a Department of Biomedical Engineering , Kyungpook National University Hospital , Daegu , Korea.
b Department of Medical & Biological Engineering , Graduate School, Kyungpook National University , Daegu , Korea.
Comput Assist Surg (Abingdon). 2017 Dec;22(sup1):86-92. doi: 10.1080/24699322.2017.1379224. Epub 2017 Sep 25.
The increase in mortality associated with arrhythmia is an inevitable problem of modern society such as westernized eating habits and an increase in stress due to industrialization, and the related social costs are increasing. In this regard, the supply of automatic external defibrillator (AED) used outside hospitals is increasing mainly in public institutions, and AED is a medical practice performed by non-medical personnel. Therefore, studies on arrhythmia detection algorithm to make accurate clinical judgment for proper use are increasing. In this paper, we propose a time domain analysis method to detect arrhythmia in real time and implement AED by porting it to programmable gate array and digital signal processor. The analysis of the phase domain improves the detection rate of R-peak using the differentiated electrocardiogram (ECG) waveform rather than the existing ECG waveform and makes it easy to distinguish the normal ECG from the arrhythmia signal in the phase domain. The proposed algorithm was verified by simulation using Labview and ModelSim, and it was verified that the proposed algorithm works effectively by performing animal experiments using the implemented AED.
与心律失常相关的死亡率增加是现代社会不可避免的问题，例如西方化的饮食习惯和工业化导致的压力增加，相关的社会成本正在增加。在这方面，主要在公共机构中增加了用于医院外的自动体外除颤器 (AED) 的供应，AED 是由非医务人员进行的医疗实践。因此，研究心律失常检测算法以进行准确的临床判断以进行正确使用的研究正在增加。本文提出了一种实时检测心律失常的时域分析方法，并通过将其移植到可编程门阵列和数字信号处理器上来实现 AED。相位域的分析使用差分心电图 (ECG) 波形而不是现有的 ECG 波形来提高 R 波的检测率，并且易于在相位域中区分正常 ECG 和心律失常信号。使用 Labview 和 ModelSim 进行了模拟验证，通过使用实现的 AED 进行动物实验验证了该算法的有效性。
