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  • 學位論文

發展可攜式生理訊號長期記錄及分析系統

The Development of a Portable Biosignal Recording System

指導教授 : 胡威志

摘要


本研究目的在於設計可攜式生理訊號長期記錄及分析系統評估心律變異度以及同一時間的腦波變化相關性,此系統以MSP430微控器為主控,擷取一個通道心電圖(ECG)以及六個通道腦波(EEG)訊號,生理訊號之取樣率為200Hz,儲存在128 Mbytes flash中可記錄24小時。系統可將生理訊號傳輸到電腦端計算,分析心率變異度(HRV)與腦波頻譜功率,評估兩者之相關性。 本研究利用正常睡眠實驗及腦波異常相關位置實驗驗證儀器的實效性,正常睡眠實驗共測試與記錄十人例,利用非快速動眼期(NREM)以及快速動眼期(REM)睡眠中的心律及腦波變化情形去驗證此系統,在NREM睡眠時,越趨於熟睡心律會呈現平穩及緩慢的狀態,且腦波低頻成分(δactivity)會變大,在REM睡眠期時,腦波低頻成分(δ activity)會變小,高頻成分會變大 (βactivity)以及心率變異會增加。在腦波異常相關位置實驗共測試與記錄二人例,驗證異常慢波發生之位置與腦部血管或缺血之相關位置。透過以上臨床實驗結果驗證本系統長時間記錄心電圖及腦波及利用本系統設計之分析程式可找出陣發性心率變異與腦波異常的相關性。

並列摘要


The objective of the study was to design a portable bio-signal recording system to assess the relationship between electro -encephalogram (EEG) activity and heart rate variability (HRV). The system was integrated using a microprocessor (MSP430) to acquire signals of six channels of EEG and one channel of ECG. The sampling rate of the devices was 200Hz. The acquired data of ECG and EEG signals can be recorded in a 128Mbytes flash memory. The size of memory was sufficient for 24 hours of recording. The data can be downloaded to a personal computer. The recorded ECG and EEG can be reviewed and analyzed using self-developed software. One is able to review the relationship of EEG and HRV with the result of short-time Fourier analysis. The results from normal sleeping data analysis and the data of patient with cerebral lesion were used to verify the effectiveness of the system. Ten sets of normal sleeping data were used to examine the coherence of our data to the reviewed literatures. The result showed that the, heart rate was significantly stable and slow, and delta activity increased gradually during Non Rapid Eye Movement (NREM) and deep sleeping. The heart rate was fast and delta activity decreased, beta activity increased in Rapid Eye Movement sleeping stage. The abnormal slow wave recorded with CT confirmed cerebral lesion patients were showing the corresponding location of recording lead to the location of cerebral lesion. With these results, the device and the developed analysis software can be used in detecting paroxysmal tachycardia and abnormal EEG.

參考文獻


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