Comput. Biol. Med. - Current methods in electrocardiogram characterization.

Tópicos

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Resumo

The Electrocardiogram (ECG) is the P-QRS-T wave depicting the cardiac activity of the heart. The subtle changes in the electric potential patterns of repolarization and depolarization are indicative of the disease afflicting the patient. These clinical time domain features of the ECG waveform can be used in cardiac health diagnosis. Due to the presence of noise and minute morphological parameter values, it is very difficult to identify the ECG classes accurately by the naked eye. Various computer aided cardiac diagnosis (CACD) systems, analysis methods, challenges addressed and the future of cardiovascular disease screening are reviewed in this paper. Methods developed for time domain, frequency transform domain, and time-frequency domain analysis, such as the wavelet transform, cannot by themselves represent the inherent distinguishing features accurately. Hence, nonlinear methods which can capture the small variations in the ECG signal and provide improved accuracy in the presence of noise are discussed in greater detail in this review. A CACD system exploiting these nonlinear features can help clinicians to diagnose cardiovascular disease more accurately.

Resumo Limpo

electrocardiogram ecg pqrst wave depict cardiac activ heart subtl chang electr potenti pattern repolar depolar indic diseas afflict patient clinic time domain featur ecg waveform can use cardiac health diagnosi due presenc nois minut morpholog paramet valu difficult identifi ecg class accur nake eye various comput aid cardiac diagnosi cacd system analysi method challeng address futur cardiovascular diseas screen review paper method develop time domain frequenc transform domain timefrequ domain analysi wavelet transform repres inher distinguish featur accur henc nonlinear method can captur small variat ecg signal provid improv accuraci presenc nois discuss greater detail review cacd system exploit nonlinear featur can help clinician diagnos cardiovascular diseas accur

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