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Notes PG 2020 : Science (Cochin University of Science & Technology (CUSAT), Kochi)

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Rahul Gnath
Cochin University of Science & Technology (CUSAT), Kochi
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Proceedings of the 8th World Congress on Intelligent Control and Automation July 6-9 2010, Jinan, China A New ECG-based Automated External Defibrillator System Wenguang Han1,Yongjun Li1,Rui Zhang1,Chao Hu1,2 Max Q.-H. Meng1,2 1.Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences 1.Department of Electronic Engineering The Chinese University of Hong Kong 2.Shenzhen Institute of Advanced Integration Technology, Chinese Academy of Science Shatin, N.T. HongKong {chao.hu@siat.ac.cn,max@ee.cuhk.edu.hk} 2.The Chinese University of Hong Kong Shenzhen, China wg.han@siat.ac.cn Abstract Automated External Defibrillators (AED) are basic portable defibrillators that are designed for minimallytrained or untrained non-medical personnel. A microprocessor inside the defibrillation automatically analyzes the patient s heart rhythm and advises the operator whether a shock is needed. Audible and visual prompts will guide the user through the process. AED would advise a shock only to ventricular fibrillation. In this paper, we will present a framework of AED system. There are two crucial components should be elaborately designed, the hardware system and the algorithm of detecting ventricular fibrillation. In this paper, we will present the design of hardware system and a new algorithm which could discriminate ventricular fibrillation (VF) from other unshockable rhythm through the measurement of Sample Entropy (SampEn). We compared the sensitivity, specificity, positive prediction, accuracy of the new algorithm with several earlier VF detection algorithms. The experimental results prove that the new algorithm can be well suited for short data sequences analysis, and reaches an elegant balance between detection time and accuracy. Index Terms Automated External Defibrillator, Sudden Cardiac Arrest, ECG Collection, Algorithm of Defibrillation, Ventricular Fibrillation, Sample Entropy, Bi-phase waveform I. INTRODUCTION Sudden Cardiac Arrest (SCA) has been one of the leading causes that strike people to death without any forebode, while the key cause of SCA is the ventricular fibrillation (VF). In VF, the heart is in an uncoordinated and invalid state. Many victims of SCA could survive if bystanders can apply first aid correctly and immediately while victims have not lost ventricular fibrillation. Electrical defibrillation can recover victim rhythm to normal state, and is well proved as the most effective therapy for cardiac arrest caused by VF or ventricular tachycardia (VT) [1]. A lot of research papers have shown that the delay from collapse to delivery of the first shock is the most important factor of the survival. The possibility of successful defibrillation declines at a rate of 7-10% with each minute of delay [2]. During the defibrillation, a rescue device is required and it is called defibrillation. The defibrillator was invented in 1946, and at first it used 978-1-4244-6712-9/10/$26.00 2010 IEEE 2204 the alternating current (AC) method. In 1950s, a new method of defibrillation with direct current (DC) method was discovered by ZOLL, and this DC method substitutes the old AC method quickly. With the improvement of the defibrillation technology, a major breakthrough came to the introduction of Automated External Defibrillators (AED). In the early days, single-phase waveform defibrillation is the major way for SCA treatment. However, with the progress of defibrillator technology, biphasic waveform [3] defibrillation has become more and more important due to its low power requirement, perfect effect and high livability. Traditional AEDs have lots of disadvantages such as bulky, low velocity of charge and low sensitivity of VF detection. So we need to develop a high stable and efficient AED system. In this paper, we present a framework of AED system in both hardware and algorithm. Firstly, we built an ECG signal collection system. Here, we focus on the design of amplifier and acquisition circuit, which is a key part of the hardware system and even the whole defibrillation system. Secondly, the charging circuit and energy selection circuit are presented, which store some appropriate power in two energy-storey capacitors. Finally, the discharge circuit was designed to release the high voltage waveform to the objective. The detection algorithm is another pivotal component in the whole system. It is used to distinguish the ventricular fibrillation (VF) correctly and promptly from the non VF. If a normal sinus rhythm is misinterpreted as VF that might lead to unnecessary shock delivery, a fatal damage to the patient s heart might occur. Therefore, an appropriate VF detection method must be found for any AED. The sample entropy (SampEn) [4] is used in our algorithm to serve as a descriptor of VF detection. The sample entropy is well suitable for analyzing short and noisy datasets. Compared with other conventional time and frequency domain approaches, as well as nonlinear dynamic methods, this presented algorithm can reach an elegant tradeoff between detection time and accuracy. The simulation and experimental results show that the new algorithm can reach 69.1% sensitivity, 93.6% specificity, 72.9% positive prediction and

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