Heart Failure ; diagnosis ; therapy ; Humans ; Phonocardiography ; methods

In this paper, an improved empirical mode decomposition (EMD) algorithm for phonocardiogram (PCG) signal de-noising is proposed. Based on PCG signal processing theory, the S1/S2 components can be extracted by combining the improved EMD-Wavelet algorithm and Shannon energy envelope algorithm. Firstly, by applying EMD-Wavelet algorithm for pre-processing, the PCG signal was well filtered. Then, the filtered PCG signal was saved and applied in the following processing steps. Secondly, time domain features, frequency domain features and energy envelope of the each intrinsic mode function's (IMF) were computed. Based on the time frequency domain features of PCG's IMF components which were extracted from the EMD algorithm and energy envelope of the PCG, the S1/S2 components were pinpointed accurately. Meanwhile, a detecting fixed method, which was based on the time domain processing, was proposed to amend the detection results. Finally, to test the performance of the algorithm proposed in this paper, a series of experiments was contrived. The experiments with thirty samples were tested for validating the effectiveness of the new method. Results of test experiments revealed that the accuracy for recognizing S1/S2 components was as high as 99.75%. Comparing the results of the method proposed in this paper with those of traditional algorithm, the detection accuracy was increased by 5.56%. The detection results showed that the algorithm described in this paper was effective and accurate. The work described in this paper will be utilized in the further studying on identity recognition.
Algorithms ; Humans ; Phonocardiography ; Signal Processing, Computer-Assisted

According to the valvular theory, the vibrations affected by the mitral and tricuspid valves closure in early systole produce the first heart sound (S1). S1 usually includes many frequency components. In this paper, a method using the multi-resolution analysis of wavelet transformation is recommended for detecting the frequency range of S1. First, S1 was decomposed into different levels on frequency. Then the normalized Shannon energy of the different levels was calculated. The level containing the maximum energy is the major components' level of S1. The frequency range of this level is the major frequency range of S1. The frequency range of S1 was successfully detected by the method.
Algorithms ; Heart Sounds ; Humans ; Phonocardiography ; methods ; Signal Processing, Computer-Assisted

BACKGROUND: The rate of rise of left ventricular(LV) systolic pressure, dp/kt, and the peak ejection rate(PER) of LV may be more accurate indices for assessing LV systolic function than ejection fraction(EF). Both can be easily obtained by noninvasive methods, M-mode echo/phonocardiography and automated border detection(ABD) echocardiography, respectively. Mean dp/dt by M-mode echo/phonocardiography and PER by ABD echocardiography were compared with mean dp/dt by Doppler echocardiography. METHODS: Twenty-one adult patients who had normal sinus rhythm, mitral regurgitant signals by continuous wave Doppler echocardiography and an apical 4 chamber view of LV in which at least 75% of the endocardium was clearly visualized were selected for our study. The off-line estimation of LV end-diastolic volume (1) were performed by the method of disc, after manually tracing the endocardial border on the apical 4 chamber view and EF was calculated. M-mode echocardiography of the aortive valve and phonocardiography were simultaneously recorded on the strip chart to measure the isovolumic contraction time(dtM). A blood pressure (2) and LV end-diasolic pressure(LVEDP) was assigned 20mmHg in patients with Q wave myocardial infarction or EF< or =40% and 10mmHg in others. The mean dp/dtM during isovolumic contraction time was calculated as (aortic diastolic pressure-LVEDP)/dtM and was compared with the Doppler-derived mean rate of LV pressure rise(dp/dtDoppler) over the time period between velocities of 1 and 3m/sec on the ascending slope of the Doppler velocity spectrum. ABD system was used to measure the changes in LV volume and PER on the apical four chamber view. PER was compared with mean dp/dtDoppler. RESULTS: Mean dp/dtM positively correlated with mean dp/dtDoppler(r=0.73, p<0.001), but the limits of agreement between two methods were somewhat wide(-659-937mmHg/sec). PER also positively correlated with dp/dtDoppler and EF(r=0.73, p<0.001 ; r=0.80, p<0.001). CONCLUSIONS: Mean dp/dtM by M-mode echo/phomocardiography and PER by ABD echocardiography may be useful indices for assessing LV systolic function.
Adult ; Blood Pressure ; Echocardiography* ; Echocardiography, Doppler ; Endocardium ; Humans ; Myocardial Infarction ; Phonocardiography

Recently, the proportion of cardiovascular disease as a cause of death in diabetics is in ever increasing tendency. Present study is designed to evaluate the change of myocardial performance by the effect of microangiopathy of diabetics. The measurements of systolic time intervals were obtained from simultaneous high speed recordings(100mm/sec) of electrocardiography, phonocardiography, and carotid pulse tracing in diabetics(male 26, female 31). 1. As the diabetic retinopathy got severe, shortening of LVET and prologation of PEP were noted, but QS2 showed no significant change. 2. PEP/LVET ratio fo diabetics without diabetic retinopathy was significantly higher than that of normal control(p<0.01). 3. PEP/LVET ratio of diabetics with diastolic blood pressure under 95mmHg was significantly higher than that of normal control group(p<0.01), and PEP/LVET ratio of diabetics with diastolic blood pressure over 96mmHg was significantly higher than that of normal control and that of diabetics with diastolic blood pressure under 95mmHg(p<0.01). 4. PEP/LVET ratio of diabetics with proliperative retinopathy was significantly higher than that of normal control and that of diabetics with mild diabetic retinopathy(p<0.01), but this result was not conclusive because of the small case number.
Blood Pressure ; Cardiovascular Diseases ; Cause of Death ; Diabetic Retinopathy ; Electrocardiography ; Female ; Humans ; Phonocardiography ; Systole*

OBJECTIVEExtraction of cepstral coefficients combined with Gaussian Mixture Model (GMM) is used to propose a biometric method based on heart sound signal.

METHODSFirstly, the original heart sounds signal was preprocessed by wavelet denoising. Then, Linear Prediction Cepstral Coefficients (LPCC) and Mel Frequency Cepstral Coefficients (MFCC) are compared to extract representative features and develops hidden Markov model (HMM) for signal classification. At last, the experiment collects 100 heart sounds from 50 people to test the proposed algorithm.

RESULTSThe comparative experiments prove that LPCC is more suitable than MFCC for heart sound biometric, and by wavelet denoising in each piece of heart sound signal, the system achieves higher recognition rate than traditional GMM.

CONCLUSIONThose results show that this method can effectively improve the recognition performance of the system and achieve a satisfactory effect.

Algorithms ; Biometry ; Heart ; physiology ; Humans ; Markov Chains ; Models, Biological ; Phonocardiography ; methods ; Wavelet Analysis

In this paper is described a comprehensive system, which can acquire heart sounds and electrocardiogram (ECG) in parallel, synchronize the display; and play of heart sound and make auscultation and check phonocardiogram to tie in. The hardware system with C8051F340 as the core acquires the heart sound and ECG synchronously, and then sends them to indicators, respectively. Heart sounds are displayed and played simultaneously by controlling the moment of writing to indicator and sound output device. In clinical testing, heart sounds can be successfully located with ECG and real-time played.
Electrocardiography ; instrumentation ; methods ; Humans ; Monitoring, Physiologic ; Phonocardiography ; instrumentation ; methods ; Signal Processing, Computer-Assisted

OBJECTIVETo investigate the change of cardiac reserve during abnormal pregnancy and explore its evaluation methods.

METHODSTotally 96 women with abnormal pregnancies (AP group), 356 women with normal pregnancies (NP group), and 100 women of childbearing age (CBA group) were monitored by the exercise cardiac contractility monitor (ECCM). Phonocardiogram of participants at resting status was recorded by ECCM. The amplitude of first heart sound (S1), the amplitude of second heart sound (S2), cardiac cycle, diastolic duration (D), and systolic duration (S) were detected and then the S1/S2 ratio,the D/S ratio, and heart rate (HR) were calculated.

RESULTSCompared with the CBA group, S1/S2 ratio and HR were significantly higher and D/S was significantly lower in both AP group and NP group (all P<0.001). Compared with the NP group, S1/S2 ratio and HR were significantly higher in AP group and D/S was significnatly lower (all P<0.001). A D/S ratio less than 1.1 or S1/S2 ratio higher than 1.8 was associated with higher risk of poor pregnancy outcomes. Among four common pregnancy-associated abnormalities, the level of cardiac reserve was lowest in eclampsia, followed by twins, gestational diabetes mellitus, and gestational hypertension.

CONCLUSIONSCardiac reserve is mobilized during pregnancy, and is especially during the abnormal pregnancies due to the heavy cardiac burden. S1/S2 ratio, D/S ratio, and HR are useful in evaluating the cardiac reserve during abnormal pregnancy.

Adult ; Female ; Heart ; physiopathology ; Humans ; Phonocardiography ; Pregnancy ; Pregnancy Complications ; physiopathology ; Pregnancy Outcome ; Young Adult

In order to discriminate normal and abnormal heart sounds accurately and effectively, a new method is proposed to analyze heart sounds, namely heart sound characteristic waveform (HSCW) method. Digital stethoscope is used to collect heart sound signals. The recorded data are transmitted to a computer by USB interface for analysis based on HSCW, which is extracted from an analytical model of single degree-of-freedom (SDOF). Furthermore, a case study on the normal and abnormal cardiac sounds is demonstrated to validate the usefulness and efficiency of the proposed HSCW method. Besides, in order to test the accuracy of discriminating normal and abnormal heart sounds, 40 normal and 20 abnormal heart sounds are collected and analyzed, the accuracy performances are achieved by 92.5% and 95.0%, respectively.
Algorithms ; Heart Auscultation ; instrumentation ; methods ; Heart Sounds ; physiology ; Humans ; Phonocardiography ; methods ; Signal Processing, Computer-Assisted

Independent component analysis (ICA) is a novel method developed in recent years for Blind Source Separation. In this paper, the phonocardiogram (PCG) was separated into three components by applying ICA. The basic principle of ICA was introduced in this paper. A fast and robust fixed-point algorithm for ICA was used to analyze PCG signals in this study. The experiments showed that ICA could separate the components of heart sounds from PCG signals successfully.
Algorithms ; Heart Sounds ; Humans ; Phonocardiography ; methods ; Principal Component Analysis ; Signal Processing, Computer-Assisted