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  • 學位論文

心率變異度量測實現雲端個人健康管理平台- 一種改良式心電圖QRS波即時偵測方法

A Cloud-based Personal Health Management Platform by Measuring Heart Rate Variability – An Improved ECG QRS Detection Algorithm

指導教授 : 林永松

摘要


近幾年智慧型行動裝置市場呈現爆炸性成長,並已逐漸改變消費者既有之生活型態與使用習慣。資通訊技術的快速變化,也帶動了行動醫療與預防醫學的發展,學者預估以往疾病治療的支出比重也將由2007年的70%減少至2025年的35%,預防監測的支出比重則將日益增加。醫療服務地點也將由醫療院所逐漸分散至診所、家庭與個人,院外的連續監測與個人健康管理將愈趨重要。 傳統心電圖監測多為病人在醫院靜躺在床上所做的靜態心電圖,且必須由醫護人員操作複雜的醫療儀器進行監測。直到為了連續監測,而開始使用24小時心電圖監測器,自始心電圖監測開始行動化,不再限制於醫院做監測。 1996年歐美醫學專家制定了心率變異度(Heart Rate Variability, HRV),為監控個人自律神經健康程度的一個最重要指標,自律神經健康程度與我們日常生活品質息息相關。透過心率變異度分析判斷自律神經健康,使得心電圖監測不再只是在醫院內疾病治療時的工具,而是隨時隨地觀察個人健康狀況的重要工具。 然而傳統心電圖監測方式使得心電圖監測並未能普及,不但每次量測需要耗材,在操作上更必須有專業知識醫護人員在旁輔助教學。因此本研究為了改善此狀況,讓心電圖的監測真正普及化,提出以穿戴式裝置實現隨時隨地監測心電圖。但捨棄傳統導極貼片式量測方式,卻為自動化心電圖波形偵測帶來相當的困難,導致過去的偵測方法並不適用,因此偵測方法的改進為本研究之重點所在。 本研究建構一完整個人健康管理平台,透過隨時隨地心率變異度分析,並隨時上傳資料與透過雲端檢視歷史資料,幫助個人作自律神經健康之管理。主要提出一改良式自動化偵測QRS波方法,克服穿戴式裝置量測心電圖時,自動化心電圖波形偵測的困難,包括訊號微弱造成雜訊較大與量測中晃動造成不正常的波形產生等等,以真正實現穿戴式裝置心電圖量測量測,同時更利用心源性呼吸方式(EDR, ECG Derived Respiration)加入了即時呼吸變化偵測機制,增加此健康管理平台的發展性。

並列摘要


In recent years, smart mobile devices market showed explosive growth, and has gradually changed both the consumer lifestyle and habits. Rapid changes in information and communication technology, has also led to action the development of medical and preventive medicine. Scholars estimate the proportion of the expenditure in the past treatment of disease will also be reduced FROM 70% in 2007 to 35% in 2025, instead preventive monitoring will be an increasing proportion of the expenditure. Also, Medical service locations will also be gradually dispersed to hospitals clinics, family and individual, and the individual's self-monitoring and health management will become increasingly valued. In traditional ECG monitoring, patients has to lie on hospital bed, and the complex medical instruments must operate by healthcare professionals. Not until there are 24-hour ECG monitors (Holter) for some patients to do the continuous monitoring, the ECG monitoring can only be done in hospital. In 1996 Western medical experts have developed the HRV (Heart Rate Variability, HRV) being the most important indicator of health of ANS (Autonomic Nervous System). Health of autonomic nervous system and is closely related to the quality of our daily lives. It is because that through the Analysis of heart rate variability can observe autonomic nervous system health, making ECG monitoring is no longer just a tool for disease treatment in the hospital but a important tool for personal health management anytime and anywhere. However, the traditional way of making electrocardiographic monitoring ECG monitoring did not spread to the world, not only because every single time monitoring needs consumables but it must have experts beside for operate. Therefore, this study in order to improve this situation, and let ECG monitoring truly universal, has proposed the wearable ECG monitoring device, achieving HRV measurements at any time to help individuals manage the autonomic nervous system health. But not using the traditional patch type measurement method causes considerable difficulties to the automated detection of the ECG waveform and led past detection methods do not apply. This study constructed a complete personal health management platform to help individuals make the autonomic nervous system health management through Heart rate variability analysis at anywhere and anytime. Also it can upload data and view historical data through the cloud server. Mainly proposed an improved automated detection method of QRS complex to overcome the difficulties occurred when using wearable device to monitor ECG, including weak signal and moving when measuring. In addition, immediate breathing change detection, which is implemented by EDR (ECG Derived Respiration), is added on the platform to increase the Expansibility of this health management platform.

參考文獻


一、中文文獻
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[3] 郭沛欣(2009),遠距醫療照護服務之雲端運算應用初探,資策會MIC產業情報研究所。
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