SHOCKABLE SIGNAL DETECTION METHOD OF AN AUTOMATED EXTERNAL DEFIBRILLATOR USING A NEURAL NETWORK WITH A WEIGHTED FUZZY MEMBERSHIP FUNCTION CAPABLE OF ACCURATELY AND QUICKLY DETECTING SHOCK HEART SIGNALS

摘要

PURPOSE: A shockable signal detection method of an automated external defibrillator using a neural network with a weight fuzzy membership function is provided to increase revive rate of heart-stop patients by accurately and quickly detecting shockable heart signals through neural network with a weighted fuzzy membership function.;CONSTITUTION: A shockable signal detection of an automated external defibrillator using a neural network with a weight fuzzy membership function comprises: a step(S100) of collecting electrocardiograph signal; a step(S200) of detecting beats from collected electrocardiograph signal; a step(S300) of detecting shockable signals by quickly judging ventricular tachycardia, if pulse from the beats is over predetermined value; a step(S400) of pre-processing beat signals through signal filtering; a step(S600) of extracting characteristics from the pre-processed signals; and a step(S700) of detecting a shockable signal and non-shockable signal by using the characteristics as input characteristics of a neural network with a weighted fuzzy membership function.;COPYRIGHT KIPO 2012