Interictal EEG denoising using independent component analysis and empirical mode decomposition
Noise contamination is inevitable in biomedical recordings. In some cases biomedical recordings are highly contaminated with artifacts which make the effective recovering process hard to achieve. Many different methods have been proposed for artifact removal from biomedical signals but introducing an effective method which can present valuable data for medical analysis, is still an ongoing process. In this paper a new method for interictal EEG denoising is presented. Single-channel ICA denoising method based on EMD decomposition is used to improve the multi-channel ICA denoising results. This method is tested on simulated epileptic recordings which are contaminated with real muscle artifact and EEG background activity.