Signal validation in electroencephalography research

Event related potentials are signals that can be evoked from the nervous system, and measured at the (human) scalp through methodical stimulation of one or more sensory modalities. The actual response signal is always deeply embedded in the background EEG activity, where signal-to-noise power ratio (SNR) for a single response can be as low as -20dB. Therefore, additional processing is needed to extract the evoked response signal from the measurement. The most common processing method is averaging of single trials (sweeps), by which the event related (time-locked to the stimulus) signal is enhanced and the unlocked signal is cancelled out. However, while this, or any other, processing technique is meant to improve the signal-to-noise ratio of the response signal, it is still uncommon to indicate the quality of the

[1]  H. Shapiro,et al.  The identification of rhythmic EEG artifacts by power-spectrum analysis. , 1980, Anesthesiology.

[2]  E. J. Powers,et al.  A digital technique to estimate second-order distortion using higher order coherence spectra , 1992, IEEE Trans. Signal Process..

[3]  P. Libby The Scientific American , 1881, Nature.

[4]  L. Zetterberg Estimation of parameters for a linear difference equation with application to EEG analysis , 1969 .

[5]  Sara Keeney Artifact: Sources and Solutions , 1981 .

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

[7]  H Hinrichs,et al.  A trend-detection algorithm for intraoperative EEG monitoring. , 1996, Medical engineering & physics.

[8]  R. Elul Gaussian Behavior of the Electroencephalogram: Changes during Performance of Mental Task , 1969, Science.

[9]  N V Thakor,et al.  Detection of neurological injury using time-frequency analysis of the somatosensory evoked potential. , 1996, Electroencephalography and clinical neurophysiology.

[10]  M Veldevande,et al.  EEG analysis for monitoring of anesthetic depth , 1991 .

[11]  D. Regan Human brain electrophysiology: Evoked potentials and evoked magnetic fields in science and medicine , 1989 .

[12]  M. Alexander,et al.  Principles of Neural Science , 1981 .

[13]  D. Samson-Dollfus,et al.  Etude automatique de l'eeg: Une methode de detection des non stationnarites , 1978 .

[14]  Rafael Ernesto Delgado,et al.  Automated identification and interpretation of auditory brainstem responses , 1993 .

[15]  N. T. Smith,et al.  Density modulation--a technique for the display of three-variable data in patient monitoring. , 1979, Anesthesiology.

[16]  R. Hartley A More Symmetrical Fourier Analysis Applied to Transmission Problems , 1942, Proceedings of the IRE.

[17]  H M Praetorius,et al.  Adaptive segmentation of EEG records: a new approach to automatic EEG analysis. , 1977, Electroencephalography and clinical neurophysiology.

[18]  A Värri,et al.  Automatic identification of significant graphoelements in multichannel EEG recordings by adaptive segmentation and fuzzy clustering. , 1991, International journal of bio-medical computing.

[19]  P. Rosenfalck Intra- and extracellular potential fields of active nerve and muscle fibres. A physico-mathematical analysis of different models. , 1969, Acta physiologica Scandinavica. Supplementum.

[20]  W. Levy Intraoperative EEG Patterns: Implications for EEG Monitoring , 1984, Anesthesiology.

[21]  S Cerutti,et al.  Monitoring the autonomic nervous system in the ICU through cardiovascular variability signals. , 1997, IEEE engineering in medicine and biology magazine : the quarterly magazine of the Engineering in Medicine & Biology Society.

[22]  T Grönfors,et al.  Effect of sampling frequencies and averaging resolution on medical parameters of auditory brainstem responses. , 1995, Computers in biology and medicine.

[23]  G Hellmann,et al.  Extensible biosignal (EBS) file format: simple method for EEG data exchange. , 1996, Electroencephalography and clinical neurophysiology.

[24]  C. Thornton Assessment of graded changes in the central nervous system, during general anaesthesia and surgery in man, using the auditory evoked response , 1990 .

[25]  S. Shapiro,et al.  An Analysis of Variance Test for Normality (Complete Samples) , 1965 .

[26]  M. Van Gils,et al.  Signal processing in prolonged EEG recordings during intensive care , 1997, IEEE Engineering in Medicine and Biology Magazine.

[27]  Banu Onaral,et al.  Biomedical Signals: Origin and Dynamic Characteristics; Frequency-Domain Analysis , 1999 .

[28]  N. Pradhan,et al.  Patterns of attractor dimensions of sleep EEG. , 1995, Computers in biology and medicine.

[29]  P Berg,et al.  A multiple source approach to the correction of eye artifacts. , 1994, Electroencephalography and clinical neurophysiology.

[30]  D.H. Lange,et al.  A robust parametric estimator for single-trial movement related brain potentials , 1996, IEEE Transactions on Biomedical Engineering.

[31]  D. H. Lange,et al.  Modeling and estimation of single evoked brain potential components , 1997, IEEE Transactions on Biomedical Engineering.

[32]  Ben H. Jansen,et al.  Autoregressive Estimation of Short Segment Spectra for Computerized EEG Analysis , 1981, IEEE Transactions on Biomedical Engineering.

[33]  R.D. Jones,et al.  Enhancement of deep epileptiform activity in the EEG via 3-D adaptive spatial filtering , 1999, IEEE Transactions on Biomedical Engineering.

[34]  W E Hostetler,et al.  Assessment of a computer program to detect epileptiform spikes. , 1992, Electroencephalography and clinical neurophysiology.

[35]  Leonard Carmichael,et al.  ELECTRICAL POTENTIALS FROM THE INTACT HUMAN BRAIN. , 1935, Science.

[36]  S. Shapiro,et al.  A Comparative Study of Various Tests for Normality , 1968 .

[37]  A. Shetter,et al.  Intraoperative monitoring of brain-stem auditory evoked potentials. , 1982, Journal of neurosurgery.

[38]  C.W. Anderson,et al.  Multivariate autoregressive models for classification of spontaneous electroencephalographic signals during mental tasks , 1998, IEEE Transactions on Biomedical Engineering.

[39]  M E Lutman,et al.  Quality estimation of click-evoked oto-acoustic emissions. , 1990, Scandinavian audiology.

[40]  J R Bourne,et al.  Artificial intelligence methods in quantitative electroencephalogram analysis. , 1982, Computer programs in biomedicine.

[41]  B. Oken,et al.  Short-term variability in EEG frequency analysis. , 1985, Electroencephalography and clinical neurophysiology.

[42]  Evaluation of automatic quality assessment of auditory evoked potentials in clinical data , 1996, Proceedings of 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[43]  M P Robinson,et al.  Interference to medical equipment from mobile phones. , 1997, Journal of medical engineering & technology.

[44]  C. A. Berry,et al.  A simple cable for reduction of movement artifact in electroencephalographic recordings. , 1967, Electroencephalography and clinical neurophysiology.

[45]  S Cerutti,et al.  Classification of the EEG during neurosurgery. Parametric identification and Kalman filtering compared. , 1986, Journal of biomedical engineering.

[46]  John R. Glover,et al.  A Multichannel Signal Processor for the Detection of Epileptogenic Sharp Transients in the EEG , 1986, IEEE Transactions on Biomedical Engineering.

[47]  P. Tonella,et al.  EEG data compression techniques , 1997, IEEE Transactions on Biomedical Engineering.

[48]  Winni F. Hofman,et al.  Sleep-wake research in the Netherlands , 1999 .

[49]  P. Deltenre,et al.  A new descriptor of the dual character of the input-output behaviour of the cochlea, with implications for signal-to-noise ratio estimation of brain-stem auditory potentials evoked by alternating polarity clicks. , 1993, Electroencephalography and clinical neurophysiology.

[50]  H. Lüders,et al.  Interobserver variability in EEG interpretation , 1985, Neurology.

[51]  C. Brunia,et al.  Distribution of slow brain potentials related to motor preparation and stimulus anticipation in a time estimation task. , 1988, Electroencephalography and clinical neurophysiology.

[52]  J. Makhoul,et al.  Linear prediction: A tutorial review , 1975, Proceedings of the IEEE.

[53]  A R MacLennan,et al.  Reduction of evoked potential measurement time by a TMS320 based adaptive matched filter. , 1995, Medical engineering & physics.

[54]  Bodis-Wollner,et al.  International Federation of Societies for Electroencephalography and Clinical Neurophysiology. , 1974, Electroencephalography and clinical neurophysiology.

[55]  P J Cluitmans,et al.  Information processing during cardiac surgery: an event related potential study. , 1995, Electroencephalography and clinical neurophysiology.

[56]  G. B. Anderson,et al.  Modeling the Stationarity and Gaussianity of Spontaneous Electroencephalographic Activity , 1975, IEEE Transactions on Biomedical Engineering.

[57]  William J. Williams,et al.  Time-frequency analysis of electrophysiology signals in epilepsy , 1995 .

[58]  H. Jasper,et al.  The ten-twenty electrode system of the International Federation. The International Federation of Clinical Neurophysiology. , 1999, Electroencephalography and clinical neurophysiology. Supplement.

[59]  N. T. Smith,et al.  SPECTRAL EDGE FREQUENCY — A NEW CORRELATE OF ANESTHETIC DEPTH , 1980 .

[60]  Sergio Cerutti,et al.  Parameter extraction in EEG processing during riskful neurosurgical operations , 1985 .

[61]  M. M. van den Berg-Lenssen,et al.  Correction of ocular artifacts in EEGs using an autoregressive model to describe the EEG; a pilot study. , 1989, Electroencephalography and clinical neurophysiology.

[62]  David S. Gorney The Practical Guide to Digital EEG , 1992 .

[63]  M.B. Cunha,et al.  SIGIF: a digital signal interchange format with application in neurophysiology , 1997, IEEE Transactions on Biomedical Engineering.

[64]  R. Sclabassi,et al.  The modulatory effect of prior input upon afferent signals in the somatosensory system , 1977 .

[65]  B. Rosen,et al.  The associations between 40 Hz-EEG and the middle latency response of the auditory evoked potential. , 1987, The International journal of neuroscience.

[66]  R. Verleger Valid identification of blink artefacts: are they larger than 50 microV in EEG records? , 1993, Electroencephalography and clinical neurophysiology.

[67]  R.C.W. Grieve,et al.  Training neural networks for stimulus artifact reduction in somatosensory evoked potential measurements , 1996, Proceedings of 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[68]  R. Jané,et al.  Acoustic analysis of snoring sound in patients with simple snoring and obstructive sleep apnoea. , 1996, The European respiratory journal.

[70]  R. Coppola,et al.  Signal to noise ratio and response variability measurements in single trial evoked potentials. , 1978, Electroencephalography and clinical neurophysiology.

[71]  Vladimír Strejc,et al.  Least squares parameter estimation , 1979, Autom..

[72]  R. Verleger,et al.  The instruction to refrain from blinking affects auditory P3 and N1 amplitudes. , 1991, Electroencephalography and clinical neurophysiology.

[73]  M. Charlton,et al.  EEG in the operating room: artifacts and unusual waveforms. , 1982, The American journal of EEG technology.

[74]  Stephan Weiss,et al.  A sequential detection method for late auditory evoked potentials , 1996, Proceedings of 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[75]  R. Sclabassi,et al.  SOMATOSENSORY EVOKED POTENTIALS TO RANDOM STIMULUS TRAINS , 1980, Annals of the New York Academy of Sciences.

[76]  T.F. Collura,et al.  EView-a workstation-based viewer for intensive clinical electroencephalography , 1993, IEEE Transactions on Biomedical Engineering.

[77]  C Thornton,et al.  Evoked potentials in anaesthesia. , 1991, European journal of anaesthesiology.

[78]  Joseph D. Bronzino,et al.  The Biomedical Engineering Handbook , 1995 .

[79]  van Mj Mark Gils Peak identification in auditory evoked potentials using artificial neural networks , 1995 .

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

[81]  J.C. Principe,et al.  Neural networks for EEG signal decomposition and classification , 1995, Proceedings of 17th International Conference of the Engineering in Medicine and Biology Society.

[82]  T. Gasser,et al.  Transformations towards the normal distribution of broad band spectral parameters of the EEG. , 1982, Electroencephalography and clinical neurophysiology.

[83]  Nitish V. Thakor,et al.  Detection of EEG changes via a generalized Itakura distance , 1997, Proceedings of the 19th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. 'Magnificent Milestones and Emerging Opportunities in Medical Engineering' (Cat. No.97CH36136).

[84]  J. Gotman,et al.  Frequency content of EEG and EMG at seizure onset: possibility of removal of EMG artefact by digital filtering. , 1981, Electroencephalography and clinical neurophysiology.

[85]  C. Brunia,et al.  Event-related desynchronization related to the anticipation of a stimulus providing knowledge of results , 1999, Clinical Neurophysiology.

[86]  D. Beer Monitoring adequacy of anesthesia using spontaneous and evoked electroencephalographic activity , 1996 .

[87]  K. Bloch,et al.  Polysomnography: a systematic review. , 1997, Technology and health care : official journal of the European Society for Engineering and Medicine.

[88]  P. Raudzens INTRAOPERATIVE MONITORING OF EVOKED POTENTIALS , 1980, Annals of the New York Academy of Sciences.

[89]  A. Hasman,et al.  Piecewise analysis of EEGs using AR-modeling and clustering. , 1981, Computers and biomedical research, an international journal.

[90]  S Nishida,et al.  Method for recording short latency evoked potentials using an EKG artifact elimination procedure. , 1990, Journal of biomedical engineering.

[91]  Pierre J. M. Cluitmans,et al.  Non-linear Analysis Of Sensory Evoked Potentials , 1991, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society Volume 13: 1991.

[92]  Guideline Eleven: Guidelines for Intraoperative Monitoring of Sensory Evoked Potentials , 1994, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.

[93]  R Biscay,et al.  Multiresolution decomposition of non-stationary EEG signals: a preliminary study. , 1995, Computers in biology and medicine.

[94]  P. Lang,et al.  The effects of eye fixation and stimulus and response location on the contingent negative variation (CNV). , 1973, Biological psychology.

[95]  Ronald N. Bracewell The Hartley transform , 1986 .

[96]  I Korhonen,et al.  Building the IMPROVE Data Library. , 1997, IEEE engineering in medicine and biology magazine : the quarterly magazine of the Engineering in Medicine & Biology Society.

[97]  P. Young,et al.  Time series analysis, forecasting and control , 1972, IEEE Transactions on Automatic Control.

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

[99]  G Bodenstein,et al.  Computerized EEG pattern classification by adaptive segmentation and probability-density-function classification. Description of the method. , 1985, Computers in biology and medicine.

[100]  V. Reus,et al.  Mind and brain. , 1993, Science.

[101]  N Saranummi,et al.  Improving control of patient status in critical care. , 1997, IEEE engineering in medicine and biology magazine : the quarterly magazine of the Engineering in Medicine & Biology Society.

[102]  M I Mendel,et al.  Early components of the averaged electroencephalic response to constant level clicks during all-night sleep. , 1971, Journal of speech and hearing research.

[103]  G. Litscher,et al.  Brain-stem auditory evoked potential monitoring. Variations of stimulus artifact in brain death. , 1995, Electroencephalography and clinical neurophysiology.

[104]  B. Hannaford,et al.  Short Time Fourier Analysis of the Electromyogram: Fast Movements and Constant Contraction , 1986, IEEE Transactions on Biomedical Engineering.

[105]  Joachim Mocks,et al.  Correcting ocular artifacts in the EEG: A comparison of several methods , 1989 .

[106]  S. Henneberg,et al.  Autoregressive Modeling with Exogenous Input of Middle-Latency Auditory-Evoked Potentials to Measure Rapid Changes in Depth of Anesthesia , 1996, Methods of Information in Medicine.

[107]  Guidelines for Clinical Evoked Potential Studies , 1986 .

[108]  R. Barry,et al.  EOG correction: a new aligned-artifact average solution. , 1998, Electroencephalography and clinical neurophysiology.

[109]  M. Ferdjallah,et al.  Adaptive digital notch filter design on the unit circle for the removal of powerline noise from biomedical signals , 1994, IEEE Transactions on Biomedical Engineering.

[110]  Ronald G. Emerson,et al.  Spike detection II: automatic, perception-based detection and clustering , 1999, Clinical Neurophysiology.

[111]  T. Sloan,et al.  Evoked potential monitoring. , 1996, International anesthesiology clinics.

[112]  J. Cohen,et al.  On the number of trials needed for P300. , 1997, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[113]  J Gotman,et al.  Automatic EEG analysis during long-term monitoring in the ICU. , 1998, Electroencephalography and clinical neurophysiology.

[114]  O Ozdamar,et al.  Computer methods for on-line hearing testing with auditory brain stem responses. , 1990, Ear and hearing.

[115]  A.S. Gevins,et al.  Automated analysis of the electrical activity of the human brain (EEG): A progress report , 1975, Proceedings of the IEEE.

[116]  N Pradhan,et al.  A nonlinear perspective in understanding the neurodynamics of EEG. , 1993, Computers in biology and medicine.

[117]  H. Shapiro,et al.  Automated EEG processing for intraoperative monitoring: a comparison of techniques. , 1980, Anesthesiology.

[118]  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.

[119]  Milan Palus,et al.  Nonlinearity in normal human EEG: cycles, temporal asymmetry, nonstationarity and randomness, not chaos , 1996, Biological Cybernetics.

[120]  R. Erwin,et al.  Midlatency auditory evoked responses: differential effects of sleep in the human. , 1986, Electroencephalography and clinical neurophysiology.

[121]  S. Zeki The visual image in mind and brain. , 1992, Scientific American.

[122]  D. Liberati,et al.  A parametric method of identification of single-trial event-related potentials in the brain , 1988, IEEE Transactions on Biomedical Engineering.

[123]  K. Nieminen,et al.  A clinical description of the IMPROVE data library , 1997, IEEE Engineering in Medicine and Biology Magazine.

[124]  H Shibasaki,et al.  Clinical application of automatic integrative interpretation of awake background EEG: quantitative interpretation, report making, and detection of artifacts and reduced vigilance level. , 1996, Electroencephalography and Clinical Neurophysiology.

[125]  S. Park,et al.  TDAT-time domain analysis tool for EEG analysis , 1990, IEEE Transactions on Biomedical Engineering.

[126]  W. Gersch Spectral analysis of EEG's by autoregressive decomposition of time series , 1970 .

[127]  P M Patel,et al.  A comparison of the electrophysiologic characteristics of EEG burst-suppression as produced by isoflurane, thiopental, etomidate, and propofol. , 1996, Journal of neurosurgical anesthesiology.

[128]  J Gade,et al.  Collecting EEG signals in the IMPROVE Data Library. , 1997, IEEE engineering in medicine and biology magazine : the quarterly magazine of the Engineering in Medicine & Biology Society.

[129]  J S Barlow A general-purpose automatic multichannel electronic switch for EEG artifact elimination. , 1985, Electroencephalography and clinical neurophysiology.

[130]  J. Frost,et al.  Context-based automated detection of epileptogenic sharp transients in the EEG: elimination of false positives , 1989, IEEE Transactions on Biomedical Engineering.

[131]  E. Pöppel,et al.  Sensory information processing during general anaesthesia: effect of isoflurane on auditory evoked neuronal oscillations. , 1991, British journal of anaesthesia.

[132]  Gerhard Litscher,et al.  Neurophysiologische Signalableitung. Neue technische und praxisbezogene Aspekte zu EEG-Ableiteelektroden - Neurophysiological Signal Recording. EEG Electrodes: New Technical and Practical Aspects , 1996 .

[133]  Jari P. Kaipio,et al.  Simulation of nonstationary EEG , 1997, Biological Cybernetics.

[134]  Emmanuel Ifeachor,et al.  Intelligent artefact identification in electroencephalography signal processing , 1997 .

[135]  Pjm Pierre Cluitmans,et al.  Neurophysiological monitoring of anesthetic depth , 1990 .

[136]  D L Woods,et al.  Differential auditory processing continues during sleep. , 1991, Electroencephalography and clinical neurophysiology.

[137]  P. Prior,et al.  The rationale and utility of neurophysiological investigations in clinical monitoring for brain and spinal cord ischaemia during surgery and intensive care. , 1996, Computer methods and programs in biomedicine.

[138]  G. Faye Boudreaux-Bartels,et al.  Time-Frequency Signal Representations for Biomedical Signals , 1999 .

[139]  F D Dunstan,et al.  The detection of artefacts in EEG series. , 1991, Statistics in medicine.

[140]  R. Bickford,et al.  Brain stem auditory evoked potentials: the use of noise estimate. , 1980, Electroencephalography and clinical neurophysiology.

[141]  V. Goel,et al.  Auto-regressive analysis of EEG reveals brain's response to injury , 1994, Proceedings of 16th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[142]  O. Ozdamar,et al.  Automated auditory brainstem response interpretation , 1994, IEEE Engineering in Medicine and Biology Magazine.

[143]  A Värri,et al.  A computerized analysis system for vigilance studies. , 1992, Computer methods and programs in biomedicine.

[144]  R Benlamri,et al.  An automated system for analysis and interpretation of epileptiform activity in the EEG , 1997, Comput. Biol. Medicine.

[145]  A Hasman,et al.  Piece-wise EEG analysis: an objective evaluation. , 1981, International journal of bio-medical computing.

[146]  J. Gotman Automatic recognition of epileptic seizures in the EEG. , 1982, Electroencephalography and clinical neurophysiology.

[147]  J Gotman,et al.  State-dependent spike detection: concepts and preliminary results. , 1991, Electroencephalography and clinical neurophysiology.

[148]  R. Barry,et al.  EOG correction: a new perspective. , 1998, Electroencephalography and clinical neurophysiology.

[149]  N. Thakor,et al.  Higher-order spectral analysis of burst patterns in EEG , 1999, IEEE Transactions on Biomedical Engineering.

[150]  F. Duffy,et al.  Spike detection. I. Correlation and reliability of human experts. , 1996, Electroencephalography and clinical neurophysiology.

[151]  J Persson Comments on estimations and tests of EEG amplitude distributions. , 1974, Electroencephalography and clinical neurophysiology.

[152]  B. Hjorth EEG analysis based on time domain properties. , 1970, Electroencephalography and clinical neurophysiology.

[153]  J. Victor,et al.  A new statistic for steady-state evoked potentials. , 1991, Electroencephalography and clinical neurophysiology.

[154]  L Korpinen,et al.  Evaluation of Epilepsy Expert--a decision support system. , 1994, Computer methods and programs in biomedicine.

[155]  M.T. Hagan,et al.  Multireference adaptive noise canceling applied to the EEG , 1997, IEEE Transactions on Biomedical Engineering.

[156]  IEEE Spectrum , 2022 .

[157]  Boualem Boashash,et al.  Preprocessing noisy EEG data using time-frequency peak filtering , 1993, Proceedings of the 15th Annual International Conference of the IEEE Engineering in Medicine and Biology Societ.

[158]  D. Dutt Spectral estimation of EEG signals using cascaded inverse filters. , 1994, International journal of bio-medical computing.

[159]  S Cerutti,et al.  Non-linear algorithms for processing biological signals. , 1996, Computer methods and programs in biomedicine.

[160]  Xuan Kong,et al.  Quantification of injury-related EEG signal changes using distance measures , 1999, IEEE Transactions on Biomedical Engineering.

[161]  B. Kemp,et al.  A proposal for computer‐based sleep/wake analysis , 1993, Journal of sleep research.

[162]  J. Tukey,et al.  An algorithm for the machine calculation of complex Fourier series , 1965 .

[163]  M. Cohen,et al.  Improving evoked response audiometry with special reference to the use of machine scoring. , 1974, Audiology : official organ of the International Society of Audiology.

[164]  C. Thomsen,et al.  Assessment of anaesthetic depth by clustering analysis and autoregressive modelling of electroencephalograms. , 1991, Computer methods and programs in biomedicine.

[165]  N. Burch,et al.  Period analytic estimates of moments of the power spectrum: a simplified EEG time domain procedure. , 1971, Electroencephalography and clinical neurophysiology.

[166]  J A Sgro,et al.  Phase synchronized triggering: a method for coherent noise elimination in evoked potential recording. , 1985, Electroencephalography and clinical neurophysiology.

[167]  Lotfi Senhadji,et al.  On some time-frequency signatures in stereo-electroencephalography (SEEG) , 1996, Proceedings of 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[168]  John W. Dalle Molle,et al.  Trispectral analysis of stationary random time series , 1995 .

[169]  J. Intriligator,et al.  On the relationship between EEG and ERP variability. , 1995, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[170]  C. Brunia Stimulus Preceding Negativity: Arguments in Favour of Non Motoric Slow Waves , 1993 .

[171]  B H Jansen,et al.  Quantitative analysis of electroencephalograms: is there chaos in the future? , 1991, International journal of bio-medical computing.

[172]  G. Litscher,et al.  Burst-Suppression-Erkennung beim pEEG - Detection of Burst Suppression in the pEEG , 1997 .

[173]  B S Oken,et al.  Filtering and aliasing of muscle activity in EEG frequency analysis. , 1986, Electroencephalography and clinical neurophysiology.

[174]  P K Sadasivan,et al.  Minimization of EOG artefacts from corrupted EEG signals using a neural network approach. , 1994, Computers in biology and medicine.

[175]  F. Sharbrough,et al.  Nonpathologic Factors Influencing Brainstem Auditory Evoked Potentials , 1978 .

[176]  M Scherg,et al.  Distortion of the middle latency auditory response produced by analog filtering. , 1982, Scandinavian audiology.

[177]  A Värri,et al.  Evaluation of a computerized system for recognition of epileptic activity during long-term EEG recording. , 1994, Electroencephalography and clinical neurophysiology.

[178]  Identification of EEG patterns occurring in anesthesia by means of autoregressive parameters. , 1991, Biomedizinische Technik. Biomedical engineering.

[179]  N. Kawabata A nonstationary analysis of the electroencephalogram. , 1973, IEEE transactions on bio-medical engineering.

[180]  I Pichlmayr,et al.  Testing the Gaussianity of the Human EEG During Anesthesia , 1992, Methods of Information in Medicine.

[181]  John S. Barlow,et al.  Computerized Clinical Electroencephalography in Perspective , 1979, IEEE Transactions on Biomedical Engineering.

[182]  R. Schmidt Integrative Functions of the Central Nervous System , 1985 .

[183]  R. Tammana,et al.  An Artificial Neural-Network Approach to ERP Classification , 1995, Brain and Cognition.

[184]  S Nishida,et al.  Method for single-trial recording of somatosensory evoked potentials. , 1993, Journal of biomedical engineering.

[185]  I. Lesný,et al.  [Principles of electroencephalography]. , 1953, Prakticky lekar.

[186]  N. Kraus,et al.  High-pass filter settings affect the detectability of MLRs in humans. , 1987, Electroencephalography and clinical neurophysiology.

[187]  H. Akaike A new look at the statistical model identification , 1974 .

[188]  A S Gevins,et al.  On-line computer rejection of EEG artifact. , 1977, Electroencephalography and clinical neurophysiology.

[189]  B. Jansen,et al.  Single trial evoked potential analysis by means of crosscorrelation and dynamic time-warping , 1986 .

[190]  M. Hansson,et al.  Estimation of single event-related potentials utilizing the Prony method , 1996, IEEE Transactions on Biomedical Engineering.

[191]  E. Sedgwick,et al.  Evoked Potential Primer: Visual, Auditory, and Somatosensory Evoked Potentials in Clinical Diagnosis , 1987 .

[192]  P. Cluitmans,et al.  Haemodynamic responses to incision and sternotomy in relation to the auditory evoked potential and spontaneous EEG. , 1996, British journal of anaesthesia.

[193]  G. Bodenstein,et al.  Feature extraction from the electroencephalogram by adaptive segmentation , 1977, Proceedings of the IEEE.

[194]  Martti Juhola,et al.  Latency estimation of auditory brainstem response by neural networks , 1997, Artif. Intell. Medicine.

[195]  Richard Aufrichtig,et al.  Order estimation and model verification in autoregressive modeling of EEG sleep recordings , 1992, 1992 14th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[196]  C. Thomsen,et al.  Quantitative EEG in assessment of anaesthetic depth: comparative study of methodology. , 1996, British journal of anaesthesia.

[197]  Alpo Värri,et al.  Weighted FMH filters , 1993, Signal Process..

[198]  J R Bourne,et al.  Identification and labeling of EEG graphic elements using autoregressive spectral estimates. , 1982, Computers in biology and medicine.

[199]  M Juhola,et al.  On digital filtering of auditory brainstem responses. , 1993, Medical progress through technology.

[200]  M. Todd,et al.  EEGs, EEG processing, and the bispectral index. , 1998, Anesthesiology.

[201]  P. Jayakar,et al.  Artifacts in ambulatory cassette electroencephalograms. , 1985, Electroencephalography and Clinical Neurophysiology.

[202]  R Summers,et al.  Using artificial neural networks for classifying ICU patient states. , 1997, IEEE engineering in medicine and biology magazine : the quarterly magazine of the Engineering in Medicine & Biology Society.

[203]  T. Gasser,et al.  Test-retest reliability of spectral parameters of the EEG. , 1985, Electroencephalography and clinical neurophysiology.

[204]  R. Bender,et al.  Reduktion der Anzahl von EEG-Ableitungen für ein routinemäßiges Monitoring auf der Intensivstation - Electroencephalographic Monitoring in the ICU - Reduction of the Number of Recorded Channels , 1992 .

[205]  B Kemp,et al.  Simulation of human hypnograms using a Markov chain model. , 1986, Sleep.

[206]  W J Levy,et al.  Effect of Epoch Length on Power Spectrum Analysis of the EEG , 1987, Anesthesiology.

[207]  Neurologische Klinik,et al.  Neurophysiologisches Monitoring bei neurochirurgischen Gefäßoperationen: Spezifische technische Anforderungen und deren Umsetzung , 1992 .

[208]  L. Gupta,et al.  Nonlinear alignment and averaging for estimating the evoked potential , 1996, IEEE Transactions on Biomedical Engineering.

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

[210]  F. H. Lopes da Silva,et al.  Event-related potentials: methodology and quantification , 1998 .

[211]  É. Moulines,et al.  Testing that a stationary time-series is Gaussian: time-domain vs. frequency-domain approaches , 1993, [1993 Proceedings] IEEE Signal Processing Workshop on Higher-Order Statistics.

[212]  W.R. Fright,et al.  A multistage system to detect epileptiform activity in the EEG , 1993, IEEE Transactions on Biomedical Engineering.

[213]  K. Lowy,et al.  Assessing the significance of averaged evoked potentials with an on-line computer: the split-sweep method. , 1968, Electroencephalography and clinical neurophysiology.

[214]  R A Pronk,et al.  Interference suppression for EEG recording during open heart surgery. , 1979, Electroencephalography and clinical neurophysiology.

[215]  Reexamination of effects of stimulus rate and number on the middle components of the averaged electroencephalic response. , 1975, Audiology : official organ of the International Society of Audiology.

[216]  Antoine Rémond,et al.  Clinical Applications of Computer Analysis of Eeg and Other Neurophysiological Signals , 1987 .

[217]  H. Schimmel The (�) Reference: Accuracy of Estimated Mean Components in Average Response Studies , 1967, Science.

[218]  J. S. Barlow,et al.  Muscle spike artifact minimization in EEGs by time-domain filtering. , 1983, Electroencephalography and clinical neurophysiology.

[219]  C Tomberg,et al.  Inadequacy of the average reference for the topographic mapping of focal enhancements of brain potentials. , 1990, Electroencephalography and clinical neurophysiology.

[220]  Guideline Thirteen: Guidelines for Standard Electrode Position Nomenclature , 1994, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.

[221]  F. L. D. Silva,et al.  EEG analysis: Theory and Practice , 1998 .

[222]  T. Picton,et al.  Evaluation of brain-stem auditory evoked potentials using dynamic time warping. , 1988, Electroencephalography and clinical neurophysiology.

[223]  J. Gotman,et al.  State dependent spike detection: validation. , 1992, Electroencephalography and clinical neurophysiology.

[224]  M. S. Mobin,et al.  Weighted averaging of evoked potentials , 1992, IEEE Transactions on Biomedical Engineering.

[225]  C Elberling,et al.  Quality estimation of averaged auditory brainstem responses. , 1984, Scandinavian audiology.

[226]  H. Lilliefors On the Kolmogorov-Smirnov Test for Normality with Mean and Variance Unknown , 1967 .

[227]  M. R. Saatchi,et al.  Adaptive multiresolution analysis based evoked potential filtering , 1997 .

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

[229]  F H Duffy,et al.  Status of Quantitative EEG (QEEG) in Clinical Practice, 1994 , 1994, Clinical EEG.

[230]  M Hoke,et al.  Weighted averaging--theory and application to electric response audiometry. , 1984, Electroencephalography and clinical neurophysiology.

[231]  J. Robert Boston,et al.  Spectra of Auditory Brainstem Responses and Spontaneous EEG , 1981, IEEE Transactions on Biomedical Engineering.

[232]  J.R. Boston,et al.  Automated interpretation of brainstem auditory evoked potentials: a prototype system , 1989, IEEE Transactions on Biomedical Engineering.

[233]  C Thornton,et al.  Evoked responses in anaesthesia. , 1998, British journal of anaesthesia.

[234]  Donald W. Klass,et al.  The Continuing Challenge of Artifacts in the EEG , 1995 .

[235]  B. L. Grundy Monitoring of sensory evoked potentials during neurosurgical operations: methods and applications. , 1982, Neurosurgery.

[236]  Richard D. Jones,et al.  The self-organising feature map in the detection of epileptiform transients in the EEG , 1996, Proceedings of 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[237]  J A Swets,et al.  Measuring the accuracy of diagnostic systems. , 1988, Science.

[238]  M M Cohen,et al.  Improving evoked response audiometry. Results of normative studies for machine scoring. , 1975, Audiology : official organ of the International Society of Audiology.

[239]  F. L. D. Silva,et al.  Dynamics of EEGs as signals of neuronal populations: models and theoretical considerations , 1998 .

[240]  P. Husar,et al.  Bispectrum analysis of visually evoked potentials , 1997, IEEE Engineering in Medicine and Biology Magazine.

[241]  J Persson,et al.  Comments on "Modeling the stationarity and Gaussianity of spontaneous electroencephalographic activity". , 1977, IEEE transactions on bio-medical engineering.

[242]  W R Webber,et al.  Practical detection of epileptiform discharges (EDs) in the EEG using an artificial neural network: a comparison of raw and parameterized EEG data. , 1994, Electroencephalography and clinical neurophysiology.

[243]  D. Pierce Testing normality in autoregressive models , 1985 .

[244]  G. Alarcón,et al.  Power spectrum and intracranial EEG patterns at seizure onset in partial epilepsy. , 1995, Electroencephalography and clinical neurophysiology.

[245]  C Elberling,et al.  Objective detection of averaged auditory brainstem responses. , 1984, Scandinavian audiology.

[246]  M Scherg,et al.  Simultaneous recording and separation of early and middle latency auditory evoked potentials. , 1982, Electroencephalography and clinical neurophysiology.

[247]  J S Barlow Automatic elimination of electrode-pop artifacts in EEG's. , 1986, IEEE transactions on bio-medical engineering.

[248]  Event-related potentials as indirect measures of recognition memory. , 1996, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[249]  P A Parker,et al.  Stimulus artifact reduction in evoked potential measurements. , 1996, Archives of physical medicine and rehabilitation.

[250]  T. Gasser Goodness-of-fit tests for correlated data , 1975 .

[251]  L P Panych,et al.  Practical digital filters for reducing EMG artefact in EEG seizure recordings. , 1989, Electroencephalography and clinical neurophysiology.

[252]  Derek A. Linkens,et al.  Intelligent signal processing of evoked potentials for anaesthesia monitoring and control , 1997 .