本文選題：動(dòng)態(tài)心電圖 + 信號(hào)質(zhì)量評(píng)估　； 參考：《東北大學(xué)》2014年碩士論文

【摘要】：作為疾病中的頭號(hào)殺手,心血管疾病已經(jīng)嚴(yán)重威脅到人類(lèi)的生命安全。作為心臟活動(dòng)在體表的綜合反映,心電信號(hào)被廣泛應(yīng)用于心血管疾病的預(yù)防和診斷。常規(guī)心電圖采集的是人體靜臥狀態(tài)下的心電信號(hào),多用于臨床診斷或重癥監(jiān)護(hù)。動(dòng)態(tài)心電圖能夠24小時(shí)不間斷的記錄人體在日�；顒�(dòng)過(guò)程中的心電信號(hào)變化情況,彌補(bǔ)了靜態(tài)心電只能對(duì)短時(shí)和靜止?fàn)顟B(tài)下心電分析的不足,可以有效檢測(cè)突發(fā)性和一過(guò)性的心律失常、心肌缺血等心血管疾病。因此,對(duì)于日常行為下的動(dòng)態(tài)心電的提取和分析具有重要的意義。信號(hào)質(zhì)量評(píng)估就是建立一個(gè)評(píng)價(jià)信號(hào)質(zhì)量好壞和噪聲大小的評(píng)估標(biāo)準(zhǔn),將信號(hào)按質(zhì)量劃分為幾種不同等級(jí)的信號(hào),為下一步的處理和分析做好準(zhǔn)備。它不是直接對(duì)信號(hào)進(jìn)行整形、去噪以及特征提取等處理,而是通過(guò)噪聲的特點(diǎn)或波形特征進(jìn)行具體分析,得到反映信號(hào)質(zhì)量高低的信號(hào)質(zhì)量指數(shù),對(duì)信號(hào)的整體數(shù)據(jù)或者局部數(shù)據(jù)進(jìn)行綜合評(píng)價(jià)。與靜態(tài)心電信號(hào)相比,由于采集過(guò)程中人體處于活動(dòng)狀態(tài),動(dòng)態(tài)心電信號(hào)受到的外界干擾更大,噪聲干擾的變化更為復(fù)雜,嚴(yán)重時(shí)甚至?xí)螠缧碾娦盘?hào)。低質(zhì)量的動(dòng)態(tài)心電信號(hào)不僅加大了信號(hào)處理的難度,而且其處理的結(jié)果往往并不理想,提供的多為無(wú)效甚至錯(cuò)誤的信息,影響疾病的監(jiān)測(cè)和診斷。因此,對(duì)動(dòng)態(tài)心電信號(hào)進(jìn)行信號(hào)質(zhì)量評(píng)估是十分有必要的。本文選取了包絡(luò)差、短時(shí)能量和1-5Hz功率譜密度三種質(zhì)量評(píng)估參數(shù),定義了相應(yīng)的動(dòng)態(tài)心電信號(hào)的質(zhì)量評(píng)估指數(shù),并基于三種質(zhì)量評(píng)估指數(shù)提出了動(dòng)態(tài)心電的綜合質(zhì)量評(píng)估算法,對(duì)采集的動(dòng)態(tài)心電信號(hào)進(jìn)行了質(zhì)量評(píng)估,根據(jù)評(píng)估結(jié)果將信號(hào)分為優(yōu)、良、差三檔,實(shí)現(xiàn)了動(dòng)態(tài)心電信號(hào)的質(zhì)量評(píng)估。此外,采用了墨西哥帽小波極大值法對(duì)濾波后的動(dòng)態(tài)心電信號(hào)進(jìn)行R波提取,對(duì)心電信號(hào)質(zhì)量評(píng)估的結(jié)果進(jìn)行了驗(yàn)證,并根據(jù)提取的R波結(jié)果進(jìn)行了心率分析。本文提出的基于信號(hào)質(zhì)量評(píng)估的動(dòng)態(tài)心電分析系統(tǒng)主要研究了心電信號(hào)的質(zhì)量評(píng)估和R波檢測(cè),并計(jì)算了相應(yīng)的心率。
[Abstract]:As the leading killer of diseases, cardiovascular disease has seriously threatened the safety of human life. As a comprehensive reflection of cardiac activity on the body surface, ECG signal is widely used in the prevention and diagnosis of cardiovascular disease. Electrocardiogram (ECG) is usually used in clinical diagnosis or intensive care. Dynamic electrocardiogram (ECG) can record the changes of ECG in daily activities 24 hours, which makes up for the deficiency that static ECG can only be used to analyze ECG in a short time and in a static state. Can effectively detect sudden and transient arrhythmia, myocardial ischemia and other cardiovascular diseases. Therefore, it is of great significance to extract and analyze dynamic ECG in daily behavior. Signal quality assessment is to establish an evaluation standard of signal quality and noise size, and divide the signal into several kinds of signals according to the quality of the signal, so as to prepare for the next step of processing and analysis. It is not a direct processing of signal shaping, denoising and feature extraction, but through the specific analysis of the characteristics of noise or waveform, the signal quality index reflecting the signal quality is obtained. Comprehensive evaluation of the overall or local data of the signal. Compared with the static ECG signal, the dynamic ECG signal is more disturbed by the outside world and the change of the noise interference is more complex because the human body is in the active state during the acquisition process, and even annihilates the ECG signal when it is serious. The low quality dynamic ECG signal not only increases the difficulty of signal processing, but also the result of processing is often not ideal. The information provided is mostly invalid or wrong, which affects the monitoring and diagnosis of disease. Therefore, it is necessary to evaluate the signal quality of dynamic ECG signal. In this paper, three quality evaluation parameters, envelope difference, short time energy and 1-5Hz power spectral density, are selected, and the corresponding quality evaluation index of dynamic ECG signal is defined. Based on the three quality evaluation indexes, a comprehensive quality evaluation algorithm for dynamic ECG is proposed. The quality evaluation of the collected dynamic ECG signal is carried out. According to the evaluation results, the signal is divided into three parts: excellent, good and bad, and the quality evaluation of the dynamic ECG signal is realized. In addition, the method of maximum value of Mexican hat wavelet is used to extract R wave of filtered dynamic ECG signal, and the evaluation result of ECG signal quality is verified, and heart rate analysis is carried out according to the obtained result of R wave. A dynamic ECG analysis system based on signal quality assessment is proposed in this paper, which mainly studies the quality assessment and R wave detection of ECG signals, and calculates the corresponding heart rate.
【學(xué)位授予單位】：東北大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類(lèi)號(hào)】：R540.4;TN911.7

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