Biomechanical Models and Robotic Systems for Human Motion Assessment
Sarah Seko
EECS Department, University of California, Berkeley
Technical Report No. UCB/EECS-2021-22
May 1, 2021
http://www2.eecs.berkeley.edu/Pubs/TechRpts/2021/EECS-2021-22.pdf
Over the past several decades, there have been advances in the development of complex robotic devices for daily assistance or rehabilitation. The use of such devices, however, has largely remained limited to a research setting due to the prohibitive cost and required operational engineering expertise. Likewise, dedicated biomechanics facilities perform quantitative motion analysis, contrasting the qualitative and static imaging methods which are standard in clinical care. The aim of this dissertation is to develop and validate affordable methods and devices for assessing and assisting human motion.
We first present a framework for improved estimation of whole-body human kinematics with data from a single depth-camera. The algorithm incorporates biomechanical and dynamic constraints for near-real time analysis of human motion. The approach is validated against data from a ground-truth motion capture system on sit-to-stand (STS), an activity of daily living which requires significant torque generation and coordinated movement of multiple joints. We additionally present two methods for modeling the torso: a generalized relationship for the lower-lumbar angle and an optimization-based method for estimating a subject-specific model. Building on these modeling methods, we introduce a passive elastic knee orthotic device which provides bilateral knee assistance during STS. The device design and analysis integrate models of the human and device dynamics. Preliminary human subjects tests demonstrate a decrease in the human knee torque as well as positive changes in whole-body biomechanics. Finally, we introduce an affordable planar robotic manipulandum for upper limb assessment and assistance. The mechanical, electrical, and control architectures are presented, along with preliminary human subjects tests of reaching and elliptical trajectories with force field assistance under an admittance controller. A protocol for the assessment of strength and coordination is introduced and integrated with a biomechanical model of the arm. With a total material cost of less than $800, this device provides an accessible platform for clinical robotic assessment and rehabilitation.
Advisors: Ruzena Bajcsy
BibTeX citation:
@phdthesis{Seko:EECS-2021-22,
Author= {Seko, Sarah},
Title= {Biomechanical Models and Robotic Systems for Human Motion Assessment},
School= {EECS Department, University of California, Berkeley},
Year= {2021},
Month= {May},
Url= {http://www2.eecs.berkeley.edu/Pubs/TechRpts/2021/EECS-2021-22.html},
Number= {UCB/EECS-2021-22},
Abstract= {Over the past several decades, there have been advances in the development of complex robotic devices for daily assistance or rehabilitation. The use of such devices, however, has largely remained limited to a research setting due to the prohibitive cost and required operational engineering expertise. Likewise, dedicated biomechanics facilities perform quantitative motion analysis, contrasting the qualitative and static imaging methods which are standard in clinical care. The aim of this dissertation is to develop and validate affordable methods and devices for assessing and assisting human motion.
We first present a framework for improved estimation of whole-body human kinematics with data from a single depth-camera. The algorithm incorporates biomechanical and dynamic constraints for near-real time analysis of human motion. The approach is validated against data from a ground-truth motion capture system on sit-to-stand (STS), an activity of daily living which requires significant torque generation and coordinated movement of multiple joints. We additionally present two methods for modeling the torso: a generalized relationship for the lower-lumbar angle and an optimization-based method for estimating a subject-specific model. Building on these modeling methods, we introduce a passive elastic knee orthotic device which provides bilateral knee assistance during STS. The device design and analysis integrate models of the human and device dynamics. Preliminary human subjects tests demonstrate a decrease in the human knee torque as well as positive changes in whole-body biomechanics. Finally, we introduce an affordable planar robotic manipulandum for upper limb assessment and assistance. The mechanical, electrical, and control architectures are presented, along with preliminary human subjects tests of reaching and elliptical trajectories with force field assistance under an admittance controller. A protocol for the assessment of strength and coordination is introduced and integrated with a biomechanical model of the arm. With a total material cost of less than $800, this device provides an accessible platform for clinical robotic assessment and rehabilitation.},
}
EndNote citation:
%0 Thesis %A Seko, Sarah %T Biomechanical Models and Robotic Systems for Human Motion Assessment %I EECS Department, University of California, Berkeley %D 2021 %8 May 1 %@ UCB/EECS-2021-22 %U http://www2.eecs.berkeley.edu/Pubs/TechRpts/2021/EECS-2021-22.html %F Seko:EECS-2021-22