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Neuromuscular Reflex Control for Prostheses and Exoskeletons

Hnat, Sandra K
http://rave.ohiolink.edu/etdc/view?acc_num=csu1525883440762107

Abstract Details

2018, Doctor of Engineering, Cleveland State University, Washkewicz College of Engineering.
Recent powered lower-limb prosthetic and orthotic (P/O) devices aim to restore legged mobility for persons with an amputation or spinal cord injury. Though various control strategies have been proposed for these devices, specifically finite-state impedance controllers, natural gait mechanics are not usually achieved. The goal of this project was to invent a biologically-inspired controller for powered P/O devices. We hypothesize that a more muscle-like actuation system, including spinal reflexes and vestibular feedback, can achieve able-bodied walking and also respond to outside perturbations. The outputs of the Virtual Muscle Reflex (VMR) controller are joint torque commands, sent to the electric motors of a P/O device. We identified the controller parameters through optimizations using human experimental data of perturbed walking, in which we minimized the error between the torque produced by our controller and the standard torque trajectories observed in the able-bodied experiments. In simulations, we then compare the VMR controller to a four-phase impedance controller. For both controllers the coefficient of determination R^2 and root-mean-square (RMS) error were calculated as a function of the gait cycle. When simulating the hip, knee, and ankle joints, the RMS error and R^2 across all joints and all trials is 15.65 Nm and 0.28 for the impedance controller, respectively, and for the VMR controller, these values are 15.15 Nm and 0.29, respectively. With similar performance, it was concluded that the VMR controller can reproduce characteristics of human walking in response to perturbations as effectively as an impedance controller. We then implemented the VMR controller on the Parker Hannifin powered exoskeleton and performed standard isokinetic and isometric knee rehabilitation exercises to observe the behavior of the virtual muscle model. In the isometric results, RMS error between the measured and commanded extension and flexion torques are 3.28 Nm and 1.25 Nm, respectively. In the isokinetic trials, we receive RMS error between the measured and commanded extension and flexion torques of 0.73 Nm and 0.24 Nm. Since the onboard virtual muscles demonstrate similar muscle force-length and force-velocity relationships observed in humans, we conclude the model is capable of the same stabilizing capabilities as observed in an impedance controller.
Antonie van den Bogert (Advisor)
Hanz Richter (Committee Member)
Michael Hammonds (Committee Member)
Jason Halloran (Committee Member)
Eric Schearer (Committee Member)
225 p.
Biomechanics; Engineering; Mechanical Engineering
reflex control, muscle control, prosthetics, exoskeletons

Recommended Citations

Citations

  • Hnat, S. K. (2018). Neuromuscular Reflex Control for Prostheses and Exoskeletons [Doctoral dissertation, Cleveland State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=csu1525883440762107

    APA Style (7th edition)

  • Hnat, Sandra. Neuromuscular Reflex Control for Prostheses and Exoskeletons. 2018. Cleveland State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=csu1525883440762107.

    MLA Style (8th edition)

  • Hnat, Sandra. "Neuromuscular Reflex Control for Prostheses and Exoskeletons." Doctoral dissertation, Cleveland State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=csu1525883440762107

    Chicago Manual of Style (17th edition)

csu1525883440762107
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© 2018, all rights reserved.
This open access ETD is published by Cleveland State University and OhioLINK.