Heart sound signal segmenting method

Abstract

The invention discloses a heart sound signal segmenting method. The heart sound signal segmenting method is characterized by comprising the following steps: 1, preprocessing; 2, correcting; 3, screening. The heart sound signal segmenting method is simple in steps and convenient to use; through the heart sound signal segmenting method comprising multi-level correcting and screening, right heart sound segments can be obtained, so that a more convenient and quick method is provided for heart rate detection; therefore, the heart sound signal segmenting method is suitable for popularization and application.

Description

technical field [0001] The invention relates to a heart rate detection method, in particular to a heart sound signal segmentation method. Background technique [0002] Heart sound refers to the sound produced by the vibration caused by myocardial contraction, heart valve closing and blood hitting the wall of the ventricle, the wall of the aorta, etc. It can be heard with a stethoscope on a certain part of the chest wall; now it can also be heard with an electronic stethoscope, which is converted into a digital signal and processed for identification. [0003] The heart sound signal is an unstable cycle signal, and it is segmented to obtain a separate cycle. There are two main purposes: 1. To obtain the heart rate; 2. To identify and diagnose with the cycle as the basic unit. Therefore, segmenting heart sound signals has always been a necessary link in heart sound signal processing. [0004] As the first link in the whole process of heart sound signal processing, the qualit...

AI Technical Summary

Problems solved by technology

[0005] 1. When dealing with high-noise signals, a large number of error segments will occur due to missed detection caused by a large noise amplitude and a high threshold value, or a large number of noise envelopes are mixed between the heart sound signal envelopes;

[0006] 2. When processing some disease signals or special signals, errors may occur due to the atypical shape of the heart sound envelope or the unstable amplitude of the heart sound signal;

[0007] 3. Some segments that use autocorrelation have a large amount of calculation, and the calculation time is too long when transplanted to the mobile platform

Therefore, in practical applications, it can only be applied to ideal signals with low noise, or has strict requirements on the environment and equipment collected.

[0008] Correct segmentation cannot be obtained under high noise only by simple correction