Digital analysis and technical specifications.

Digital acquisition and analysis of sleep data has become more common over the past 20 years. Many investigators have developed strategies to record and analyze sleep in a quantitative way. Initially, digital recording and analysis were restricted by technical limitations. With current technology, the technical limitations of computer acquisition, data storage, and analysis are less constraining, and the development of recommendations for the specifications and scoring of sleep can be more clearly guided by the goal of characterizing physiologic phenomena. In order to develop recommendations and specifications regarding digital acquisition and analysis, a literature search, evidence review, and standardized consensus process focused on 5 questions regarding computer-assisted sleep recording and analysis. These questions included: (1) the reliability of computerized scoring of sleep stages, (2) the analysis of elemental events and waveforms, (3) the physiological and/or clinical significance of digitally-analyzed signals, (4) the importance of proposed changes in standardized scoring that could incorporate digital analysis, and (5) the potential advantages and disadvantages of computerized sleep recordings. Of 154 studies identified by the search, 119 were found to be suitable for evidence review. The evidence review suggested that computer scoring and quantitative analysis of sleep is still in the formative stage of development. For many technical specification decisions, little or no direct evidence was found, although basic engineering principles or standard practices provided some rationale which was utilized to develop the recommendations formulated during the subsequent UCLA/Rand standardized consensus process.

[1]  A. Loomis,et al.  Cerebral states during sleep, as studied by human brain potentials , 1937 .

[2]  N. Kleitman,et al.  Regularly occurring periods of eye motility, and concomitant phenomena, during sleep. , 1953, Science.

[3]  A. Rechtschaffen,et al.  A manual of standardized terminology, technique and scoring system for sleep stages of human subjects , 1968 .

[4]  J R Smith,et al.  EEG sleep stage scoring by an automatic hybrid system. , 1971, Electroencephalography and clinical neurophysiology.

[5]  P Courtney,et al.  A hybrid computer system for unsupervised scoring of sleep records. , 1972, Biomedical sciences instrumentation.

[6]  L C Johnson,et al.  Effect of flurazepam on sleep spindles and K-complexes. , 1976, Electroencephalography and clinical neurophysiology.

[8]  A Kumar,et al.  An automatic spindle analysis and detection system based on the evaluation of human ratings of the spindle quality. , 1979, Waking and sleeping.

[9]  J. R. Smith,et al.  Automated measurement of alpha, beta, sigma, and theta burst characteristics. , 1979, Sleep.

[10]  P Y Ktonas,et al.  Automated detection of EEG artifacts during sleep: preprocessing for all-night spectral analysis. , 1979, Electroencephalography and clinical neurophysiology.

[11]  Sleep Pharmacology and Automated EEG Analysis , 1979 .

[12]  R F Hoffmann,et al.  Conceptual and methodological considerations towards the development of computer-controlled research on the electro-physiology of sleep. , 1979, Waking and sleeping.

[13]  D J Kupfer,et al.  An automated analysis of REM sleep in primary depression. , 1979, Biological psychiatry.

[14]  J R Smith.  Automated EEG analysis with microcomputers. , 1980, Medical instrumentation.

[15]  I Gath,et al.  Computerized method for scoring of polygraphic sleep recordings. , 1980, Computer programs in biomedicine.

[16]  J. R. Smith,et al.  Sleep spindle characteristics as a function of age. , 1982, Sleep.

[17]  D. Kupfer,et al.  Application of automated REM analysis in depression. , 1982, Archives of general psychiatry.

[18]  M Hirshkowitz,et al.  Sleep spindles: pharmacological effects in humans. , 1982, Sleep.

[19]  Ktonas Py.  Automated analysis of abnormal electroencephalograms. , 1983 .

[20]  J Hasan,et al.  Differentiation of normal and disturbed sleep by automatic analysis. , 1983, Acta physiologica Scandinavica. Supplementum.

[21]  D. Kupfer,et al.  Application of automated REM and slow wave sleep analysis: II. Testing the assumptions of the two-process model of sleep regulation in normal and depressed subjects , 1984, Psychiatry Research.

[22]  R. Hoffmann,et al.  Quantitative description of sleep stage electrophysiology using digital period analytic techniques. , 1984, Sleep.

[23]  D. Kupfer,et al.  Application of automated REM and slow wave sleep analysis: I. Normal and depressed subjects , 1984, Psychiatry Research.

[24]  Log amplitude is a linear function of log frequency in NREM sleep eeg of young and elderly normal subjects. , 1984, Electroencephalography and clinical neurophysiology.

[25]  D. Kupfer,et al.  Electroencephalographic sleep of younger depressives. Comparison with normals. , 1985, Archives of general psychiatry.

[26]  D. Kupfer,et al.  Slow wave sleep in elderly depressed, demented, and healthy subjects. , 1985, Sleep.

[27]  A. Declerck,et al.  Sleep spindle detection and its clinical relevance. , 1986, European neurology.

[28]  Twenty-four hour ambulatory EEG monitoring: development and applications. , 1986, Journal of medical engineering & technology.

[29]  S Matsuoka,et al.  [Automatic determination system of human sleep stages on an experimental basis]. , 1986, Journal of UOEH.

[30]  S R Ray,et al.  Computer sleep stage scoring--an expert system approach. , 1986, International journal of bio-medical computing.

[31]  W Burr,et al.  Computerized analysis of epileptic activity and sleep in mobile long-term EEG monitoring. , 1986, European neurology.

[32]  D. Kupfer,et al.  Comparison of automated REM and slow-wave sleep analysis in young and middle-aged depressed subjects , 1986, Biological Psychiatry.

[33]  L Höller,et al.  Comparison of visual analysis and automatic sleep stage scoring (Oxford Medilog 9000 System). , 1986, European neurology.

[34]  J. Pilcher,et al.  Automatic analysis overcomes limitations of sleep stage scoring. , 1986, Electroencephalography and clinical neurophysiology.

[35]  R Hoffmann,et al.  Computer quantification of delta activity in sleep EEG. , 1987, Computers and biomedical research, an international journal.

[36]  M. Kerkhofs,et al.  Automated sleep scoring: a comparative reliability study of two algorithms. , 1987, Electroencephalography and clinical neurophysiology.

[37]  Importance of both amplitude and incidence measures in time-domain analysis. , 1988, Sleep.

[38]  H. Kuwahara,et al.  Automatic real-time analysis of human sleep stages by an interval histogram method. , 1988, Electroencephalography and clinical neurophysiology.

[39]  I. Feinberg,et al.  Response of delta (0-3 Hz) EEG and eye movement density to a night with 100 minutes of sleep. , 1988, Sleep.

[40]  P Y Ktonas,et al.  Non-random patterns of REM occurrences during REM sleep in normal human subjects: an automated second-order study using Markovian modeling. , 1988, Electroencephalography and clinical neurophysiology.

[41]  B.H. Jansen,et al.  Knowledge-based approach to sleep EEG analysis-a feasibility study , 1989, IEEE Transactions on Biomedical Engineering.

[42]  R Ferri,et al.  Comparison between the results of an automatic and a visual scoring of sleep EEG recordings. , 1989, Sleep.

[43]  D. Dijk,et al.  Sex differences in the sleep EEG of young adults: visual scoring and spectral analysis. , 1989, Sleep.

[44]  D. Kupfer,et al.  Effects of age on delta and REM sleep parameters. , 1989, Electroencephalography and clinical neurophysiology.

[45]  Daniel J Buysse,et al.  Sleep, gender, and depression: An analysis of gender effects on the electroencephalographic sleep of 302 depressed outpatients , 1990, Biological Psychiatry.

[46]  P. Macfarlane,et al.  Recommendations for standardization and specifications in automated electrocardiography: bandwidth and digital signal processing. A report for health professionals by an ad hoc writing group of the Committee on Electrocardiography and Cardiac Electrophysiology of the Council on Clinical Cardiology, , 1990, Circulation.

[47]  Daniel J Buysse,et al.  Electroencephalographic sleep in the healthy "old old": a comparison with the "young old" in visually scored and automated measures. , 1991, Journal of gerontology.

[48]  Daniel J Buysse,et al.  Sleep in late-life recurrent depression. Changes during early continuation therapy with nortriptyline. , 1991, Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology.

[49]  I. Feinberg,et al.  Acute deprivation of the terminal 3.5 hours of sleep does not increase delta (0-3-Hz) electroencephalograms in recovery sleep. , 1991, Sleep.

[50]  J Röschke,et al.  Excitability and susceptibility of the brain's electrical activity during sleep: an analysis of late components of AEPs and VEPs. , 1991, The International journal of neuroscience.

[51]  S. Naganuma,et al.  Effect of the continuity and sampling rate of polygraphy data on sleep stage by a computerized scoring system--a reliability study. , 1992, Nihon eiseigaku zasshi. Japanese journal of hygiene.

[52]  J Gade,et al.  Sleep disturbances in IDDM patients with nocturnal hypoglycemia. , 1992, Sleep.

[53]  W. Trojaborg,et al.  Effect of growth hormone on human sleep energy , 1992, Clinical endocrinology.

[54]  G. Rosadini,et al.  An EEG computerized system for the evaluation of hypnotic drugs. , 1992, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[55]  A Värri,et al.  A simple format for exchange of digitized polygraphic recordings. , 1992, Electroencephalography and clinical neurophysiology.

[56]  P. Prinz,et al.  Quantitative analysis of the EEG during tonic REM sleep--methodology. , 1992, Electroencephalography and Clinical Neurophysiology.

[57]  American Electroencephalographic Society Guidelines for Polygraphic Assessment of Sleep‐Related Disorders (Polysomnography) , 1992, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.

[58]  A computerized system for acquisition and evaluation of polysomnographic recordings , 1992, International journal of clinical monitoring and computing.

[59]  J. Hasan,et al.  Validation of computer analysed polygraphic patterns during drowsiness and sleep onset. , 1993, Electroencephalography and clinical neurophysiology.

[60]  D. McCormick,et al.  Cellular mechanisms of a synchronized oscillation in the thalamus. , 1993, Science.

[61]  T. Sejnowski,et al.  Thalamocortical oscillations in the sleeping and aroused brain. , 1993, Science.

[62]  S. Andreas,et al.  Validation of automated sleep stage and apnoea analysis in suspected obstructive sleep apnoea. , 1993, The European respiratory journal.

[63]  J. Röschke,et al.  Dynamical properties of the sleep EEG in different frequency bands. , 1993, The International journal of neuroscience.

[64]  J P Macher,et al.  Neural network model: application to automatic analysis of human sleep. , 1993, Computers and biomedical research, an international journal.

[65]  G. Fromm,et al.  Evaluation of human consciousness level by means of “automated fluctuation analysis” of high frequency electroencephalogram fitted by double Lorentzians , 1993, Integrative physiological and behavioral science : the official journal of the Pavlovian Society.

[66]  M Hirshkowitz,et al.  Issues in computerized polysomnography. , 1994, Sleep.

[67]  Detection of EEG patterns related to nocturnal hypoglycemia. , 1994, Methods of information in medicine.

[68]  J Röschke,et al.  Nonlinear EEG dynamics during sleep in depression and schizophrenia. , 1994, The International journal of neuroscience.

[69]  M. Vitiello,et al.  C STAGE, automated sleep scoring: development and comparison with human sleep scoring for healthy older men and women. , 1994, Sleep.

[70]  N. Kajimura,et al.  A quantitative sleep-EEG study on the effects of benzodiazepine and zopiclone in schizophrenic patients , 1995, Schizophrenia Research.

[71]  D J Kupfer,et al.  Automating the sleep laboratory: implementation and validation of digital recording and analysis. , 1995, International journal of bio-medical computing.

[72]  L. Ferini-Strambi,et al.  Arousal Fluctuations in Non‐Rapid Eye Movement Parasomnias: The Role of Cyclic Alternating Pattern as a Measure of Sleep Instability , 1995, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.

[73]  C. Albertario,et al.  Comparison of a frequency-based analysis of electroencephalograms (Z-ratio) and visual scoring on the multiple sleep latency test. , 1995, Sleep.

[74]  Sleep EEG changes in psychotic disorders: gender and age effects. , 1995, Neuropsychobiology.

[75]  J Hasan,et al.  Past and future of computer-assisted sleep analysis and drowsiness assessment. , 1996, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.

[76]  R. Vasko,et al.  Muscle artifacts in the sleep EEG: Automated detection and effect on all‐night EEG power spectra , 1996, Journal of sleep research.

[77]  W. Herrmann,et al.  The future of computer-assisted investigation of the polysomnogram: sleep microstructure. , 1996, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.

[78]  A. Muzet,et al.  Sleep stage scoring using the neural network model: comparison between visual and automatic analysis in normal subjects and patients. , 1996, Sleep.

[79]  E. Sforza,et al.  Automatic Oxford-Medilog 9200 sleep staging scoring: comparison with visual analysis. , 1996, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.

[80]  T. Sejnowski,et al.  Spatiotemporal Patterns of Spindle Oscillations in Cortex and Thalamus , 1997, The Journal of Neuroscience.

[81]  R Baumgart-Schmitt,et al.  On the use of neural network techniques to analyse sleep EEG data. First communication: application of evolutionary and genetic algorithms to reduce the feature space and to develop classification rules. , 1997, Neuropsychobiology.

[82]  W. Dimpfel,et al.  A new frequency based automatic sleep analysis - description of the healthy sleep. , 1997, European journal of medical research.

[83]  J. Hasan,et al.  The detection of drowsiness and sleep onset periods from ambulatory recorded polygraphic data. , 1997, Electroencephalography and clinical neurophysiology.

[84]  D. McCormick,et al.  Sleep and arousal: thalamocortical mechanisms. , 1997, Annual review of neuroscience.

[85]  R. Bart Sangalm,et al.  Computerized Scoring of Abnormal Human Sleep: A Validation , 1997, Clinical EEG.

[86]  B Stubinski,et al.  Comparison between visual scoring of cyclic alternating pattern (CAP) and computerized assessment of slow EEG oscillations in the transition from light to deep non-REM sleep. , 1997, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.

[87]  D. White,et al.  Evaluation of a computerized polysomnographic system. , 1998, Sleep.

[88]  A. Watanabe.  Cerebral changes in hepatic encephalopathy , 1998, Journal of gastroenterology and hepatology.

[89]  J. Stradling,et al.  Sleep fragmentation indices as predictors of daytime sleepiness and nCPAP response in obstructive sleep apnea. , 1998, American journal of respiratory and critical care medicine.

[90]  G. Pfurtscheller,et al.  Quality control of polysomnographic sleep data by histogram and entropy analysis , 1999, Clinical Neurophysiology.

[91]  D. Sajkov,et al.  Portable computerized polysomnography in attended and unattended settings. , 1999, Chest.

[92]  P. Escourrou,et al.  Needs and costs of sleep monitoring. , 2000, Studies in health technology and informatics.

[93]  C Guilleminault,et al.  Upper airway resistance syndrome. Central electroencephalographic power and changes in breathing effort. , 2000, American journal of respiratory and critical care medicine.

[94]  Hae-Jeong Park,et al.  Automated Sleep Stage Scoring Using Hybrid Rule- and Case-Based Reasoning , 2000, Comput. Biomed. Res..

[95]  A. Besset,et al.  Sleep architecture, slow wave activity, and sleep spindles in adult patients with sleepwalking and sleep terrors , 2000, Clinical Neurophysiology.

[96]  T. Penzel,et al.  Computer based sleep recording and analysis. , 2000, Sleep medicine reviews.

[97]  Jean Gotman,et al.  Computer-assisted sleep staging , 2001, IEEE Trans. Biomed. Eng..

[98]  J. Montplaisir,et al.  Daytime sleepiness and EEG spectral analysis in apneic patients before and after treatment with continuous positive airway pressure. , 2001, Chest.

[99]  D. Giles,et al.  Beta/Gamma EEG activity in patients with primary and secondary insomnia and good sleeper controls. , 2001, Sleep.

[100]  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.

[101]  C. Guilleminault,et al.  Sleep and wakefulness in somnambulism: a spectral analysis study. , 2001, Journal of psychosomatic research.

[102]  R. Armitage,et al.  Sleep EEG, depression and gender. , 2001, Sleep medicine reviews.

[103]  C. Guilleminault,et al.  Sleep and daytime sleepiness in upper airway resistance syndrome compared to obstructive sleep apnoea syndrome. , 2001, The European respiratory journal.

[104]  D. Giles,et al.  Temporal and stagewise distribution of high frequency EEG activity in patients with primary and secondary insomnia and in good sleeper controls , 2001, Journal of sleep research.

[105]  Jukka Saarinen,et al.  Fuzzy detection of EEG alpha without amplitude thresholding , 2002, Artif. Intell. Medicine.

[106]  Jean Gotman,et al.  Digital Tools in Polysomnography , 2002, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.

[107]  J. Röschke,et al.  The sleep EEG's microstructure in depression: alterations of the phase relations between EEG rhythms during REM and NREM sleep. , 2002, Sleep medicine.

[108]  A John Rush,et al.  Quantitative EEG amplitude across REM sleep periods in depression: preliminary report. , 2002, Journal of psychiatry & neuroscience : JPN.

[109]  Peter Achermann,et al.  Visual and Spectral Analysis of Sleep EEG in Acute Hemispheric Stroke , 2002, European Neurology.

[110]  C J Michel,et al.  A computer method for identifying patterns in electroencephalogram signals , 2003, Journal of medical engineering & technology.

[111]  P. Ktonas,et al.  Two-minute rapid eye movement (REM) density fluctuations in human REM sleep , 2003, Neuroscience Letters.

[112]  A. Wichniak,et al.  Spectral composition of NREM sleep in healthy subjects with moderately increased daytime sleepiness , 2003, Clinical Neurophysiology.

[113]  A. Besset,et al.  Sleep architecture, slow wave activity and sleep spindles in mild sleep disordered breathing , 2003, Clinical Neurophysiology.

[114]  Manuel Schabus,et al.  Sleep spindles and their significance for declarative memory consolidation. , 2004, Sleep.

[115]  Koby Todros,et al.  Assessment of automated scoring of polysomnographic recordings in a population with suspected sleep-disordered breathing. , 2004, Sleep.

[116]  J. Röschke,et al.  The dimensionality of human's electroencephalogram during sleep , 1991, Biological Cybernetics.

[117]  Alpo Värri,et al.  Sleep Depth Oscillations: An Aspect to Consider in Automatic Sleep Analysis , 2003, Journal of Medical Systems.

[118]  I. Feinberg,et al.  Rapid eye movement density shows trends across REM periods but is uncorrelated with NREM delta in young and elderly human subjects , 2004, Brain Research Bulletin.

[119]  M. Lehtokangas,et al.  Autoassociative MLP in Sleep Spindle Detection , 2004, Journal of Medical Systems.

[120]  Development of a new manual for characterizing sleep. , 2004, Sleep.

[121]  Raffaele Ferri,et al.  Inter-rater reliability of sleep cyclic alternating pattern (CAP) scoring and validation of a new computer-assisted CAP scoring method , 2005, Clinical Neurophysiology.

[122]  J. Röschke,et al.  Nonlinear analysis of sleep eeg in depression: Calculation of the largest lyapunov exponent , 2005, European Archives of Psychiatry and Clinical Neuroscience.

[123]  T. Åkerstedt,et al.  Hypnotics and sleep physiology: A consensus repot , 2005, European Archives of Psychiatry and Clinical Neuroscience.

[124]  A John Rush,et al.  High Frequency EEG Activity during Sleep: Characteristics in Schizophrenia and Depression , 2005, Clinical EEG and neuroscience.

[125]  Jean Gotman,et al.  Detection of rapid-eye movements in sleep studies , 2005, IEEE Transactions on Biomedical Engineering.

[126]  M. Littner,et al.  Practice parameters for the indications for polysomnography and related procedures: an update for 2005. , 2005, Sleep.

[127]  J. Virkkala,et al.  Automated Frequency Analysis of Synchronous and Diffuse Sleep Spindles , 2005, Neuropsychobiology.

[128]  A. Schlögl,et al.  An E-Health Solution for Automatic Sleep Classification according to Rechtschaffen and Kales: Validation Study of the Somnolyzer 24 × 7 Utilizing the Siesta Database , 2005, Neuropsychobiology.

[129]  L. Tarassenko,et al.  New method of automated sleep quantification , 1992, Medical and Biological Engineering and Computing.

[130]  A. Walters,et al.  The scoring of arousal in sleep: reliability, validity, and alternatives. , 2007, Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine.

[131]  A. Chesson,et al.  The American Academy of Sleep Medicine (AASM) Manual for the Scoring of Sleep and Associated Events: Rules, Terminology and Technical Specifications , 2007 .