期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2014
卷号：2
期号：11
出版社：S&S Publications
摘要：Compressed Electrocardiography (ECG) is being used in modern telecardiology applications for fasterand efficient transmission. ECG diagnosis algorithms require the compressed ECG packets to be decompressed beforediagnosis can be applied. This additional process of decompression before performing diagnosis for every ECG packetintroduces undesirable delays, which can have severe impact on the longevity of the patient. ECG signal analysis hasshown an important role in the prognosis, diagnosis and survival analysis of heart diseases. ECG signal compression isrequired due to three main reasons: low storage data space, reduction of low data transmission rate and transmissionbandwidth conversation. The electrocardiogram (ECG) signal compression using clustered under PrematureContraction (PC), Premature Ventricular Contraction (PVC), and Arterial Flutter (AF) is presented in this paper.Principal Component Analysis (PCA) technique is used for dimensionality reduction and data classification. Themethods are applied to the MIT/BIH arrhythmia ECG database. The results are efficient promising that this approachcan useful for data compression of ECG signals. The experimental results are analyzed on the basis of Percentage ofroot mean square difference (PRD and compression ratio (CR).
关键词：Compressed Electrocardiography; Compression Ratio; Electrocardiogram; Fuzzy Inference System;And Medical Data Mining
