本文選題：光電容積脈搏波 + 運動偽差��； 參考：《南京郵電大學》2017年碩士論文

【摘要】：隨著人口老齡化現(xiàn)象加劇,同時伴隨著各種疾病在人群中的傳播,人們對自身的健康日益關(guān)注,越來越希望能夠?qū)崟r的了解自身身體狀況,建立健全的網(wǎng)絡(luò)化醫(yī)療監(jiān)測體系顯得尤為重要。血氧飽和度是反應(yīng)人體生理狀態(tài)的重要參數(shù)之一,本文主要研究了針對血氧提取的網(wǎng)絡(luò)化監(jiān)測系統(tǒng)。首先,對峰谷值提取算法進行了介紹,提出了改善的峰谷提取算法——變窗長滑窗法,改進后的滑窗法采用了跳躍式檢測,而不是對每個點都檢測,因此運算量減少了,同時跳躍步長和檢測窗長都是根據(jù)實時心率周期進行更新使得該算法不僅運行效率高而且對變心率有很好的適應(yīng)性,這對之后的運動偽差消除算法和血氧提取奠定了基礎(chǔ)。然后,針對PPG信號中的運動干擾,本文研究了兩種偽差消除算法:第一種為基于ICA與自適應(yīng)濾波的PPG信號運動偽差消除算法,應(yīng)用在需要還原并顯示波形情況下,算法主要內(nèi)容為先從干擾PPG信號中合成可適應(yīng)濾波器需要的參考信號,即結(jié)合周期移動平均和獨立成分分析來分離PPG成分和運動偽差成分,并通過獨立成分選擇算法來提取出PPG成分,接著通過可適應(yīng)濾波器來恢復PPG信號的幅值信息,該算法可有效降低運動偽差的干擾并恢復PPG信號波形形態(tài);第二種為基于統(tǒng)計分析的PPG信號運動偽差檢測與剔除算法,應(yīng)用于干擾劇烈且只需要提取出血氧值而不需顯示波形的情況下,該算法采用設(shè)定閾值的方法對分段后信號的統(tǒng)計量進行檢測,剔除含有干擾的波段,將剩余的優(yōu)質(zhì)波段提取出來,用提取出的優(yōu)質(zhì)波段代替整段信號計算血氧飽和度可以屏蔽掉運動偽差的干擾,從而提高了血氧檢測的精確性。其次,介紹了基于線性回歸的特征值提取算法。驗證了紅光與紅外光PPG信號的相關(guān)性;研究出了參與運算樣本數(shù)在采樣頻率附近時會使R值更加穩(wěn)定的結(jié)論;證明了線性回歸法提取R值比峰谷值法的穩(wěn)定性更高;最后進行了標定試驗,表明了R值與血氧值的高度相關(guān)性。最后,詳細地闡述了整個網(wǎng)絡(luò)化血氧檢測系統(tǒng)的實現(xiàn)方法,介紹了血氧檢測系統(tǒng)的網(wǎng)絡(luò)化以及硬件、軟件構(gòu)成:首先簡要介紹了網(wǎng)絡(luò)化實現(xiàn)的背景意義以及實現(xiàn)方式,然后介紹了硬件系統(tǒng),包括血氧傳感器的選擇、WiFi模塊和采集處理模塊的功能;最后在軟件方面,介紹了基于Android系統(tǒng)編寫的信號分析軟件,主要功能包括數(shù)據(jù)通信,實時波形顯示和生理參數(shù)計算。
[Abstract]:With the increasing aging of the population and the spread of various diseases in the population, people are increasingly concerned about their own health, and more and more hope to be able to understand their physical conditions in real time. The establishment of a sound network medical monitoring system is particularly important. The saturation of blood oxygen is one of the important parameters of the body's physiological state. In this paper, the network monitoring system for blood oxygen extraction is mainly studied. First, the peak valley extraction algorithm is introduced, and the improved peak valley extraction algorithm, the variable window long sliding window method, is proposed. The improved sliding window method uses jumping detection, not the detection of every point, so the computation is reduced, jumping step length and inspection are also taken. The length of the window is updated according to the real time heart rate period. The algorithm not only has high efficiency but also has good adaptability to the rate of change of heart rate. It lays the foundation for the motion artifact elimination algorithm and blood oxygen extraction. Then, two kinds of pseudo difference elimination algorithms are studied in this paper for the motion interference in the PPG signal: the first is based on the ICA The algorithm of PPG signal motion pseudo difference elimination with adaptive filtering is applied in the case of the need to restore and display the waveform. The main content of the algorithm is to synthesize the reference signals that can be adapted to the needs of the filter first from the interference PPG signal, that is to separate the PPG components and the motion artifact combining the periodic moving average and the independent component analysis. The PPG component is extracted by the selection algorithm, and then the amplitude information of the PPG signal is recovered by the adaptive filter. The algorithm can effectively reduce the interference of the motion artifact and restore the form of the PPG signal waveform. The second kinds of PPG signal motion pseudo difference detection and elimination method based on statistical analysis are applied to the intense interference and only need to extract the bleeding. In the case of oxygen value without showing the waveform, the algorithm uses a set threshold method to detect the statistics of the segmented signal, remove the bands containing the interference, extract the remaining high quality band, and use the extracted high quality band instead of the whole signal to calculate the saturation degree of blood oxygen, so that the interference of the motion artifact can be shielded. Thus, the interference of the motion artifact can be shielded. Thus, the interference of the motion artifact can be shielded. Thus, the interference of the motion artifact can be shielded. Thus, the interference of the motion artifact can be shielded and thus the interference of the motion artifact can be shielded. Secondly, the characteristic value extraction algorithm based on linear regression is introduced. The correlation between red light and infrared PPG signal is verified. The conclusion that the R value will be more stable when the number of the operation samples is near the sampling frequency is studied. It is proved that the linear regression method is more stable than the peak valley value method; finally, the R value is more stable; finally, the linear regression method is more stable than the peak valley value method; finally, the result shows that the linear regression method is more stable than the peak valley value method; finally, the results are more stable than the peak valley value method; finally, the results are more stable than the peak valley value method. Finally, the results are proved to be more stable than the peak valley value method. Finally, the results show that the linear regression method is more stable than the peak valley value method; finally, the results are more stable than the peak valley value method; finally, the results are more stable than the peak valley value method. Finally, the results are proved to be more stable than the peak valley value method. The calibration test is carried out, and the high correlation between the R value and the blood oxygen value is shown. Finally, the realization method of the whole network blood oxygen detection system is elaborated in detail. The network of the blood oxygen detection system and the hardware and software are introduced. First, the background meaning and the realization method of the network realization are briefly introduced. Then the hardware system is introduced. It includes the selection of blood oxygen sensor, the function of the WiFi module and the acquisition and processing module. Finally, in the software aspect, it introduces the signal analysis software based on the Android system. The main functions include the data communication, the real-time waveform display and the calculation of the physiological parameters.
【學位授予單位】：南京郵電大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：R318;TP274

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