Detecting Algorithm for AF and SAS Precaution System via Separation Biosignals

Kenji Hashiodani, Shinichi Takada, Yohei Fukumizu, Hironori Yamauchi, Yoshimasa Kurumi, and Tohru Tani


Biosignals, Sound separation, Arterial sclerosis, Atrial fibrillation


Sounds in the human body (biosignals) have been widely researched. Specifically, separating intended sounds from biosignals has been researched actively to detect circulatory conditions. Among circulatory conditions, arterial sclerosis (AS), atrial fibrillation (AF), and sleep apnea syndrome (SAS) are dangerous diseases because these diseases are often not noticed in daily life. Therefore, many patients do not notice them and may die suddenly. However, most studies of biosignals only separate an intended sound from biosignals. These methods are insufficient for detecting circulatory conditions because to detect it, we have to analyze relatively heart, breath, and bloodstream sounds. Therefore, we introduce a method to separate heart, breath, and bloodstream sounds from biosignals at one time and detect warning signs of AF and SAS. And also, this method leads more robust results than our existing methods. Moreover, we can quickly and easily detect warning signs of AF and SAS by using this method.

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