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首頁(yè)> 外文學(xué)位 >Predicting Pathophysiological Events: Sleep Disordered Breathing, Vigilance Lapses, Driving Errors.
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Predicting Pathophysiological Events: Sleep Disordered Breathing, Vigilance Lapses, Driving Errors.

機(jī)譯：預(yù)測(cè)病理生理事件：睡眠障礙呼吸，警惕失誤，駕駛錯(cuò)誤。

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摘要

Disrupted or insuficient sleep is a major cause of motor vehicle accidents, workplace injuries, and industrial disasters. Responding to this epidemic is a public health imperative. Two major causes of disrupted sleep and consequent impairment of daytime performance are obstructive sleep apnea (OSA) and sleep restriction or deprivation. OSA is a highly prevalent disorder in which patients experience repetitive total or partial collapses of the airway, respectively referred to as apneas and hypopneas, during sleep. These episodes of sleep disordered breathing (SDB) are commonly associated with arousal from sleep. Consequently, OSA patients experience disrupted sleep and are exposed to chronic intermittent hypoxemia, leading to impaired daytime performance and excessive daytime sleepiness. People with OSA are also at risk for heart disease, stroke, metabolic disorders, and cognitive dysfunction. Many of the adverse out- comes associated with OSA are also associated with sleep deprivation, even in the absence of a concomitant sleep disorder.;Therefore, there is a pressing need to develop a deeper understanding of the mechanisms that underlie OSA and the effects of restricted sleep. Furthermore, public safety will be enhanced by improved and more efficacious treatment of sleep disorders as well as accurate and reliable methodologies to monitor the behavioral state of at-risk individuals and respond to imminent decrements or lapses in performance. At the same time, the complexity of the processes that underlie SDB, sleep restriction, and their consequences, as well as significant inter-individual variability, necessitates individualized systems-based approaches. Such methodologies may provide important tools to aid in the identification and disentanglement of the differential impact of numerous pathophysiological mechanisms in heterogeneous populations and reveal subgroups or empirical stratifications among groups of individuals.;This dissertation aimed to take a first step toward responding to these needs by establishing the feasibility of individualized approaches to predict the onset of pathophysiological events in people with OSA and in acutely sleep deprived but otherwise healthy individuals. Our methods were also designed to expose precisely the signals and signal features that enable accurate and reliable predictions. The analysis of important predictors of pathophysiological events provides a novel approach to investigating the mechanisms that initiate the events. In particular, methods were developed to 1) predict episodes of SDB in the next 10 to 60 seconds in OSA patients, 2) lapses in vigilance, or sustained attention, within the next 30 seconds in OSA patients and in healthy individuals acutely deprived of sleep for 24 hours, and 3) mistakes during simulated driving within the next 30 seconds in OSA patients and acutely sleep deprived healthy subjects. (Abstract shortened by UMI.).
機(jī)譯：睡眠中斷或睡眠不足是導(dǎo)致汽車事故，工作場(chǎng)所受傷和工業(yè)災(zāi)難的主要原因。應(yīng)對(duì)這種流行病是公共衛(wèi)生的當(dāng)務(wù)之急。睡眠受阻并導(dǎo)致日間表現(xiàn)受損的兩個(gè)主要原因是阻塞性睡眠呼吸暫停（OSA）和睡眠受限或剝奪。 OSA是一種高度流行的疾病，在這種疾病中，患者在睡眠期間反復(fù)出現(xiàn)氣道的全部或部分塌陷，分別稱為呼吸暫停和呼吸不足。這些睡眠呼吸障礙（SDB）發(fā)作通常與睡眠引起的覺(jué)醒有關(guān)。因此，OSA患者的睡眠受到干擾，并暴露于慢性間歇性低氧血癥，導(dǎo)致白天的表現(xiàn)受損和白天過(guò)多的嗜睡。 OSA患者也有患心臟病，中風(fēng)，代謝紊亂和認(rèn)知功能障礙的風(fēng)險(xiǎn)。即使在沒(méi)有伴隨的睡眠障礙的情況下，許多與OSA相關(guān)的不良后果也與睡眠剝奪有關(guān);因此，迫切需要對(duì)OSA的基礎(chǔ)機(jī)制及其產(chǎn)生的影響有更深入的了解睡眠受限。此外，將通過(guò)改進(jìn)和更有效的睡眠障礙治療方法以及用于監(jiān)測(cè)高危人群的行為狀態(tài)并對(duì)即將發(fā)生的性能下降或下降做出反應(yīng)的準(zhǔn)確可靠的方法來(lái)提高公共安全。同時(shí)，作為SDB的過(guò)程的復(fù)雜性，睡眠限制及其后果以及個(gè)體之間的重大差異，都需要采用基于系統(tǒng)的個(gè)性化方法。這樣的方法學(xué)可能提供重要的工具，以幫助識(shí)別和區(qū)分異質(zhì)種群中多種病理生理機(jī)制的差異影響，并揭示個(gè)體群體之間的亞組或經(jīng)驗(yàn)分層。確定個(gè)體化方法的可行性，以預(yù)測(cè)OSA患者和嚴(yán)重缺乏睡眠但健康的個(gè)體中病理生理事件的發(fā)作。我們的方法還旨在精確暴露信號(hào)和信號(hào)特征，從而能夠進(jìn)行準(zhǔn)確而可靠的預(yù)測(cè)。病理生理事件的重要預(yù)測(cè)因子的分析提供了一種新穎的方法來(lái)調(diào)查引發(fā)事件的機(jī)制。特別是，已經(jīng)開(kāi)發(fā)出了以下方法：1）在OSA患者中預(yù)測(cè)接下來(lái)10至60秒內(nèi)SDB的發(fā)作； 2）在OSA患者和嚴(yán)重缺乏睡眠的健康個(gè)體中，在接下來(lái)的30秒內(nèi)保持警惕或持續(xù)關(guān)注持續(xù)24小時(shí)，以及3）OSA病人在接下來(lái)的30秒內(nèi)進(jìn)行模擬駕駛時(shí)出現(xiàn)錯(cuò)誤，并且嚴(yán)重睡眠不足的健康受試者。 （摘要由UMI縮短。）。

著錄項(xiàng)

  • 作者

    Waxman, Jonathan A.;

  • 作者單位

    University of Illinois at Chicago.;

  • 授予單位 University of Illinois at Chicago.;
  • 學(xué)科 Engineering Electronics and Electrical.;Engineering General.;Health Sciences Pathology.
  • 學(xué)位 Ph.D.
  • 年度 2014
  • 頁(yè)碼 742 p.
  • 總頁(yè)數(shù) 742
  • 原文格式 PDF
  • 正文語(yǔ)種 eng
  • 中圖分類 遙感技術(shù);
  • 關(guān)鍵詞

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