Processing obstructive sleep apnea syndrome (OSAS) data

Ren Sin Tung, Wai Yie Leong

Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Kuala Lumpur, Malaysia.

DOI: 10.4236/jbise.2013.62019                

Abstract

In this study, the EEG signals were processed. Thirteen ICA algorithms were tested to verify the performance efficiency. The EEG signals were recorder using 10/20 international system, based on a 20 minute sleep recording of a severe Obstructive Sleep Apnea Syndrome (OSAS) during NREM and REM sleep. Seven channels were used to record the EEG signals which are sampled at 100 Hz. The performance analysis of the algorithms were investigated to eliminate the loss of the informative EEG signal during the data processing. The denoising results were magnified with the purpose of evaluating the robustness of the denoising algorithms. From the result we obtained, we are able to understand the denoising algorithm is more suitable to process the EEG signal with lower amplitude.

Keywords

EEG; Obstructive Sleep Apnea Syndrome (OSAS); Independent Component Analysis (ICA); Wavelets Analysis

Conflicts of Interest

The authors declare no conflicts of interest.

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