Diagnosis method, device and system based on lung sound diagnosis
A diagnostic method and lung sound technology, applied in the field of lung sound diagnosis, can solve the problems of low detection accuracy of lung disease, mixed noise, etc., and achieve the effect of facilitating the treatment of lung disease and improving the accuracy
Inactive Publication Date: 2021-08-17
GUANGDONG POLYTECHNIC NORMAL UNIV
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Problems solved by technology
[0002] People listen to the lungs of the human body through sounders, and judge the corresponding pathology through lung sounds and experience. In related technologies, people judge the corresponding pathology through the sound of the lungs, which is easy to be mixed with some noise, resulting in low accuracy of lung disease detection.
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Embodiment
[0057] see figure 1 , figure 1 It is a schematic flowchart of the diagnosis method based on lung sound diagnosis in the embodiment of the present invention.
[0058] Such as figure 1 Shown, a kind of diagnosis method based on lung sound diagnosis, described method comprises:
[0059] S11: Obtain a lung sound segment;
[0060] In the specific implementation process of the present invention, the lung sound segment can detect the lungs through corresponding detectors, wherein there can be multiple detectors, and multiple detectors are arranged along the edge of the lungs to facilitate the detection of the lungs. edge sound, combined with detectors in the middle of the lungs, to facilitate the construction of the 3D and outer contours of the lungs.
[0061] S12: digitally convert the lung sound segment, and form a trending audio record;
[0062] In the specific implementation process of the present invention, the specific steps may be: establish a schematic diagram of the coo...
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The invention discloses a diagnosis method, device and system based on lung sound diagnosis, and the method comprises the steps: obtaining a lung sound segment; carrying out digital conversion on the lung sound segment, and forming an audio frequency recording graph with a trend; determining repeated initial points and final points in each section of audio frequency recording graph; intercepting an audio recording graph between the initial point and the final point as a test recording graph, and matching the test recording graph with preset pathological recording graphs to determine a coincident wave band of the test recording graph and each preset pathological recording graph; if a plurality of coincident wavebands exist and a plurality of distribution times exist, enabling the plurality of coincident wavebands to be coincident with corresponding subsequent record graphs in the audio frequency record graphs at the same time, wherein the coincident wavebands with the coincidence rate larger than a preset coincidence rate threshold value serve as current pathological record graphs; and determining a corresponding lung disease type according to the current pathological record graph.
Description
technical field [0001] The technical field of lung sound diagnosis related to the present invention, in particular, relates to a diagnosis method, device and system based on lung sound diagnosis. Background technique [0002] People listen to the lungs of the human body through sounders, and judge the corresponding pathology through lung sounds and experience. In related technologies, people judge the corresponding pathology through the sound of the lungs, which is easy to be mixed with some noise, resulting in low accuracy of lung disease detection. . Contents of the invention [0003] The object of the present invention is to overcome the deficiencies of the prior art. The present invention provides a diagnosis method, device and system based on lung sounds, which can detect lung diseases through lung sounds, and through the effective analysis of audio recordings The accuracy of lung sounds is selected to improve the accuracy of lung disease detection, and a variety of ...
Claims
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Login to View More IPC IPC(8): G10L25/66A61B7/04
CPCA61B7/003A61B7/04G10L25/66
Inventor 詹瑾王磊军赵慧民
Owner GUANGDONG POLYTECHNIC NORMAL UNIV