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DETECTING ALGORITHM FOR AF AND SAS PRECAUTION SYSTEM VIA SEPARATION BIOSIGNALS

机译:通过分离基本原理检测AF和SAS预防系统的算法

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摘要

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.
机译:人体中的声音(生物信号)已被广泛研究。具体而言,已经积极研究了从生物信号中分离预期声音以检测循环系统状况。在循环系统疾病中,动脉硬化(AS),房颤(AF)和睡眠呼吸暂停综合症(SAS)是危险疾病,因为这些疾病在日常生活中通常不被发现。因此,许多患者没有注意到它们,并且可能突然死亡。然而,大多数对生物信号的研究仅将预期声音与生物信号分开。这些方法不足以检测循环系统状况,因为要检测到循环系统状况,我们必须分析相对的心脏,呼吸和血流声音。因此,我们介绍了一种方法,可以将生物信号中的心脏,呼吸和血液声音一次分离出来,并检测AF和SAS的警告信号。而且,与我们现有的方法相比,此方法可带来更可靠的结果。此外,通过这种方法,我们可以快速轻松地检测到AF和SAS的警告信号。

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