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基于無(wú)線通信的多點(diǎn)脈搏信號(hào)檢測(cè)方法研究

發(fā)布時(shí)間:2018-05-16 11:18

  本文選題:PVDF + ZigBee無(wú)線技術(shù)。 參考:《華南理工大學(xué)》2012年碩士論文


【摘要】:人體的脈搏波動(dòng)中蘊(yùn)藏著豐富的生理病理信息,通過對(duì)提取的脈搏信號(hào)進(jìn)行分析,可以將潛在的心血管疾病盡早的診斷出來(lái),為心血管疾病的預(yù)防和治療爭(zhēng)取寶貴的時(shí)間。目前人們對(duì)脈搏信息檢測(cè)和分析方面的研究做了很多工作,也取得了很多優(yōu)秀的成果;跓o(wú)線通信的多點(diǎn)脈搏信號(hào)檢測(cè)是一種新穎而有效的檢測(cè)方法,它將PVDF壓電薄膜傳感器、Zigbee無(wú)線通信、USB接口和信號(hào)處理等技術(shù)相結(jié)合,使得檢測(cè)過程更加方便靈活,檢測(cè)結(jié)果更為準(zhǔn)確豐富。 使用五點(diǎn)式PVDF壓電脈搏傳感器來(lái)檢測(cè)人體橈動(dòng)脈處五點(diǎn)的脈搏信息,消除了單點(diǎn)傳感器測(cè)量帶來(lái)的偶然誤差,而且獲取的脈搏信息更為豐富。設(shè)計(jì)PVDF壓電脈搏傳感器為臺(tái)型,將五個(gè)圓形的PVDF壓電薄膜嵌入五個(gè)排列規(guī)則且互相獨(dú)立的槽中,制作信號(hào)調(diào)理電路來(lái)處理PVDF壓電薄膜形變產(chǎn)生的脈搏電荷信號(hào),獲取所需的脈搏電壓信號(hào)。在傳感器背側(cè)安裝電池和天線,保證信號(hào)采集過程中的電源供應(yīng)與信號(hào)發(fā)射。 采用Zigbee無(wú)線通信技術(shù)來(lái)傳輸脈搏信息,達(dá)到了移動(dòng)性、實(shí)時(shí)性、可靠性、功耗低、成本低和輻射小的效果。使用USB接口連接PC機(jī),實(shí)現(xiàn)了高速傳輸和方便快捷的目的。Zigbee單片機(jī)型號(hào)選用CC2430,USB接口芯片采用EZ-USB FX2,工作模式為SLAVE FIFO。數(shù)字脈搏信號(hào)從Zigbee網(wǎng)絡(luò)節(jié)點(diǎn)傳輸?shù)街鳈C(jī)的過程是:Zigbee網(wǎng)絡(luò)節(jié)點(diǎn)將采集的脈搏信號(hào)通過組網(wǎng)傳給Zigbee協(xié)調(diào)器,協(xié)調(diào)器單片機(jī)CC2430作為外部主控制器控制EZ-USB FX2的工作,將脈搏數(shù)據(jù)通過USB接口傳到PC機(jī)。SLAVE FIFO的工作模式降低了EZ-USB FX2接口芯片工作的復(fù)雜性,同時(shí)也提高了傳輸效率。 獲取的脈搏信息需要進(jìn)行數(shù)字濾波處理。文中使用了三種濾波方法,即采用單片機(jī)程序?qū)γ}搏信息進(jìn)行滑動(dòng)算術(shù)平均值濾波、小波變換閾值濾波和建立在零點(diǎn)極點(diǎn)抵消基礎(chǔ)上的簡(jiǎn)單整系數(shù)濾波,并對(duì)三種濾波效果進(jìn)行了比較。接下來(lái)對(duì)獲取的脈搏信息分別進(jìn)行了時(shí)域和頻域的信號(hào)分析,獲得了較好的處理效果。時(shí)域方面,采用了基于模極大值的時(shí)域特征點(diǎn)提取和基于經(jīng)驗(yàn)?zāi)B(tài)分解的時(shí)域特征點(diǎn)提取方法;頻域方面,應(yīng)用了基于功率譜估計(jì)的特征提取和基于譜能比的特征提取方法。
[Abstract]:There are abundant physiological and pathological information in pulse fluctuation of human body. By analyzing the extracted pulse signals, potential cardiovascular diseases can be diagnosed as soon as possible, and valuable time can be gained for the prevention and treatment of cardiovascular diseases. At present, people have done a lot of research on pulse information detection and analysis, and achieved a lot of excellent results. Multi-point pulse signal detection based on wireless communication is a novel and effective detection method. It combines PVDF piezoelectric film sensor with PVDF interface and signal processing technology, which makes the detection process more convenient and flexible. The results are more accurate and abundant. The five-point PVDF piezoelectric pulse sensor is used to detect the five-point pulse information of the human radial artery, which eliminates the accidental error caused by the single-point sensor measurement, and the obtained pulse information is more abundant. The PVDF piezoelectric pulse sensor is designed. Five circular PVDF piezoelectric films are embedded in five regular and independent grooves. A signal conditioning circuit is made to process the pulse charge signal generated by the PVDF piezoelectric film deformation. Obtain the desired pulse voltage signal. Batteries and antennas are installed on the back of the sensor to ensure power supply and signal transmission during signal acquisition. Zigbee wireless communication technology is used to transmit pulse information, which achieves the effect of mobility, real-time, reliability, low power consumption, low cost and low radiation. Using USB interface to connect PC, the purpose of high speed transmission and convenience is realized. EZ-USB FX2 is used in CC2430U USB interface chip, and the mode of operation is SLAVE FIFO. The process of transmitting digital pulse signal from Zigbee network node to host computer is that the pulse signal collected by the network node is transmitted to the Zigbee coordinator through the network, and the single chip microcomputer CC2430 acts as the external master controller to control the work of EZ-USB FX2. The mode of transmitting pulse data through USB interface to SLAVE FIFO reduces the complexity of EZ-USB FX2 interface chip and improves the transmission efficiency. The obtained pulse information needs to be processed by digital filtering. In this paper, three kinds of filtering methods are used, that is, sliding arithmetic average filter for pulse information, wavelet transform threshold filter and simple integer coefficient filter based on zero pole cancellation. Three filtering effects are compared. Then the obtained pulse information is analyzed in time domain and frequency domain, and good processing effect is obtained. In time domain, time domain feature point extraction based on modulus maximum and time domain feature point extraction based on empirical mode decomposition are adopted. In frequency domain, power spectrum estimation based feature extraction and spectral energy ratio based feature extraction method are applied.
【學(xué)位授予單位】:華南理工大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2012
【分類號(hào)】:R318

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