Method for positioning and segmenting heart sound signal

Abstract

The invention relates to a method for positioning and segmenting heart sound signal and a device. The device comprises a preprocessing unit, an initial state determination unit, a calculation unit, afirst search unit, a second search unit and a segmentation unit, wherein the preprocessing unit comprises a filter functional module which is used for preprocessing the heart sound signal and filtering noise out of band; the initial state determination unit is used for determining a start cycle, the maximum cycle and an initial point; the calculation unit is used for calculating correlation coefficient of signals in two adjacent calculation cycles; the first search unit is used for searching correlation coefficient extremum 1 in the correlation coefficient; the second search unit is used for search correlation coefficient extremum 2 in the correlation coefficient extremum 1; and the segmentation unit is used for segmenting the heart sound signal. In the invention, the method for positioning and segmenting the heart sound signal and the device use a self-correlated coefficient method to position automatically and accurately.

Description

technical field [0001] The invention relates to the field of heart sound signal processing, in particular to a method for locating the period of the heart sound signal. Background technique [0002] The development and utilization of advanced auxiliary diagnostic instruments such as ultrasonic Doppler and ECG (Electrocardiogram) make the utilization of heart sound signals neglected. However, ultrasonic Doppler is expensive and not easy to popularize; although ECG signal is more effective for the diagnosis of diseases related to blood circulation and blood tissue, it cannot effectively reflect the pathological information related to organic heart disease. [0003] The heart sound signal contains rich information that can reflect the normal or pathological nature of the heart. The normal heart sound includes four heart sounds: the first heart sound (S1), the second heart sound (S2), the third heart sound (S3) and the fourth heart sound (S4). Among them, S1 and S2 are audible ...

AI Technical Summary

Problems solved by technology

[0007] The disadvantages of the traditional heart sound signal segmentation algorithm are: first, the ECG signal or carotid wave signal is required as a reference, which increases the burden on software and hardware; second, the heart sound signal itself is a typical non-stationary signal, and the traditional The heart sound segmentation algorithm treats the heart sound signal as a stable signal, and uses its time domain and frequency domain characteristics for positioning. This approach will produce large errors; high and sensitive to noise

[0008] Disadvantages of ECG signal segmentation technology: First, the algorithm is complex and time-consuming

Second, noise has a greater impact on the segmentation effect; third, only the approximate positions of s1 and s2 can be located, and the information of the duration of s1 and s2 is lost, and the time range of systole and diastole cannot be judged, let alone Accurate positioning of heart sound signal cycle

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