How to Quantify “Good Sleep”: A Spectral Analysis of Sleep Morphology in Healthy Adult EEG and the Role of Sleep Spindles in Aging and Neurodegeneration
| dc.contributor.advisor | David Condon Don Tucker | en |
| dc.contributor.advisor | ||
| dc.contributor.advisor | ||
| dc.contributor.author | Kabasenche, Elyria | |
| dc.date.accessioned | 2022-09-28T22:17:59Z | |
| dc.date.available | 2022-09-28T22:17:59Z | |
| dc.date.issued | 2022-05 | |
| dc.description | 23 pages | en |
| dc.description.abstract | The importance of good sleep cannot be overstated. What makes sleep “good”, productive, and beneficial are of interest to any sleep researcher. Studying morphology of sleep features can provide insight about what differentiates healthy and unhealthy sleep and create benchmarks for recognizing instances when characteristics such as aging and disease may be impacting sleep quality. The purpose of this study was to examine an N2 sleep feature termed a sleep spindle and conduct an analysis of morphology on a sample of healthy adult EEG using recently validated and created sleep spindle detection algorithm to create a baseline measurement for spindle presence. The effect of age on spindles was of particular interest and was found to be related to a decrease in spindle length. The possible reason for this effect is discussed, as well as future applications for use of this algorithm and spindle analysis. | en |
| dc.identifier.uri | https://hdl.handle.net/1794/27517 | |
| dc.language.iso | en | en |
| dc.publisher | University of Oregon | en |
| dc.rights | Creative Commons BY-NC-ND 4.0-US | en |
| dc.subject | Psychology | en |
| dc.subject | Sleep Spindles | en |
| dc.subject | Morphology | en |
| dc.subject | Aging | en |
| dc.subject | Neurodegeneration | en |
| dc.subject | EEG | en |
| dc.title | How to Quantify “Good Sleep”: A Spectral Analysis of Sleep Morphology in Healthy Adult EEG and the Role of Sleep Spindles in Aging and Neurodegeneration | en |
| dc.type | Thesis / Dissertation | en |