Paper Info
Title
Kinematic and Kinetic Validation of an Improved Depth Camera Motion Assessment System Using Rigid Bodies.
Abstract
The study of joint kinematics and dynamics has broad clinical applications including the identification of pathological motions or compensation strategies and the analysis of dynamic stability. High-end motion capture systems, however, are expensive and require dedicated camera spaces with lengthy set-up and data processing commitments. Depth cameras, such as the Microsoft Kinect, provide an inexpensive, marker-free alternative at the sacrifice of joint-position accuracy. In this work, we present a fast framework for adding biomechanical constraints to the joint estimates provided by a depth camera system. We also present a new model for the lower lumbar joint angle. We validate key joint position, angle, and velocity measurements against a gold standard active motion-capture system on ten healthy subjects performing sit-to-stand (STS). Our method showed significant improvement in Mean Absolute Error and Intraclass Correlation Coefficients for the recovered joint angles and position-based metrics. These improvements suggest that depth cameras can provide an accurate and clinically viable method of rapidly assessing the kinematics and kinetics of the STS action, providing data for further analysis using biomechanical or machine learning methods.
Year
DOI
Venue
2019
10.1109/JBHI.2018.2872834
IEEE journal of biomedical and health informatics
Keywords
Field
DocType
Cameras,Kinematics,Biological system modeling,Biomechanics,Informatics,Kinetic theory,Task analysis
Sit to stand,Motion capture,Computer vision,Data processing,Kinematics,Lumbar joint,Computer science,Artificial intelligence,Biomechanics,Intraclass correlation,Kinetic energy
Journal
Volume
Issue
ISSN
23
4
2168-2208
Citations 
PageRank 
References 
1
0.34
0
Authors
4
Name
Order
Citations
PageRank
Robert Peter Matthew146.51
Sarah Seko212.03
Ruzena Bajcsy321.71
Jeffrey C. Lotz412.03