Symptom-free in zero-g? Novel techniques for rapid assessment of vestibulo-ocular function and their use in predicting performance from baseline metrics
| dc.contributor.advisor | Zee, David S. | |
| dc.contributor.committeeMember | Shelhamer, Mark J. | |
| dc.contributor.committeeMember | Young, Eric D. | |
| dc.contributor.committeeMember | Schubert, Michael C. | |
| dc.contributor.committeeMember | Bloomberg, Jacob | |
| dc.creator | Beaton, Kara Huffman | |
| dc.date.accessioned | 2018-10-03T03:04:41Z | |
| dc.date.available | 2018-10-03T03:04:41Z | |
| dc.date.created | 2014-05 | |
| dc.date.issued | 2014-03-27 | |
| dc.date.submitted | May 2014 | |
| dc.date.updated | 2018-10-03T03:04:41Z | |
| dc.description.abstract | Spaceflight elicits adaptive changes in neurovestibular signaling to accommodate exposure to novel gravity levels. With the prospect of longer-duration missions to Mars and beyond, NASA is currently faced with two immediate needs, which form the founda-tion of this dissertation: (1) portable technologies to evaluate functional decrements in sensorimotor performance that can be quickly self-administered, and (2) countermeasures that can pre-adapt astronauts prior to spaceflight, accelerate adaptation inflight, or fore-cast performance (e.g., adaptive capabilities or space motion sickness susceptibility) from preflight metrics alone. In this dissertation, we focus specifically on the design, devel-opment, and implementation of three innovative approaches to quantify the vestibular control of eye movements using minimal hardware, and we use these techniques to pre-dict adaptive performance from baseline measures. Vertical and Torsional Alignment Nulling and Vestibulo-Ocular Nulling (VON) were developed to evaluate binocular positioning misalignments and the vestibulo-ocular reflex (VOR), respectively. These tests are embedded in a hand-held device, which in-corporates a tablet computer, small wireless motion sensors, and a pair of specialized eyeglasses, and employs various mobile-apps developed in-house. Through a series of experiments performed in the laboratory and in parabolic-flight, we validated these new assessment tests and explored gravity-level dependencies in vestibulo-ocular function. We found that ocular misalignments are gravity-dependent and developed a bilateral con-trol systems model to describe this dependency. Additionally, variability in baseline tor-sional misalignment strongly correlates with motion-sickness susceptibility in altered gravity environments. Our VON test provides a rapid measure of dynamic gaze stability that is more consistent than traditional measures of VOR gain. VON results vary system-atically with gravity levels, providing evidence for an otolith-modulating component of the angular VOR. Finally, the strength of baseline inter-trial correlations forecast adap-tive capacity in the VOR. The portable technologies developed in this dissertation have applications beyond spaceflight operations, including bedside clinical testing, remote field-testing, or any ap-plications limited by time constraints, resources, technical personnel, or clinical expertise. The ability to forecast performance from baseline metrics alone, without exposure to an adaptive stimulus, has important implications for the design of individualized interven-tions, such as rehabilitation protocols to expedite terrestrial compensation for vestibular pathologies, or preflight training and inflight countermeasures to facilitate adaptation to altered gravity environments. | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.uri | http://jhir.library.jhu.edu/handle/1774.2/59426 | |
| dc.language | en | |
| dc.publisher | Johns Hopkins University | |
| dc.publisher.country | USA | |
| dc.subject | vestibular | |
| dc.subject | oculomotor | |
| dc.subject | spaceflight | |
| dc.subject | prediction | |
| dc.title | Symptom-free in zero-g? Novel techniques for rapid assessment of vestibulo-ocular function and their use in predicting performance from baseline metrics | |
| dc.type | Thesis | |
| dc.type.material | text | |
| thesis.degree.department | Biomedical Engineering | |
| thesis.degree.discipline | Biomedical Engineering | |
| thesis.degree.grantor | Johns Hopkins University | |
| thesis.degree.grantor | School of Medicine | |
| thesis.degree.level | Doctoral | |
| thesis.degree.name | Ph.D. |