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Processing obstructive sleep apnea syndrome (OSAS) data

Processing obstructive sleep apnea syndrome (OSAS) data
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摘要 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. 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.
出处 《Journal of Biomedical Science and Engineering》 2013年第2期152-164,共13页 生物医学工程(英文)
关键词 EEG OBSTRUCTIVE SLEEP APNEA Syndrome (OSAS) Independent Component ANALYSIS (ICA) WAVELETS ANALYSIS EEG Obstructive Sleep Apnea Syndrome (OSAS) Independent Component Analysis (ICA) Wavelets Analysis
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