A Novel EEG Index for Evaluating the Sleep Quality in Patients with Obstructive Sleep Apnea-Hypopnea Syndrome

Abstract

Obstructive sleep apnea-hypopnea syndrome (OSAHS) is a highly prevalent sleep disorder characterized by recurrent episodes of oxygen desaturation during sleep, decreased sleep quality, and excessive daytime sleepiness. A basic method of evaluating sleep quality is polysomnography (PSG) where sleep stages are identified from the electroencephalogram (EEG), electrooculogram and chin electromyogram. The implementation of PSG is limited to sleep laboratories because this test is rather complicated to perform and quite time-consuming to analysis, requiring skilled technicians. Development of simple alternative methods to PSG could enable sleep tests to be performed at home. Our study aimed to identify simple measures for evaluating the sleep quality. We focused on a simple index, entropy, which is derived from power spectrum of EEG signals throughout the night, and reflects the dynamics of EEG signals, and examined whether the entropy of EEG reflects the sleep quality of OSAHS. The EEG signals for the analysis of EEG entropy were recorded from the temple area. The EEG entropy was compared with the sleep quality by traditional approaches of EEG from PSG in 58 OSAHS patients and 8 healthy volunteers. The EEG entropy in each subject showed the negative values and fluctuated during sleep. There was a significant correlation between the EEG entropy and the sleep quality (r = 0.626, p < 0.001); namely, the amplitude of the fluctuation was increased with the increase in the sleep quality. We therefore propose that the EEG entropy could be useful for evaluating the sleep quality of OSAHS. Obstructive sleep apnea-hypopnea syndrome (OSAHS) is a highly prevalent sleep disorder characterized by recurrent upper airway obstruction during sleep leading to hypoxemia and sleep fragmentation. This disease has many potential consequences including excessive daytime sleepiness, neurocognitive deterioration, endocrinologic and metabolic effects, and decreased sleep quality (Guilleminault et al. 1976). Moreover, OSAHS patients are at increased risk for vascular events, which represent the greatest morbidity and mortality of all associated complications (Jennum and Riha 2009).The sleep quality has been evaluated as the sleep efficiency [slow wave sleep (SWS)/total sleep time (TST)] by the manual scoring approaches of PSG as the gold standard for the diagnosis of OSAHS (Rechtschaffen and Kales 1968). Generally, normal persons and mild OSAHS patients show five stages of sleep [rapid eye movement (REM), stages 1 and 2, stages 3 and 4 (SWS)], and severe OSAHS patients show little SWS. Therefore, in severe OSAHS patients, sleep efficiency (SWS/TST) could be decreased (Landolt et al. 1996;Valladares et al. 2008).The conventional PSG scoring is complicated and cannot be done in real time. Particularly, at least eight electrodes in addition to those for electrooculogram (EOG) and chin electromyogram (chin EMG) are needed on the scalp for sampling EEG signals to assess the sleep stage. Moreover, the visual scoring of the EEG is time-consuming and s...

Chronic widespread musculoskeletal pain in patients with obstructive sleep apnea syndrome and the relationship between sleep disorder and pain level, quality of life, and disability

“…OSAS is a very common sleep disorder and leads to hypoxemia and sleep fragmentation 19 ) . In this study, the prevalence of CWP in patients with OSAS was 55.4%, and female OSAS patients had a greater risk of CWP than did male OSAS patients.…”

Sensorimotor Cortical Activity during Respiratory Arousals in Obstructive Sleep Apnea

“…They do not consider arousal as an important feature of obstructive sleep apnea, which is generally not the focus of the study. A previous study has also used an entropy measure as the EEG index to determine the sleep quality in obstructive sleep apnea-hypopnea syndrome patients using full PSG recordings [20]. However, in this study we analyzed only the RCA EEG signal, which has an advantage of not only revealing a major pathology of obstructive sleep apnea but also does not require the data recorded for the entire night.…”

“…This metric has been shown in previous studies to be useful for sleep-related and other neurological disorders. Approximate entropy has been shown to detect and characterize seizures in patients with epilepsy [17], classify neurodegenerative disorders from healthy controls [18], detect sleep hypopnea [19] and evaluate sleep quality in obstructive sleep apneahypopnea syndrome [20]. Recently, approximate entropy was also used in a nonlinear model combined with polysomnography (PSG) features like nasal airflow and thoracic movements to predict the presence and severity of OSA [21].…”

Short-Term Impact of Sleep Apnea/Hypopnea on the Interaction Between Various Cortical Areas

“…12,13 Entropy, as a measure to quantify the amount of signal uncertainty, 14 has already been applied in SAHS-related research. For instance, EEG entropy was applied to evaluate the sleep quality in patients with obstructive SAHS, 15 and non–rapid eye movement (NREM) sleep instability in children with sleep disordered breathing or OSA. 16 Permutation entropy (PeEn) and symbolic transfer entropy (STE) possess the advantages of robustness, and allow easy identification of small noise differences.…”