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Method and system for detecting abnormal heart sounds

A technology of heart sounds and abnormalities, applied in applications, diagnostic recording/measurement, medical science, etc.

Pending Publication Date: 2019-12-10
ROBERT BOSCH GMBH
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  • Abstract
  • Description
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Problems solved by technology

However, effective cardiac auscultation requires trained physicians, a resource that is especially limited in low-income countries of the world

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  • Method and system for detecting abnormal heart sounds
  • Method and system for detecting abnormal heart sounds
  • Method and system for detecting abnormal heart sounds

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Embodiment Construction

[0016] For the purpose of promoting an understanding of the principles of the disclosure, reference will now be made to the embodiments illustrated in the accompanying drawings and described in the following written description. It should be understood that no limitation of the scope of the present disclosure is thereby intended. It is also to be understood that this disclosure includes any alterations and modifications to the illustrated embodiments, and further applications of the principles of the disclosure that would normally occur to one skilled in the art to which this disclosure pertains.

[0017] Abnormal Heart Sound Detection System

[0018] refer to figure 1 and 2A - 2B, depicts an exemplary embodiment of an abnormal heart sound detection system 10 for detecting abnormal heart sounds of a person 12 . Abnormal heart sound detection system 10 is configured to monitor the acoustic properties of the heart sounds of person 12 and notify the user in the event of a he...

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Abstract

The present invention discloses a method and system for detecting abnormal heart sounds in a phonocardiogram of a person. At least one segmented cardiac cycle of the phonocardiogram is received at a processor. The processor decomposes the segmented cardiac cycle into a plurality of frequency sub-bands using a first convolutional neural network having, in particular a plurality of time-convolutionlayers (tConv). The kernel weights of each time-convolution layer are learned in a training process such that the time-convolution layers identify pathologically significant frequency sub-bands. The processor determines a probability that the segmented cardiac cycle contains an abnormal heart sound based on the plurality of frequency sub-band segments using at least one further neural network. Insome embodiments, the time-convolution layers are configured to have a linear phase response (LP-tConv) or a zero phase response (ZP-tConv).

Description

[0001] This application claims priority to US Provisional Application Serial No. 62 / 680,404, filed June 4, 2018, the disclosure of which is incorporated herein by reference in its entirety. technical field [0002] The devices and methods disclosed in this document relate to detecting abnormal heart sounds, and more particularly to automatic detection of abnormal heart sounds using neural networks. Background technique [0003] Unless otherwise indicated herein, the materials described in this section are not prior art to the claims in this application and are not admitted to be prior art by inclusion in this section. [0004] Cardiovascular disease (CVD) causes approximately 17.7 million deaths annually, equivalent to 31% of global deaths. Cardiac auscultation is the most popular non-invasive and cost-effective procedure for early diagnosis of various heart diseases. However, effective cardiac auscultation requires trained physicians, a resource that is especially limited ...

Claims

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Application Information

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IPC IPC(8): A61B7/02
CPCA61B7/02A61B7/04A61B5/7264
Inventor S.加法扎德甘冯哲A.I.胡马云T.哈桑
Owner ROBERT BOSCH GMBH
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