Signal processing is an area of applied mathematics that deals with operations on or analysis of signals, in either discrete or continuous time to perform useful operations on those signals. Depending upon the application, a useful operation could be control, data compression, data transmission, denoising, prediction, filtering, smoothing, deblurring, tomographic reconstruction, identification, classification, or a variety of other operations. Signals of interest can include sound, images, time-varying measurement values and sensor data, for example biological data such as electrocardiograms, control system signals, telecommunication transmission signals such as radio signals, and many others.
Published in Chapter:
Trends of ECG Analysis and Diagnosis
Swanirbhar Majumder (NERIST (Deemed University), India) and Saurabh Pal (University of Calcutta, India)
Copyright: © 2016
|Pages: 26
DOI: 10.4018/978-1-4666-8828-5.ch009
Abstract
Any biomedical signal has the specialty in terms of the remoteness and nature of their source as an advantage over other natural signals. The analysis of biomedical signal plays a significant role in medical, and to be exact cardiological decision making, provided, the subject information is accurate and reliable. Normally experienced and trained medical practitioners, are known to study and know them better, but in this age of technology computerized expert system are better for long term continuous monitoring and automatic decision making. This led to evolution of biomedical engineering as a separate wing where parts of engineering under automatic signal processing and analysis studies are done. ECG being the most vital physiological signal, its acquisition technique, noise and artifacts elimination methodologies are discussed in this chapter. A brief description on ECG and its usage as biometric and analysis of Atrial Fibrillation is presented.