以腦電圖分析及連續監控中風嚴重程度與變化

Continuous Monitoring and Analysis of Stroke Severity and Progress Based on Electroencephalography

周維中(Wei-Jung Jou)

指導教授 ： 吳安宇

國立臺灣大學/電機資訊學院/電子工程學研究所/碩士(2014年)

https://doi.org/10.6342/NTU.2014.10006

摘要

腦中風為當今世界上最主要的死亡原因之一，每年造成無數人口死亡或是嚴重失能，這些中風患者在醫療行為及家庭照護上所費不貲。除了現在醫院採用的數種功能性評估以及醫學影像系統，醫療人員需要更連續及時，更量化的檢驗方式，來反映中風病患的腦部狀態。
腦電圖為在人頭皮上以非侵入的方式填貼電極量測腦部神經的放電情形，這項工具已被廣泛的使用在反映大腦的功能，原因是腦電圖直接關係到的是腦內神經的完整度，許多研究也指出腦電圖的頻率分布可以反映出大腦的活動情形，更有研究強調腦電圖在監測各種腦疾病上有相當大的價值。而技術員表示，腦電圖的量化分析可使原本從腦電圖上看不出的異狀表露出來，輔助使得腦電圖更容易觀測，進而可使用在腦中風病人的觀察。然而，除了癲癇病人以外，現行臨床醫學鮮少把腦電圖作為分析神經疾病的標準工具，普遍是因為腦電圖的不確定性以及高比例的錯誤回報。
這篇論文的目標是提出一個嶄新的腦中風特徵擷取流程及方法，建立在腦電圖的多尺度熵分析法，並適用於加護病房的急性腦中風病人。本論文提出的改良多尺度熵量化指數 (qmMSE) 針對美國國家衛生研究院腦中風量表的結果指出，該指數可顯著的區分中風較輕微以及中風較嚴重的兩群病人，且除了可區分美國國家衛生研究院腦中風量表以外，對於其他臨床適用的指數亦顯示其一致性。最後改良多尺度熵量化指數可用於中風嚴重程度監控，並相較於傳統頻率分析方式，適用於更廣泛的中風族群。

關鍵字

腦電圖 ； 中風 ； 嚴重程度 ； 量化分析

並列摘要

Stroke is the leading cause of death and disability worldwide. This requires significant resources in health-care costs. In addition to physical examination and brain imaging, medical staff need a more quantitative and continuous method to reveal and monitor the severity of patients.
Electroencephalogram (EEG) measures the electrical activity of neuron inside the brain. It has been a reliable test to assess cerebral function, which is also strongly related to the completeness of brain. Many works indicated the EEG spectrum can represent the activity of brain neuron; other works emphasize EEG is valuable for monitoring certain encephalopathy patient. Moreover, some claim that acute quantitative EEG (qEEG) might be used to monitor and predict stroke evolution. However, apart from epilepsy detection, EEG is rarely being used to analyze other neurological disorder due to the unreliable specificity and sensitivity.
The goal of the thesis is to propose a novel feature based on nonlinear method – multiscale entropy (MSE). In the intensive care unit (ICU) admitted acute stroke patients, our proposed feature has significant difference between high NIHSS groups and low NIHSS groups. It is not only highly correlated to National Institutes of Health Stroke Scale (NIHSS), but also consistent with other clinical parameters. Beside, our proposed method is suitable for wider groups in ICU admitted acute stroke patients.

並列關鍵字

EEG ； Stroke ； Severity ； Entropy ； Quantitative

參考文獻

[1] WHO, Stroke, Cerebrovascular accident. Available: http://www.who.int/topics/cerebrovascular_accident/en/

[2] The Internet Stroke Center. Available: http://www.strokecenter.org/

[3] Stroke. Available: http://www.nhs.uk/Conditions/Stroke/Pages/Introduction.aspx

[4] L. M. Liou, C. F. Chen, Y. C. Guo, H. L. Cheng, H. L. Lee, J. S. Hsu, R. T. Lin, and H. F. Lin, "Cerebral white matter hyperintensities predict functional stroke outcome," Cerebrovasc Dis, vol. 29, pp. 22-7, 2010.

[5] S J M Smith, "EEG in neurological conditions other than epilepsy: when does it help, what does it add?" J Neurol Neurosurg Psychiatry 2005; 76: ii8-ii12.