Abstract
Electroencephalogram (EEG) is one of the medical devices that used for sleep disorder detection. Sleep disorder such as Obstructive Sleep Apnea Syndrome (OSAS) often appears during sleep event. Since the OSAS patients have the difficulties to allow the airflow into the lung while inspiration, the EEG is applied to capture and record the brainwave of the patient. In this work, the Empirical Mode Decomposition (EMD) and Ensemble Empirical Mode Decomposition (EEMD) are used to process and analyze the accuracy and efficiency of the results. Both of these methods will decompose the EEG signal into a collection of Intrinsic Mode Function (IMF). In this paper, index orthogonality has been calculated to indicate the completeness of the decomposed signal with the original signal. The instantaneous frequency and Hilbert Spectrum based on both methods also employed by IMF to analyze and present the results in frequency-time distribution to determine the characteristic of the inherent properties of signal. Besides, Hilbert marginal spectrum has been applied to measure the total amplitude contribution from each frequency value. Finally, the results shown that the EEMD is better in solving mode mixing problem and better improvement over EMD method.
Highlights
Obstructive Sleep Apnea Syndrome (OSAS) is a common sleep disorder problem that always happens among the general population nowadays
The complete set of the original EEG data are collected from severe OSAS patient which is called as objects contain of 120,000 samples for each of the channels and sampling frequency is 100 Hz for 20 minutes
We can observe that the Ensemble Empirical Mode Decomposition (EEMD) method still retains more useful information
Summary
Obstructive Sleep Apnea Syndrome (OSAS) is a common sleep disorder problem that always happens among the general population nowadays. The sleep disorder occurs when the collapse of throat’s tissue which leads to partially or completely blockage of airways flow into lung during inspiration. The OSAS will seriously affect the daily activities of the patients who suffer from sleep disorder. Daytime sleepiness and the likelihood to sleep during driving are the most common negative effects. Their health will be affected due to lack of sleeping time which may cause high blood pressure, stroke, abnormal heart rhythms and even death due to myocardial infarction
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