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研究生(外文):Yu-Wei Liu
論文名稱(外文):Clinical Application of Autonomic Nerve System Activity Analysis in Traumatic Brain Injury
外文關鍵詞:Traumatic brain injuryAutonomic dysfunction syndromeActivity of autonomic nervous systemDetrended fluctuation analysisHeart rate variabilityFractalHeavy comaPrognosis.
  • 被引用被引用:1
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Autonomic dysfunction syndrome (ADS) is reported in 15-33% of cases after severe traumatic brain injury (TBI). The clinical manifestations consist of fever, tachycardia, hypertension, tachypnea, dystonia, diaphoresis, increased intracranial pressure (IICP), etc. The vulnerable injured brain is easy to suffer from the secondary injury resulting from ADS in the acute stage. Increased morbidity and mortality are usually associated. Timely clinical assessment and fine critical care are crucial to the prognosis, and this should be proceeded aggressively under careful monitoring.
By joining the engineering technique and clinical medical care system together, this study is aimed to establish an autonomic nerval monitoring system based on the currently-used monitoring in the intensive care unit (ICU) for TBI patients. In this study, we choose the electrocardiogram, and apply the analytic algorithms of detrended fluctuation analysis (DFA) in heart rate variability analysis (HRV). With the characteristic of fractal and self-similarity, the activity of the autonomic nervous system could be assessed.
In order to help to test and establish the index of autonomic nervous system (ANS), we apply the data recorded from normal subjects to investigate the ANS activity with different influence of external stimulations on the beginning stage of this study. On the second stage of this study, we further choose the severe TBI patients who are under heavy coma and lose the function of ANS as material for this investigation, and assess the activity of ANS along the treatment course for the severe TBI patients via the ANS index. Moreover, we observe the relationship between the activity of ANS and clinical condition. By the information derived in this study, we wish to predict prognosis and monitor the patients’ response to the therapeutic intervention. Finally, we hope this monitoring system would deliver the information to guide the clinicians to predict outcome and make treatment plan for the clinical care. Therefore, the patients’ safety and the quality of clinical cares are enhanced.
Front cover i
Title Page ii
審定書 iii
授權書 iv
中文摘要 v
Abstract vi
誌謝 vii
Content viii
List of Figure ix
List of Table xi
Chapter 1 Introduction 1
1.1 Background 1
1.2 Review of Studies 9
1.3 Purpose 11
1.4 Brief summary of chapters 12
Chapter 2 Analysis Algorithm 14
2.1 Detrended Fluctuation Analysis ……...….………………………..…………..14
Chapter 3 Experiment Conditions and Method 19
3.1 Choice of Materials 19
3.2 Data Collection Process 21
3.3 Process of Data Analysis 24
3.4 Experiment Equipments 26
Chapter 4 Results 30
4.1 Materials 30
4.2 Experiment Design 31
4.3 Analysis results 36
Chapter 5 Conclusions and Discussion 56
5.1 Conclusions 56
5.2 Discussion 57
References 58
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