本研究目的在於發展一套以FPGA(Field Programmable GateArray, 現場可程式化邏輯閘陣列)為核心的SoC(System on Chip)生醫訊號處理系統平台,並可整合控制周邊裝置、LCD、USB、Flash Memory、SRAM Memory;建構可程式化RISC之MIPS運算系統及即時平行處理輸入訊號之功率頻譜(FFT,Fast Fourier Transform),以可程式化之運算方式用於多樣變化之生理訊號,利用程式執行程序處理並能進一步分析生理訊號達到即時量測分析的效果。 以FPGA可程式化系統晶片針對生醫訊號處理之時域及頻域分析需求,本論文設計以Pipeline MIPS架構為基礎之生醫晶片訊號處理系統晶片指令集,其指令集分為兩大類:尋常指令集在生醫晶片上主要功能為搬動資料及判斷比較資料等;特殊指令集為啟動平行運算旗標,並可做即時訊號處理、資訊儲存及資訊顯示等。 論文以心率變異度分析為例研發生醫電訊號之應用,將SoC系統晶片與平台用於分析心率變異度特殊目的之處理,並討論即時生醫訊號處理系統雛型之建置與驗證。本研究系統平台主頻率為50MHz、MIPS指令執行速度為10MHz、系統心電圖取樣率為303Hz,分析心率變異度以5Hz重新取樣等表現生醫電訊號分析之應用,即時心電訊號擷取與處理運算結果之FFT頻譜與MATLAB運算FFT頻譜結果作驗證比對,其驗證頻譜數值結果線性相關度達0.9926。結果顯示,本系統平台與一般現行之監視系統更具有擴充性與實用性,可提升居家看護或3C產品之開發運用。
The Objective of this research is to develop a biomedical signal processing System on Chip (SoC) platform which is based on Field Programmable Gate Array. The SoC (FPGA) will be integrating and controling the peripherals device such as LCD, USB, Flash Memory, and SRAM Memory. It is a RISC architecture Microcontroller (MCU) which is based on the Microprocessor without Interlocked Pipeline Stages (MIPS) techonology. The SoC will be used to extract the power spectral from acquired bio-signal with a dedicated co-processor of Fast Fourier Transform (FFT). The design of FPGA programmable system chip was specifically dedicated to the analysis requirement of the frequency and time domain analysis for Bio-medical signal processing. The instruction sets were divided into two types. One is regular MCU instruction which function wass to controlling the operation flow, to move data and to perform arithmetic and logic operation. The other is the special instruction set which was to set-up parallel computing flag that will be performing the signal processing in real-time, governing the data storage, and displaying the presentation of the data and the result. In this thesis, the processes of Heart Rate Variability (HRV) analysis in real-time will be an example to present the result of this SoC desing. In this Soc platform, main frequency and MIPS instruction frequency uses 50MHz and 10MHz, respectively.The sampling rate for acquiring electrocardiogram is 303Hz, and HRV is re-sampled in 5Hz for analyzing. The results of FFT power spectra of real-time ECG processing was compared to the result that processed using the MatLab. The correlation of the frequency spectrum was 0.9926. This showed that the designed SoC platform is capable for processing bio-signal in real-time.