Investigations on Signal Conditioning techniques for Cardiac electric behavior in Telecardiology Systems

Abstract

In remote cardiac diagnosis tele-cardiology has become an important tool enabling the newlinetransmission of electrocardiogram (ECG) signals between widely separated locations. newlineReceived signals can be recorded and processed to allow diagnosis so that the specialist newlinecan advise the patient. However during ECG acquisition several artefacts strongly newlinedegrade the signal quality. The dominant artefacts encounters with ECG signal are Power newlineLine Interference (PLI), Baseline Wander (BW), Muscle Artefacts (MA), Electrode newlineMotion Artefacts (EM) and channel noise generated during transmission. All of these newlinemask the tiny features of ECG signals that specialists depend upon for clinical newlinemonitoring, interpretation and diagnosis. The ability to extract high resolution, valid ECG newlinesignals from contaminated recordings is an important subject for research. In practice, newlinecontaminated cardiac signals are non-stationary and fixed coefficient filters will not work newlinewell. To track random variations in noisy signals, the filter has to be adaptive, able to newlinechange its coefficients according to statistical nature of the noise. This thesis investigates newlinethe development of Adaptive Noise Cancellers (ANCs) to remove artefacts from ECG newlinesignals. newline