本文選題：肥厚型心肌病 + 心音��； 參考：《西華大學》2017年碩士論文

【摘要】：隨著當今社會醫(yī)療知識的普及,越來越多的病癥已經(jīng)被人們所熟悉。肥厚型心肌病(Hypertrophic Cardiomyopathy,HCM)作為一種高遺傳性、高發(fā)病率、高危險性的病癥,是誘發(fā)猝死、心力衰竭和房顫的重要因素,多年來受到了國內(nèi)外的廣泛關(guān)注,越來越多的醫(yī)療工作者和科研工作者投入到HCM的診斷與治療研究中。由于受醫(yī)療水平的限制,我國HCM患者的篩查率并不高,絕大多數(shù)患者只有在發(fā)病時才會到醫(yī)院就診,錯過早期干預的黃金期,導致病情加重,為家庭和社會造成了沉重負擔。隨著病情加重,患者會出現(xiàn)胸悶、氣短、暈厥甚至猝死等癥狀。因此,建立健全HCM的早期診斷體系對于患者病情的控制具有十分重要的現(xiàn)實意義。心音包含了心臟瓣膜、各器官功能狀態(tài)的基本信息,已經(jīng)被廣泛應用于心血管疾病的診斷與治療研究當中。經(jīng)過臨床聽診顯示,左室流出道梗阻的HCM患者可能出現(xiàn)第二心音分裂,更為嚴重者會出現(xiàn)因左室流出道湍流和二尖瓣返流等原因引起的收縮期雜音。因此,將心音的分析研究運用到HCM的診斷與治療具有重要的臨床價值,并且對HCM的篩查甚至人體健康普查具有重要意義。本文在研究室和第四軍醫(yī)大學第一附屬醫(yī)院西京醫(yī)院肥厚型心肌病診治與遺傳咨詢中心前期研究工作成果的基礎(chǔ)上,將心音的檢測分析研究應用于HCM的診斷研究當中,主要完成了以下工作:(1)HCM心音信號采集利用美國BIOPAC公司生產(chǎn)的16導生理記錄儀在可視化環(huán)境下,實時采集并同步顯示心音信號,不僅操作簡單而且數(shù)據(jù)采集的質(zhì)量較高。通過此系統(tǒng)采集了年齡在20~70歲的24名正常人(男15名,女9名)和30名HCM患者(男17名,女13名)三尖瓣、二尖瓣和主動脈瓣第二聽診區(qū)三個部位的心音數(shù)據(jù),并通過篩選剔除低質(zhì)量的心音,最終選擇57例正常心音數(shù)據(jù)(24名正常人)和81例HCM心音數(shù)據(jù)(30名HCM患者)用于本研究中。(2)HCM心音信號預處理臨床HCM心音數(shù)據(jù)采集過程中不可避免的會受到儀器內(nèi)部結(jié)構(gòu)和外部環(huán)境的影響,從而產(chǎn)生額外噪聲。因此,本文首先分析了心音信號中噪聲組成部分及主要來源,然后描述了心音信號的降噪方法和過程,根據(jù)各類噪聲的性質(zhì),利用50Hz工頻陷波器、數(shù)字帶通濾波器和自適應小波閾值降噪法,消除心音中的工頻干擾和額外噪聲,以提高心音信號的信噪比,獲得了較好的降噪效果。(3)HCM心音信號特征提取本文通過時域和頻域?qū)CM心音信號進行特征提取,首先討論了基于希爾伯特變換(HT)、歸一化平均香農(nóng)能量(NASE)、單自由度模型(SDOF)、變頻同態(tài)濾波(FMH)四種方法對本文研究數(shù)據(jù)的特征波形提取效果,通過對比分析,FMH算法具有更好的特征波形提取效果。在特征波形提取后,利用局部峰值檢測和自適應雙閾值門限對HCM心音信號進行分段定位,定義了信號時域時間特征參數(shù)、時域能量特征參數(shù);最后結(jié)合小波分析,利用小波包提取頻域頻帶能量特征參數(shù),研究了正常心音和HCM心音在VLF、LF、MF和HF頻段上的能量分布,為后續(xù)臨床HCM心音的特征研究奠定了基礎(chǔ)。(4)臨床HCM心音時頻特征分析研究利用前文中的降噪方法和特征波形提取方法對篩選后的HCM心音提取特征參數(shù),在時域和頻域通過統(tǒng)計分析研究了HCM的心音特征。通過正常人與HCM的心音特征參數(shù)對比分析,討論了HCM第一心音、第二心音的特征;HCM心音中雜音出現(xiàn)的部位、時間、強度以及頻帶范圍;通過對靜息狀態(tài)下梗阻和非梗阻性HCM心音的時域能量和頻域小波包能量頻帶參數(shù)對比分析,可得雜音的性質(zhì),從而初步判斷左室流出道梗阻情況。這對于HCM的診斷有十分重要的臨床價值。綜上所述:本文在臨床HCM心音數(shù)據(jù)采集、處理及分析上進行了全面深入的研究,通過臨床HCM心音特征分析,初步描述了HCM患者第一心音、第二心音特征及雜音特征,同時結(jié)合臨床癥狀進行了初步分析,為基于心音分析的HCM診斷研究奠定了臨床基礎(chǔ)。但由于數(shù)據(jù)量相對較少,只是進行初步分析。因此,今后的工作重點將是建立臨床HCM心音數(shù)據(jù)庫,提出更加有效的HCM心音分析方法,為建立完善的臨床HCM診斷體系而努力。
[Abstract]:With the popularization of medical knowledge in today's society, more and more diseases have become familiar. Hypertrophic Cardiomyopathy (HCM), as a high hereditary, high incidence and high risk, is an important factor in inducing sudden death, heart failure and atrial fibrillation, and has been widely concerned at home and abroad for many years. The more medical workers and researchers have put into the research of the diagnosis and treatment of HCM. Because of the limitation of medical level, the screening rate of HCM patients in China is not high. The overwhelming majority of patients only go to the hospital when they are sick, miss the golden period of early intervention, cause the aggravation of the disease and cause a heavy burden to the family and the society. As the condition worsens, the patient will have symptoms such as chest tightness, shortness of breath, syncope and even sudden death. Therefore, it is of great practical significance to establish and improve the early diagnosis system of HCM for the control of the patient's condition. The heart sound contains the basic information of the heart valve and the functional state of each organ, which has been widely used in the diagnosis and treatment of cardiovascular disease. In the clinical study, the HCM patients with left ventricular outflow tract obstruction may have second heart sound mites after clinical auscultation, and the more serious are the systolic murmur caused by the left ventricular outflow tract turbulence and mitral regurgitation. Therefore, the analysis and study of the heart sound are of important clinical value in the diagnosis and treatment of HCM. And it is of great significance for the screening of HCM and the general survey of human health. On the basis of the results of the previous research work of the diagnosis and treatment and genetic counseling center of the hypertrophic cardiomyopathy in Xijing Hospital, the First Affiliated Hospital of The Fourth Military Medical University, this paper applies the detection and analysis of heart sound to the diagnosis and research of HCM. Work: (1) HCM heart sound signal acquisition and use of the 16 guide physiological recorder produced by American BIOPAC company in visual environment, real-time collection and synchronization display of heart sound signals, not only simple operation but also the high quality of data acquisition. Through this system, 24 normal people (15 men, 9 women) and 30 HCM patients (male 17) aged 20~70 years old (male 17) were collected. The heart sound data of three parts of the three cusp, mitral and aortic valve in second auscultation areas, and the selection and elimination of low quality heart sound, and the final selection of 57 normal heart sound data (24 normal persons) and 81 HCM heart sound data (30 HCM patients) were used in this study. (2) HCM heart sound signal preprocessing clinical HCM heart sound data acquisition process It is unavoidable to be influenced by the internal structure of the instrument and the external environment, thus producing extra noise. Therefore, this paper first analyzes the components and main sources of the noise in the heart sound signal, and then describes the noise reduction methods and processes of the heart sound signals. According to the properties of all kinds of noise, the 50Hz power frequency trap and digital bandpass filter are used. And adaptive wavelet threshold denoising method to eliminate the power frequency interference and extra noise in the heart sound to improve the signal to noise ratio of the heart sound signal, and get a better noise reduction effect. (3) the feature extraction of HCM heart sound signal is extracted by the feature extraction of the HCM heart sound signal in the time domain and frequency domain. The first discussion is based on the Hilbert transform (HT) and the normalized average. Shannon energy (NASE), single degree of freedom model (SDOF) and frequency conversion homomorphic filter (FMH) are used to study the feature waveform extraction effect of this paper. Through comparison and analysis, the FMH algorithm has a better feature extraction effect. After the extraction of the characteristic waveform, the local peak detection and adaptive double threshold threshold are used to divide the HCM heart sound signal. Segment location, the time domain time characteristic parameters and time domain energy characteristic parameters are defined. Finally, the energy distribution of frequency band energy in frequency domain is extracted with wavelet packet, and the energy distribution of normal heart sound and HCM heart sound in VLF, LF, MF and HF frequency bands is studied. (4) clinical HCM heart. The characteristic analysis of sound time frequency characteristics is used to extract the characteristic parameters of the HCM heart sound after the noise reduction and characteristic waveform extraction. In the time and frequency domain, the heart sound characteristics of HCM are studied by the statistical analysis in the time domain and frequency domain. The characteristics of the first heart sound of HCM, the second heart sound, and the HCM heart are discussed by the comparison and analysis of the heart sound characteristic parameters of the normal people and the HCM. The location, time, intensity, and frequency range of the sound in the sound, by comparing the time domain energy of the resting state with the non obstructive HCM heart sound and the wavelet packet energy frequency band parameters in the frequency domain, the properties of the murmurs can be obtained, thus the obstruction of the left ventricular outflow tract is preliminarily judged. This is of great clinical value for the diagnosis of HCM. To sum up, this paper makes a comprehensive and in-depth study on the clinical HCM heart sound data acquisition, processing and analysis. Through the analysis of the clinical HCM heart sound characteristics, the first heart sound, second heart sound characteristics and the murmurs characteristics of the HCM patients are preliminarily described, and the preliminary analysis of the clinical symptoms is carried out, which is established for the HCM diagnosis based on the heart sound analysis. The clinical basis. But due to the relatively small amount of data, it is only a preliminary analysis. Therefore, the focus of the future work will be to establish a clinical HCM heart sound database, and put forward a more effective method of HCM heart sound analysis, so as to establish a perfect clinical HCM diagnosis system.

【學位授予單位】：西華大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：R542.2;TN911.7

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