Exploration of the factors associated with stroke and sleep disorders
碩士 === 國立雲林科技大學 === 工業工程與管理系 === 103 === Studies have pointed out that 20%-63% stroke patients experience sleep disorders such as drowsiness, insomnia, parasomnia, circadian rhythm sleep disorders, periodic limb movement disorder, respiratory disorders, and so on. Once there is a problem, not only w...
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ndltd-TW-103YUNT00310342016-07-02T04:21:22Z http://ndltd.ncl.edu.tw/handle/85441956907572014911 Exploration of the factors associated with stroke and sleep disorders 罹患腦中風對睡眠障礙之相關性及影響因素探討 Chih-Ting Hsu 徐智霆 碩士 國立雲林科技大學 工業工程與管理系 103 Studies have pointed out that 20%-63% stroke patients experience sleep disorders such as drowsiness, insomnia, parasomnia, circadian rhythm sleep disorders, periodic limb movement disorder, respiratory disorders, and so on. Once there is a problem, not only will the quality of life be affected, but there will also be significant work and interpersonal relationship changes, which will in turn affect family function. Therefore, if we can gain an insight into the correlation between stroke and sleep disorders and find related factors that affect sleep disorders, we will be able to take measures of targeting factors and help patients in advance to minimize the possibility of sleep disorders and mitigate the obsession caused by sleep disorders. The National Health and Nutrition Examination Survey was be adopted in this study. From 2005 to 2008, a total of 341 adults aged above 18 and had stroke will be adopted as the participants. Through the genetic algorithm combine with data mining, the best factor combination affecting sleep disorders, with stroke, will be used to help medical staff monitor patient conditions, serve as a reference for medical staff in follow-up care of patients, and timely provide relevant treatment and care measures. According Genetic Algorithm combine with data mining, the impact factors of affecting sleep disorders in stroke like asthma, overweight, arthritis, congestive heart failure, Diabetes, feeling down, BMI, and so on. Appetite and chronic bronchitis may become implicit factors, and these factors are able to investigate deeply in the future. Besides, Logistic regression in this study shows more ability of predicting. It is expected to help doctors and family to determine the possibility for patients to reduce the risk of sleep disorders, provided treatment and care measures, and control of patient status at any time. Hsueh-Yi Lu 呂學毅 2015 學位論文 ; thesis 76 zh-TW |
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碩士 === 國立雲林科技大學 === 工業工程與管理系 === 103 === Studies have pointed out that 20%-63% stroke patients experience sleep disorders such as drowsiness, insomnia, parasomnia, circadian rhythm sleep disorders, periodic limb movement disorder, respiratory disorders, and so on. Once there is a problem, not only will the quality of life be affected, but there will also be significant work and interpersonal relationship changes, which will in turn affect family function. Therefore, if we can gain an insight into the correlation between stroke and sleep disorders and find related factors that affect sleep disorders, we will be able to take measures of targeting factors and help patients in advance to minimize the possibility of sleep disorders and mitigate the obsession caused by sleep disorders.
The National Health and Nutrition Examination Survey was be adopted in this study. From 2005 to 2008, a total of 341 adults aged above 18 and had stroke will be adopted as the participants. Through the genetic algorithm combine with data mining, the best factor combination affecting sleep disorders, with stroke, will be used to help medical staff monitor patient conditions, serve as a reference for medical staff in follow-up care of patients, and timely provide relevant treatment and care measures.
According Genetic Algorithm combine with data mining, the impact factors of affecting sleep disorders in stroke like asthma, overweight, arthritis, congestive heart failure, Diabetes, feeling down, BMI, and so on. Appetite and chronic bronchitis may become implicit factors, and these factors are able to investigate deeply in the future. Besides, Logistic regression in this study shows more ability of predicting. It is expected to help doctors and family to determine the possibility for patients to reduce the risk of sleep disorders, provided treatment and care measures, and control of patient status at any time.
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author2 |
Hsueh-Yi Lu |
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Hsueh-Yi Lu Chih-Ting Hsu 徐智霆 |
author |
Chih-Ting Hsu 徐智霆 |
spellingShingle |
Chih-Ting Hsu 徐智霆 Exploration of the factors associated with stroke and sleep disorders |
author_sort |
Chih-Ting Hsu |
title |
Exploration of the factors associated with stroke and sleep disorders |
title_short |
Exploration of the factors associated with stroke and sleep disorders |
title_full |
Exploration of the factors associated with stroke and sleep disorders |
title_fullStr |
Exploration of the factors associated with stroke and sleep disorders |
title_full_unstemmed |
Exploration of the factors associated with stroke and sleep disorders |
title_sort |
exploration of the factors associated with stroke and sleep disorders |
publishDate |
2015 |
url |
http://ndltd.ncl.edu.tw/handle/85441956907572014911 |
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