Improved computational fronto-central sleep depth parameters show differences between apnea patients and control subjects

All-night EEG recordings from 12 male apnea patients and 12 age-matched healthy control subjects were studied in the present work. The spectral mean frequency was used to provide computational sleep depth curves from two frontopolar and two central EEG channels. Our previously presented computational parameters quantifying the properties of the sleep depth curves were improved. The resulting light sleep percentage (LS%) values were higher in apnea patients than in control subjects in the right central brain position (P = 0.028), in concordance to our previous work. Moreover, apnea patients showed higher LS% values in the right frontopolar position (P = 0.008). Also, apnea patients showed a smaller anteroposterior sleep depth difference than control subjects on the right hemisphere (P = 0.002). These are interesting new findings, achieved by the present methodology. Thus, the developed computational parameters were able to quantify, at least to some degree, the disruption of sleep process caused by the recurrent apneic events.

[1]  I. Rezek,et al.  Stochastic complexity measures for physiological signal analysis , 1998, IEEE Transactions on Biomedical Engineering.

[2]  Y. Harrison,et al.  Frontal lobe function, sleep loss and fragmented sleep. , 2001, Sleep medicine reviews.

[3]  T Penzel,et al.  Integrated sleep analysis, with emphasis on automatic methods. , 1991, Epilepsy research. Supplement.

[4]  S. Himanen,et al.  Automatic analysis of electro-encephalogram sleep spindle frequency throughout the night , 2003, Medical and Biological Engineering and Computing.

[5]  L Parrino,et al.  Polysomnographic analysis of arousal responses in obstructive sleep apnea syndrome by means of the cyclic alternating pattern. , 1996, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.

[6]  M Steriade,et al.  Electrophysiological correlates of sleep delta waves. , 1998, Electroencephalography and clinical neurophysiology.

[7]  M. Kryger,et al.  Principles and Practice of Sleep Medicine , 1989 .

[8]  Atte Joutsen,et al.  Visual Assessment of Selected High Amplitude Frontopolar Slow Waves of Sleep: Differences between Healthy Subjects and Apnea Patients , 2004, Clinical EEG and neuroscience.

[9]  M. Lehtokangas,et al.  Optimization of sigma amplitude threshold in sleep spindle detection , 2000, Journal of sleep research.

[10]  Alpo Värri,et al.  Automatic quantification of light sleep shows differences between apnea patients and healthy subjects. , 2004, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[11]  S. Himanen,et al.  Sleep Staging with Frontopolar EEG Derivation , 2004 .

[12]  E. Wolpert A Manual of Standardized Terminology, Techniques and Scoring System for Sleep Stages of Human Subjects. , 1969 .

[13]  Hannu Oja,et al.  Topographic differences in mean computational sleep depth between healthy controls and obstructive sleep apnoea patients , 2006, Journal of Neuroscience Methods.

[14]  S.M. Kay,et al.  Spectrum analysis—A modern perspective , 1981, Proceedings of the IEEE.

[15]  M. Ferrara,et al.  Antero-posterior EEG changes during the wakefulness–sleep transition , 2001, Clinical Neurophysiology.

[16]  Alpo Värri,et al.  Systematic performance evaluation of a continuous-scale sleep depth measure. , 2007, Medical engineering & physics.

[17]  C. Anderson,et al.  Prefrontal cortex: links between low frequency delta EEG in sleep and neuropsychological performance in healthy, older people. , 2003, Psychophysiology.

[18]  J. Montplaisir,et al.  Slow-wave activity in sleep apnea patients before and after continuous positive airway pressure treatment: contribution to daytime sleepiness. , 2001, Chest.

[19]  Alpo Värri,et al.  Anteroposterior Difference in EEG Sleep Depth Measure is Reduced in Apnea Patients , 2005, Journal of Medical Systems.