Application of ICA in the Separation of BreathingArtifacts in ECG
نویسندگان
چکیده
In this work, we apply the independent component analysis (ICA) on the extraction of artifacts from the electrocardio-graphic (ECG) signals. ECG analysis is not an easy task when artifacts (electrodes, muscle, breathing, etc) corrupts the ECG, hiding important information. If the mixed signals in the ECG recordings (heart signal and artifacts) are statistically independent, the ICA can blindly separate them, even if they are overlapped in frequency. In order to verify this hypothesis, we present some preliminary results, where real ECG recordings, strongly corrupted by breathing artifacts, are processed by ICA algorithms.
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