Basic Research on the Development of an Automatic Heart Sound Diagnosis System - Analysis of Heart Sounds for Learning Policy and Experiment for the Prototype of the Auscultation Part -

Hirotoshi Hishida, Koichi Tokuuye, Keiko Hishida, Hayato Tojo, Yasuhiro Hishida, Tomomi Koide

A design policy was established for a specific data flow and learning method for the automatic heart-sound diagnosis system under development. The production of each part becomes possible, and auscultation and learning begin. It can be used over clothes as long as it is applied well to the skin surface of the chest. It would be nice to be able to set multiple auscultation positions, but there is a limit to what ordinary people can be asked to do, so this should be considered while having AI learn.

We analyzed normal heart sounds to explore learning strategies. Sounds I and II are considered to be important anchor information sources for identifying other heart sounds. Abnormal heart sounds may not be heard at every beat and the rhythm may be abnormal. AI refers to the multiple beats of heart sounds during auscultation. Heartbeat analysis is a multidimensional information analysis related to time and space, and heart sounds are factored if normal and abnormal heart sounds can be organized based on the score. For pitch that tends to depend on individuals and devices, a relative discussion would be more appropriate.

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