Optimizing sensory stimulation in humans after spinal cord injury

White, Jason Martin

Title:

Optimizing sensory stimulation in humans after spinal cord injury

dc.contributor.advisor	DeWeerth, Stephen P.
dc.contributor.author	White, Jason Martin
dc.contributor.committeeMember	Tansey, Keith E.
dc.contributor.committeeMember	Ting, Lena
dc.contributor.committeeMember	Nichols, T. Richard
dc.contributor.committeeMember	Prilutsky, Boris I.
dc.contributor.committeeMember	Egerstedt, Magnus
dc.contributor.department	Biomedical Engineering (Joint GT/Emory Department)
dc.date.accessioned	2017-01-11T14:02:04Z
dc.date.available	2017-01-11T14:02:04Z
dc.date.created	2016-12
dc.date.issued	2016-08-31
dc.date.submitted	December 2016
dc.date.updated	2017-01-11T14:02:04Z
dc.description.abstract	Sensory stimulation has shown promise in improving human walking after spinal cord injury (SCI). Previous studies have demonstrated some improvement with open-loop, non-individualized sensory stimulation, but after SCI, there are many unique, individual changes in sensorimotor processing. These changes make a priori identification of the best sensory stimulation pattern difficult for any given individual. Real-time optimization provides a solution to this individuality problem, through optimizing sensory stimulation parameters for a given subject in on-line (in real-time). In this research, I developed an approach to optimize sensory stimulation to maximally assist human walking after incomplete SCI. To do so, I had to develop and validate a novel optimization algorithm for globally-optimizing noisy, time-variant, black-box systems, while maximizing the information gained from each test (experiment). I optimized sensory stimulation across a range of SCI subjects, across multiple sensory stimulation sites, and with different stimulation parameterizations. In all subjects and stimulation sites, the optimal stimulation protocol produced better walking (i.e. less external force assistance was required) than three alternative stimulation protocols: an industry-standard stimulation protocol, a no-stimulation protocol, and a random-stimulation protocol. The optimization approach minimized the total force required from an assistive orthosis, and post-hoc analysis of the optimization sessions produced a better understanding of how stimulation parameters affected specific gait features (e.g. hip forces during swing). Transcutaneous spinal cord stimulation (TSCS) frequency had divergent effects on the stance and swing phases – high frequencies tended to assist with swing, but low frequencies tended to assist with stance. For the two peripheral nerve stimulation sites (posterior tibial and common peroneal nerves), the optimal gait-phase for stimulation was generally after mid-stance and before early swing. There was some variability within this time-range depending on the specific feature under study. Experimental history (i.e. time spent walking/time spent being stimulated) proved to be as important a predictor as any of the stimulation parameters.
dc.description.degree	Ph.D.
dc.format.mimetype	application/pdf
dc.identifier.uri	http://hdl.handle.net/1853/56259
dc.language.iso	en_US
dc.publisher	Georgia Institute of Technology
dc.subject	Optimization
dc.subject	Spinal cord injury
dc.subject	Sensory stimulation
dc.title	Optimizing sensory stimulation in humans after spinal cord injury
dc.type	Text
dc.type.genre	Dissertation
dspace.entity.type	Publication
local.contributor.advisor	DeWeerth, Stephen P.
local.contributor.corporatename	Wallace H. Coulter Department of Biomedical Engineering
local.contributor.corporatename	College of Engineering
relation.isAdvisorOfPublication	6b8c24a1-7328-4161-8715-b26e0231ae78
relation.isOrgUnitOfPublication	da59be3c-3d0a-41da-91b9-ebe2ecc83b66
relation.isOrgUnitOfPublication	7c022d60-21d5-497c-b552-95e489a06569
thesis.degree.level	Doctoral