles and constant segment lengths to be obtained. A practical method that is not sensor-specific for the optimal tuning of the extended Kalman filter covariance matrices is provided. It uses reference data obtained from a stereophotogrammetric system but it has to be tuned only once since it is task-specific only. The improvement of the optimal tuning over classical methods in setting the covariance matrices is shown with a statistical parametric mapping analysis. The proposed approach was tested with six healthy subjects who performed four rehabilitation tasks. The accuracy of joint angle estimates was assessed with a reference stereophotogrammetric system. Even if some joint angles, such as the internal/external rotations, were not well estimated, the proposed optimized algorithm reached a satisfactory average root mean square difference of 9.7 ∘ and a correlation coefficient of 0.8 for all joints. Our results show that an affordable RGB-D sensor can be used for simple in-home rehabilitation when using a constrained biomechanical model.
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ISSN:1424-8220
1424-8220
DOI:10.3390/s20102848