- 學位論文
數位訊號處理在臨床上的應用-數位腦波計數器
An Application of DSP to Clinical Medical-A Digital Brain Signal Counter
摘要
摘要 在本論文中，我們提出數位訊號處理技巧應用在腦波臨床醫學上。我們利用收集到的數位腦波訊號設計數位腦波計數器來紀錄δ、θ、α、β 或 γ次數。腦波資料來源是從一般年齡 39 到48歲的健康人取得。而我們matlab模擬系統。數位腦波計數器測試的結果腦波數位化計數是非常精準有用的。 首先，我們使用Butterworth的IIR濾波器是濾出不希望得到的腦波電源頻率。然而時間相位移將發生在腦波通過IIR濾波器時。為了消除時間相位移，腦波訊號再次通過IIR濾波器得到正確的腦波頻帶訊號。然後，為了後續處理將腦波分成信號框的語音處理技巧應用上來。再來,為了記錄腦波δ、θ、α、β 或γ 波，我們所設計的鎖相迴路應用不同的頻帶鎖頻。最後，數位計數器應用在臨床醫學數位腦波被建構。 我們研究的主要貢獻如下: (一)提出腦波在臨床醫學的時域處理。(二)希望設計數位計數腦波器給阿玆海默氏症和血栓性腦中風病患作診斷。(三)對於長時期記錄的腦波可以減少大量的記憶體。 在未來,期許可以將及時系統使用DSP晶片設計在硬體上。
並列摘要
Abstract In this thesis, the techniques of digital signal processing are applied to the application of clinical medical. A digital brain signal counter is designed to record the number of δ,θ,α,β or γ wave of a given digital Electroencephalogram ( EEG) signal. The brain signal counter is applied to the brain signal’s data comes from general healthy persons with ages 39 to 48 years old by matlab simulations. The fact that the brain signals with different frequencies are counted digitally with very good precision shows that the digital counter is practical for applications. At first, an IIR filter of Butterworth is used to filter out the undesired brain machine’s power frequencies. However, the time phase shift will occur when the brain signal passes the IIR filter. To erase the time phase shift, the brain signal passes the IIR filter again to get the correct filtered signal. Then, the techniques used in speech signal processing are adopted to divide the brain signal into frames for the subsequent processing. Next, in order to record the number of δ,θ,α,β or γwave of the brain signal, the phase locked loops with different locking frequencies are applied in our design. Finally, a digital counter for clinical medical applying to digital EEG is constructed. The main results of our work are as follows. (1) The time domain processing is used to application of clinical medical. (2) Design a digital counter for the diagnosis of patients with the Emboli Stroke’s and Alzheimer’s diseases. (3) Reduce the great amount of memory for recording the long term EEG signal. In the future, a hardware design by using DSP chip will be developed for the real-time applications.