Abnormal heart sound recognition method based on sub-band energy envelope autocorrelation characteristics

A technology of autocorrelation features and identification methods, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve problems such as inability to adapt to noisy environments, dependence, and inability to handle variable-length input signals

Inactive Publication Date: 2015-04-01
HARBIN NORMAL UNIVERSITY
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Problems solved by technology

[0008] In order to solve the above-mentioned problems in heart sound recognition that rely on heart sound segmentation, cannot process variable-length input signals, and cannot adapt to fea

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  • Abnormal heart sound recognition method based on sub-band energy envelope autocorrelation characteristics

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specific Embodiment approach 1

[0041] Specific embodiment one: the abnormal heart sound recognition method based on the sub-band energy envelope autocorrelation feature described in this embodiment is realized by the following steps:

[0042] Step 1. Heart sound preprocessing

[0043] The input heart sound signal is energy-standardized, then down-sampled to 2kHz, and a 6th-order Butterworth filter (20-900Hz) filter is used to band-pass filter the down-sampled heart sound signal to filter out the cut-off Other sounds and noises other than frequencies; Note: Assuming that the sampling frequency of the input heart sound signal is higher than 2kHz, the sampling frequency of the output signal after preprocessing is approximately 2kHz;

[0044] Step 2. Extract the average Shannon energy envelope

[0045] (1) The preprocessed heart sound signal with a sampling frequency of 2kHz is decomposed into 4 levels using the 4th-order Daubechies wavelet to obtain: an approximate coefficient sequence a 4 and four detail co...

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Abstract

The invention provides an abnormal heart sound recognition method based on sub-band energy envelope autocorrelation characteristics and relates to an abnormal heart sound recognition method. The abnormal heart sound recognition method is used for solving the problems in heart sound recognition that heart sound segmentation is depended, longer signals cannot be processed, and adaption to the characteristic extraction and classified recognition in a real noise environment cannot be realized. The method comprises the steps: carrying out energy standardization on input heart sound signals, then, carrying out down-sampling, and carrying out band-pass filtering; respectively computing an autocorrelation sequence of approximate sub-band energy envelope signals and an autocorrelation sequence of detailed sub-band energy envelope signals, and respectively intercepting first M values, which serve as approximate sub-band energy envelope autocorrelation characteristics and approximate sub-band energy envelope autocorrelation characteristics of the input heart sound signals, from the two sequences; respectively constructing two RM-space-to-Re-space scattering mappings, which act on the energy envelope autocorrelation characteristics, according to the energy envelope autocorrelation characteristics; carrying out dimensionality reduction, and then, merging to obtain the energy envelope autocorrelation characteristics of the heart sound signals; carrying out characteristic extraction on test data, and classifying the data by imputing the test data in a classification model. According to the method, a heart sound segmentation process is avoided, and the robustness in a noise environment is improved.

Description

technical field [0001] The invention relates to a method for identifying abnormal heart sounds, and relates to the fields of biological signal identification technology and intelligent information processing. Background technique [0002] According to the statistics of the World Health Organization, cardiovascular disease has become the number one killer threatening human life and health today. About 17 million people died of cardiovascular diseases in 2004, accounting for 29% of all diseases, of which 7.2 million people died of heart disease, and the number and proportion of diseases and deaths caused by heart disease are still increasing year by year. In my country, according to the results published in the "China Cardiovascular Disease Report 2012": the prevalence of cardiovascular disease in my country is on the rise. It is estimated that the number of patients with cardiovascular disease is 290 million, that is, 2 out of every 10 adults. Suffering from cardiovascular di...

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Application Information

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IPC IPC(8): A61B7/04G06F19/00
Inventor 邓世文韩纪庆唐黎明郑铁然郑贵滨张文杰
Owner HARBIN NORMAL UNIVERSITY
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