Classification and identification method and device for cardiechema signals

A technology of signal classification and recognition method, applied in speech recognition, speech analysis, medical science and other directions, can solve the problems of slow classification and recognition, complicated operation and recognition process, and inconvenient to carry the system, so as to simplify the feature extraction and calculation process. , Simple structure, strong anti-interference ability

Inactive Publication Date: 2010-12-29
CHONGQING UNIV
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Problems solved by technology

These research results have broadened the research ideas of heart sound classification, but these methods need to extract a variety of heart sound parameters as heart sound classification standards, and extracting too many heart sound parameters makes the extraction, calculation, and recognition proces

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  • Classification and identification method and device for cardiechema signals
  • Classification and identification method and device for cardiechema signals
  • Classification and identification method and device for cardiechema signals

Examples

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Embodiment

[0088] In this example, normal heart sound signals and 8 common pathological heart sound signals were selected as template signals. A total of 65 samples were collected, including: 5 normal heart sounds, 5 mitral regurgitation heart sounds, and 17 second Heart sounds of cusp stenosis, 5 cases of aortic regurgitation heart sounds, 5 cases of aortic valve stenosis heart sounds, 5 cases of pulmonary valve stenosis heart sounds, 6 cases of ventricular septal defect heart sounds, 8 cases of premature heart sounds, and 9 cases of split heart sounds.

[0089] In the acquisition process, the DSP processor first uses the coif3 wavelet to decompose and reconstruct the heart sound signal in 7 layers to obtain subband signals of different frequency bands for easy observation. After wavelet denoising, many useless components and interferences in the heart sound signal are removed, and the useful components of the signal are retained. The denoised heart sound is extracted with feature parameter...

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Abstract

The invention provides a classification and identification method for cardiechema signals and a classification and identification device for cardiechema signals by applying the method. In the method, the likelihood of GMM template features and Mel-frequency cepstrum coefficients of the cardiechema signals to be detected is used as the matching standard to perform classification and identification, so the method has the advantages of few extracted parameters, simplified processes of feature extraction and calculation, strong anti-interference capacity and high accuracy and efficiency of the classification and identification. The classification and identification device for the cardiechema signals is designed by taking the method as the total idea, adopts a DSP processor as a processing core, and has a simple, exquisite, light and convenient structure, can be carried on for measurement, is a low-cost and non-invasive cardiechema detection device, and is helpful for discovering and treating cardiac diseases in time.

Description

Technical field [0001] The invention belongs to the technical field of intelligent control applications, and particularly relates to a heart sound signal classification and recognition method and a device thereof, which provide an effective tool for automatic classification of related heart diseases. Background technique [0002] Heart sounds contain a lot of physiological and pathological information about the heart. Before cardiovascular disease has developed enough to produce clinical and pathological changes, the murmurs and aberrations in heart sounds are of great significance to the diagnosis of heart valve disease and certain congenital heart diseases. Heart sound auscultation is an important way to check the integrity of the heart function. A professionally trained physician can use a stethoscope to roughly diagnose whether the patient has heart disease. However, heart auscultation is easily affected by the doctor’s experience and the level of auscultation. Restrictions,...

Claims

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Application Information

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IPC IPC(8): G10L15/06A61B8/00G10L17/26G10L25/24
Inventor 郭兴明段赟吴文竹
Owner CHONGQING UNIV
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