Abnormal lung auscultation sound intelligent identification system

Abstract

The invention relates to an abnormal lung auscultation sound intelligent identification system, which comprises a lung auscultation sound acquisition device, a controller, a terminal and a cloud, the lung auscultation sound acquisition device acquires a digital lung auscultation sound signal of a monitored object, and the controller performs digital band-pass filtering on the digital lung auscultation sound signal and converts the digital lung auscultation sound signals into the lung auscultation sound signals in the wav format, the terminal transmits the lung auscultation sound signals in the wav format to the cloud end, the cloud end obtains the lung auscultation sound types of the lung auscultation sound signals in the wav format, and when the lung auscultation sound types are abnormal sounds, the respiratory cycle where the abnormal sounds are located is obtained. And the respiratory cycle of the abnormal sound and the abnormal sound are transmitted to the terminal to be displayed, so that real-time and automatic identification of the breathing sound is realized.

Description

technical field [0001] The invention relates to the field of sound recognition, in particular to an intelligent recognition system for abnormal lung auscultation sounds. Background technique [0002] Normal breathing sounds, abnormal breathing sounds or rales caused by the physiological structure or pathological changes of the trachea, bronchi and alveoli when air enters and exits the airway. Hearing specific types and attributes of abnormal lung auscultation sounds in specific parts is of great significance in the identification of respiratory diseases. [0003] Among them: when air enters and exits the trachea, or forms turbulent flow in the glottis, trachea, and bronchi, or produces normal breath sounds due to changes in alveolar elasticity and airflow vibration, including tracheal breath sounds, bronchial breath sounds sound), bronchoalveolar breath sound and alveolar breath sound. [0004] When the air flow in the alveoli decreases or increases, and the air flow rate ...

AI Technical Summary

Problems solved by technology

[0011] 1. Because there are many kinds of abnormal lung auscultation sounds, specialized medical training and clinical experience are required, and many abnormal sounds can only be completed by clinicians. This method is time-consuming and laborious, and consumes clinical resources

[0012] 2. The medical stethoscope cannot realize the real-time monitoring of the sound, nor can it reproduce the sound at a certain moment. This has brought great problems to the clinical diagnostic evidence storage of abnormal lung auscultation sounds with strong randomness.

[0013] 3. In the treatment of some pulmonary infectious diseases (such as new coronavirus pneumonia), doctors auscultate at close range, which increases the risk of occupational exposure of medical staff

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