Analyzing and Processing EEG-based Multichannel Signals Acquired during Sleeping

• Published in: International journal on smart sensing and intelligent systems Vol. 7; no. 5; pp. 1 - 4
• Main Authors: Vergallo, P., Lay-Ekuakille, A., Giannocaro, N.I., Trabacca, A., Porta, R. Della, De Rinaldis, M.
• Format: Journal Article
• Language: English
• Published: Sydney Sciendo 01.12.2014; De Gruyter Poland
• Subjects: Algorithms; Biomedical measurements; component; Electroencephalography; Electromyography; Empirical analysis; Empirical Mode Decomposition; Evaluation; Sensor arrays; Signal processing; sleep EEG
• ISSN: 1178-5608; 1178-5608
• DOI: 10.21307/ijssis-2019-125

Processing of signals acquired from sensor systems needs accurate algorithms to extract information of interest concerning the problem under study. In this work Empirical Mode Decomposition method is used on EEG signals obtained during polysomnography examination, when electromyographic (EMG) signals are acquired too. EMD method decomposes a signal into components named Intrinsic Mode Functions (IMF) which can exhibit important time-frequency information related to signals under observation. Since EEG signals are obtained from multiple electrodes, the problem is addressed to processing of signals acquired from multiple channels according to sensor array techniques. The objective of this work is to define an automatic method to detect transient event, changes of sleep stage in EEG signals which can allow an evaluation of the state of the patient. In this first step we analyze and process EEG signals through EMD method to remove EMG contributes. The obtained results are encouraging in the definition of a future multivariate approach to quantify brain activity by evaluating correlation of the IMFs calculated for each channel.