Fast Analysis for Emergency Critical Warning in Heart Failure Using Impact Integration Component Analysis combination with Electrocardiography Plate Waveform Recognition

Abstract

In Intensive Care Unit (ICU) Room , there are normally several sensors connected to each patient receiving intensive care and the several processors monitors and analyzes. If the processor discovers an abnormality then alerts the medical technique office. However, the most patients in heart disease concerns in the daily activities such as activity in hard work, exercises , surprise, altercation, battle. Become due to Clinical depression and Erectile Dysfunction (Impotence) which causes of anxiety and fear. They are unknown the limits of your cardiac muscle and vascular resistance. They want warning which is fast and accurate before losing control. We develops signal recognition for algorithm which is very fast and accurate. It helps warning patients to stop risk activity. However, it is able to transfer data of heartbeat pass network system for guidance of doctor. This research proposes: 1) Framework of data operation in fast Electrocardiography analysis. 2) Impact Integration Component Analysis which use for feature extraction and Electrocardiography signal recognition 3) Electrocardiography Plate waveform for identify risk condition 2 layer which are Cardiac Arrhythmia layer and identify layer of symptom. This system support expert system of medical field. Result of the experiment which test signal 100 pattern of Cardiac Arrhythmia. Impact Integration Component Analysis is able to abnormal recognition accuracy than Automata matching 12.65 - 28.11 average percentage and spends time less than other algorithm 20.54 average percentage and be able to warning within duration 15 sec.