Paper Info
Title
Estimating Sit-to-Stand Dynamics using a Single Depth Camera.
Abstract
Kinematic and dynamic analysis of human motion allows for an assessment of a patient's functional ability, providing insight beyond static imaging or subjective surveys. While advanced modelling methods and sensor systems are utilised by biomechanics laboratories, there remains a need for a clinically deployable system a to analyse patient motion in a fast, affordable, and accurate manner. This paper presents and validates a method for performing inverse dynamics with a single depth camera, including estimates of body momenta and joint torques. An allometrically scaled, sagittal plane dynamic model is used to estimate the joint torques at the ankles, knees, hips, and low back, as well as the torso momenta, and shear and normal load at the L5-S1 disc. These dynamic metrics are applied to the sit-to-stand motion and validated against a gold-standard biomechanical system consisting of full body active motion-capture and force sensing systems. The metrics obtained from the proposed method were found have excellent concordance with peak metrics that are consistent with prior biomechanical studies. This suggests the feasibility of using this system for rapid clinical assessment, with applications in diagnostics, longitudinal tracking, and quantifying patient recovery.
Year
DOI
Venue
2019
10.1109/JBHI.2019.2897245
IEEE journal of biomedical and health informatics
Keywords
Field
DocType
Dynamics,Biomechanics,Hip,Kinematics,Cameras,Informatics,Biological system modeling
Sit to stand,Computer vision,Torso,Torque,Kinematics,Computer science,Artificial intelligence,Motion analysis,Biomechanics,Sagittal plane
Journal
Volume
Issue
ISSN
23
6
2168-2208
Citations 
PageRank 
References 
0
0.34
0
Authors
5
Name
Order
Citations
PageRank
Robert Peter Matthew146.51
Sarah Seko212.03
Jeannie Bailey300.68
Ruzena Bajcsy421.71
Jeffrey C. Lotz512.03