IJARCCE - Computer and Communication Engineering

Abstract

2 Abstract: This paper aims at studying the various techniques and algorithms available in literature for the cancellation of various types of artifacts occurring out of the noise present in the Electrocardiogram (ECG) signal. It further aims at the enhancement of the ECG signal for proper monitoring and diagnosis of the patient. In the process of the transfer of the signal information from the location of the patient to a remote location, certain kind of noise is introduced in the signal that results in the disturbance as well as interference of the signal. Hence, the information cannot be predicted accurately. Thus, it is important to remove the resulting noise and the artifacts in order to enhance the ECG signal for proper treatment of the patient. During the acquisition of ECG signal in clinical environment, it can encounter numerous types of artifacts. Power line interference, muscle artifact, motion artifact, respiration movements, baseline wander and instrumentation noise are the ones of primary interest. As a result, there is degradation in the quality of the signal. The other effects includes frequency resolution, the morphology of ECG signal is strongly affected which provides valuable information about heart diseases or arrhythmias. Hence, it is quite essential to reduce interferences in ECG signal and enhance the reliability as well as accuracy for better diagnosis. The acquisition of ECG signal can be traced back in 1887 when Waller recorded the first ECG signal by capillary electrometer. An improvement in this method was seen with the introduction of string galvanometer and this was credited to Einthoven. Electronic amplifiers replaced the string-galvanometer that lead to the development of direct writing recorder or paper plotter to get ECG strips. In modern times, the acquisition of ECG is carried out by the placement of electrodes at standardized locations on the surface of the skin of the patient. It is a non-invasive technique. The cardiac health of human heart can be well predicted from the heart rate and the ECG signal. Cardiac arrhythmia is a result of the rhythm or change in the morphological pattern of the heart. Basically, a disorder in heart rate causes cardiac arrhythmia. By the analysis of the ECG waveform, these arrhythmias can be detected as well as diagnosed. The characteristics of the P-QRS-T-U waveform that is the duration and amplitude of the wave can serve as the basis to diagnose and extract useful information about the nature of the disease.