Design Of Automatic External Defibrillator And Research On Key Technology

Sudden cardiac death(SCD), commonly known as cardiac arrest, is one of the important diseases that is harmful to human health. The 80 to 90 percent among the SCD is caused by ventricular fibrillation(VF). At present, defibrillation is the only effective way to prevent cardiac ventricular fibrillation leading to sudden death. The operation steps of traditional defibrillation apparatus are very complex, the defibrillation opportunity, discharge capacity and some other factors are also judged and operated by professional doctor under the condition of the hospital as well as according to the measured ecg waveform. Intelligent automated external defibrillator(AED) is usually placed in the public place which is far away from the hospital, such as airports, etc. The operator positioned the non-medical professionals. In this paper, we used the ARM of Cortex-M3 inside-core of 32 high-performance microprocessors as the core of AED, and designed the software and hardware, studied the correlation algorithm.In this work, the hardware design of the automatic external defibrillator is divided into the following modules: physiological parameter acquisition and automatic defibrillation control module, microprocessor control module, defibrillation module. Physiological parameter acquisition and automatic defibrillation control module extract the electrocardiosignal and thoracic impedance through the special defibrillation electrode, and then determine the timing of defibrillation and select the appropriate of energy to achieve the best results defibrillation, which is one of the key technologies in this article. Microprocessor control module is the core of defibrillation apparatus combination of hardware and software design. Defibrillation module includes charging module and discharge module as required to electric defibrillation, thereinto the damping second-order discharge circuit is also one of the key technologies in this article. On the basis of the above modules, the system also adds automatic ECG signal acquisition analysis, voice prompts and other operational functions.In the signal analysis section, using the standard ECG data, we carried out the simulation comparison experiments of two algorithms of approximate entropy(Ap En) focusing on the theory of the ventricular fibrillation/ventricular tachycardia detection algorithm in the MATLAB environment. The simulation results show that the improved sample entropy fast algorithm can realize the choice of optimal timing of AED defibrillation.