| DC 欄位 |
值 |
語言 |
| DC.contributor | 機械工程學系 | zh_TW |
| DC.creator | 謝孟桓 | zh_TW |
| DC.creator | Ｍeng-Huan Hsieh | en_US |
| dc.date.accessioned | 2018-7-10T07:39:07Z | |
| dc.date.available | 2018-7-10T07:39:07Z | |
| dc.date.issued | 2018 | |
| dc.identifier.uri | http://ir.lib.ncu.edu.tw:88/thesis/view_etd.asp?URN=105323083 | |
| dc.contributor.department | 機械工程學系 | zh_TW |
| DC.description | 國立中央大學 | zh_TW |
| DC.description | National Central University | en_US |
| dc.description.abstract | 妥瑞氏症是一種常見的神經內科疾病，好發於男性孩童及青少年，主要的症狀是
動作型，如快速而短促的眨眼睛、噘嘴、裝鬼臉;以及聲語型，如清喉嚨、大叫。目
前缺乏單一的標準來判定是否為妥瑞氏症。臨床上多以精神疾病診斷與統計手冊及耶
魯抽動症整體量表為妥瑞氏症疾病輔助診斷及區分嚴重程度。
本研究以妥瑞氏症患者的全腦腦電波數據為素材(包含張眼與閉眼兩種情形之腦 電波數據)。藉由經驗模態分解法及尺度相關的固有熵分析，找尋與妥瑞氏症相關的動 態生醫指標。研究得到的動態生醫指標可以作為妥瑞氏症臨床診斷的輔助工具。此 外，也使用量化的腦波特徵參數與 YGTSS 之間的關係，建立新的指標應用於妥瑞氏症 嚴重程度的參考。
本研究發現，能量密度與尺度相關的固有熵用在實驗組與對照組間存在有顯著的 統計差異(P<0.001)。能量密度的動態生醫指標與 YGTSS 之間的關係存在一定的相關性 (R = 0.39)。隨著嚴重程度的上升，高頻腦波能量密度呈負相關，低頻腦波能量密度呈 正相關。然而，尺度相關的固有熵在與 YGTSS 的相關性並沒有能量密度來的好。
本研究根據張眼能量密度定義的動態生醫指標在診斷妥瑞氏症上有較佳的表現。
由閉眼能量密度定義的動態生醫指標則與妥瑞氏症的嚴重程度有較佳的相關性。與診
斷妥瑞氏症相關的動態生醫指標多來自於右前腦區。然而本研究存在樣本不足的問
題，期待能後續的研究中能得到更多的樣本，提升研究成果在臨床在的應用價值。 | zh_TW |
| dc.description.abstract | Tourette syndrome (TS) is a common neurological disorder. Most of patients are male children and adolescents. TS is characterized by motor tics and vocal (phonic) tics, such as eye blinking, grinning, grimacing, throat clearing, and shouting. So far, there is no clinical standard for diagnosing the TS. The Diagnostic and Statistical Manual of Mental Disorders (DSM) and Yale Global Tic Severity Scale (YGTSS) are two common tools for diagnosing and evaluating TS.
In this study, whole-brain electroencephalography (EEG) recordings, for two examination conditions of eye-open and eye-closed, were analyzed by empirical mode decomposition (EMD) and scale-dependent intrinsic entropy analysis. The aim of this study is to figure out the dynamic biomarkers for characterizing TS. These dynamic biomarkers are helpful for diagnosing TS as a complementary tool in clinical practices. Furthermore, we defined a new assessment according to the relationships between the dynamical biomarkers and YGTSS for evaluating the severity of TS.
As our findings, the statistical differences between the control and experimental groups are significant (p-value < 0.001) for many dynamic biomarkers, using the energy densities on specific channel within specific frequency bands. The dynamic biomarkers using energy densities are significantly correlated with YGTSS (the correlation coefficient is 0.39). The high-frequency energy density increases with the increase of YGTSS, and the low- frequency energy density decreases with the increase of YGTSS. The diagnostic performance using the biomarkers of energy density is better than that using biomarkers of entropies.
In summary, the biomarkers using energy densities with eye-closed performed ii
better than those using energy densities with eye-open did. The new assessment using the energy densities with eye-open is significantly correlated to the severity of TS represented by YGTSS. Most of the dynamic biomarkers locate on the right hemisphere and frontal lobe. However, only a limited number of subjects were investigated in this study. The findings of this study cannot be used in clinical practices before a sufficient number of subjects are investigated in the future works. | en_US |
| DC.subject | 非線性分析 | zh_TW |
| DC.subject | 腦波 | zh_TW |
| DC.subject | 經驗模態分解法 | zh_TW |
| DC.subject | 尺度相關的固有熵 | zh_TW |
| DC.subject | 妥瑞氏症 | zh_TW |
| DC.subject | nonlinear analysis | en_US |
| DC.subject | electroencephalogram | en_US |
| DC.subject | Empirical Mode Decomposition | en_US |
| DC.subject | scale-dependent intrinsic entropy | en_US |
| DC.subject | Tourette | en_US |
| DC.title | 以經驗模態分解法為基礎的非線性分析應用於妥瑞氏症全腦腦波分析 | zh_TW |
| dc.language.iso | zh-TW | zh-TW |
| DC.type | 博碩士論文 | zh_TW |
| DC.type | thesis | en_US |
| DC.publisher | National Central University | en_US |