Method and system for analysis of long term physiological polygraphic recordings

• US 5,047,930 A
• Filed: 06/26/1987
• Issued: 09/10/1991
• Est. Priority Date: 06/26/1987
• Status: Expired due to Fees

• Current Assignee: Nicolet Instrument Corporation
• Original Assignee: Nicolet Instrument Corporation
• Inventors: Martens, Wim L. J., Kap, Jaap I.
• Primary Examiner(s): Smith, Jerry
• Assistant Examiner(s): Tbui, Kim Thanh
• Application Number:
  US07/067,765
• Time in Patent Office: 1,537 Days
• Field of Search: 364/415, 364/413.01, 364/413.04, 364/413.03, 364/413.05, 364/413.06, 128/1 R, 128/733, 128/731, 128/745
• US Class Current: 600/301
• CPC Class Codes: A61B 5/369 Electroencephalography [EEG] devices for psychotechnics A61B5/16
• CPC Class Codes: A61B 5/389 Electromyography [EMG]
• CPC Class Codes: A61B 5/398 Electrooculography [EOG], e.g. detecting nystagmus; Electroretinography [ERG]
• CPC Class Codes: A61B 5/4809 Sleep detection, i.e. determining whether a subject is asleep or not
• CPC Class Codes: A61B 5/4812 Detecting sleep stages or cycles
• CPC Class Codes: A61B 5/4818 Sleep apnoea
• CPC Class Codes: A61B 5/7257 using Fourier transforms
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: G16H 40/63 for local operation
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: Y10S 128/92 Computer assisted medical diagnostics
• CPC Class Codes: Y10S 706/924 Medical

Abstract

An analysis system accepts physiological sensor signals, including electroencephalogram (EEG) and other signals commonly sensed in sleep analysis, stores the raw data for later retrieval, extracts features from the digitized signal data which are of a type apt to be significant in classifying and detecting physiological functions (such as the state of sleep) and matches the extracted features to patterns which indicate the type of feature that has been extracted. The matched features are then utilized to classify for each epoch (limited period of time) the state of the physiological function (such as the stage of sleep) for that epoch. The results of the classification analysis are displayed on a CRT screen to the operator on a real time basis and in time correlation with representations of detected features from the various physiological signals. Upon completion of the tests, the operator can interact with the system to change the patterns by which the features are matched and the classification criteria, and can then re-analyze the data and have it redisplayed to demonstrate the results of the re-analysis. In this manner, the operator can interactively utilize his judgment to provide a classification result which is satisfactory to him and which is particularly adapted to the individual subject under test.

Claims

1. A method of analyzing physiological signals obtained from physiological sensor on a subject, comprising the steps of:

(a) receiving the time varying physiological signals from the sensors on the subject;

(b) digitizing the physiological signals to provide digital physiological signal data;

(c) storing the digitized physiological signal data in correlation with time and making such data available for later retrieval;

(d) analyzing the physiological signal data on a real time basis to detect patterns therein indicating fluctuations in physiological function;

(e) displaying to an operator the results of the analysis on a real time basis as the data is being received from the subject;

(f) after completion of the taking of physiological data from the subject, displaying to the operator the final results of the analysis based on all the data taken;

(g) re-analyzing the physiological data stored for long term retrieval after specification by the operator of new criteria determining fluctuations is physiological function;

wherein the step of analyzing data on a real time basis and the step of re-analyzing the stored data each includes the steps of extracting significant features from the background nonsignificant features of the time varying data, comparing the extracted features with respect to model patterns to categorize the extracted features, and classifying a particular time epoch within which such categorized patterns are found into a class depending on which class has criteria which most closely match the categorized patterns for the particular time epoch.

2. The method of claim 1 wherein the features are extracted for time epochs of selected duration, and the features matched to the patterns are compared to the classification criteria to classify the physiological function for each epoch at a time.

3. The method of claim 1 wherein the step of feature extraction includes the steps of determining a threshold magnitude level and saving those portions of the waveform data which have peaks above the amplitude threshold level.

4. The method of claim 3 wherein the step of determining a threshold level is performed over preselected periods of time constituting epochs, and wherein for each epoch the threshold is calculated as a function of the magnitudes of the peaks of the waveform in the EEG signal over the epoch.

5. The method of claim 4 wherein the threshold level is set to the mean amplitude of the magnitude of the peaks found in each epoch.

6. The method of claim 1 wherein the step of classification in re-analysis includes the step of displaying to the operator a matrix of emulated classification rules having characterizing parameters listed on one axis of the matrix and classes on the other axis of the matrix, and wherein reference levels and rules are displayed to the operator in the matrix elements for the initial analysis, and including the step of receiving input from the operator to change the reference level or rule indicated in the elements of the matrix to a level or rule desired by the operator and then analyzing the data utilizing the new set of reference levels and rules as modified by the operator to carry out the classification.

7. A method of analyzing physiological signals obtained from physiological sensors on a subject, comprising the steps of:

(a) receiving the time varying physiological signals from the sensors on the subject;

(b) digitizing the physiological signals to provide digital physiological signal data;

(c) extracting features from the digital physiological signal data which meet amplitude and frequency thresholds indicative of potential significant signal patterns on a real time basis during each epoch of selected duration during which the signals are received;

(d) storing the extracted features for each epoch in correlation with the position of the epoch in time and making such data available for retrieval at a later time;

(e) detecting patterns on an epoch by epoch basis in the extracted features to match the features with preselected pattern detection criteria indicative of significant physiological events;

(f) classifying the state of a physiological function for the subject for each epoch on a comparison between the detected patterns for such epoch and classification criteria;

(g) displaying to the operator in graphic format the results of the classification on a real time basis for each epoch including the most recently classified epoch; and

(h) after completion of the taking of physiological data from the subject, re-detecting the patterns from the extracted features which are retrieved from storage after specification by the operator of new pattern detection criteria, reclassifying the matched patterns with respect to the set of classification criteria for each epoch, and displaying the results of the classification to the operator.

8. The method of claim 7 wherein the physiological signals which are sensed include at least one EEG signal, and wherein the step of feature extraction includes separating the time varying EEG signal data into a plurality of signals corresponding to frequency bands generally conforming to the frequencies of standard EEG waveform components including delta waves, theta waves, alpha waves, beta waves, and sleepspindles.

9. The method of claim 7 wherein the step of classifying comprises comparing the detected patterns with classification criteria for the five stages of sleep and awake and classifying each epoch of time into one of the five classes of sleep or awake depending on which criteria are met by the detected patterns for that epoch.

10. The method of claim 9 wherein the detected patterns for each epoch include some or all of the magnitude of delta waves, the magnitude of theta waves, the presence of theta bursts, the magnitude of alpha waves, the magnitude of beta waves, the presence and number of K-complexes, the presence and number of Sleepspindles, the presence and number of Sharp Waves, the presence of and number Rapid Eye Movements, and the magnitude of EMG taken at the chin.

11. A method of analyzing physiological signals obtained from physiological sensors on a subject, comprising the steps of:

(a) receiving the time varying physiological signals from the sensor on the subject;

(b) digitizing the physiological signals to provide digital physiological signal data;

(c) extracting features from the digital physiological signal data which meet amplitude and frequency thresholds indicative of potential significant signal patterns on a real time basis during each epoch of selected duration which the data is received;

(d) storing the extracted features for each epoch in correlation with the position of the epoch in time and making such data available for retrieval at a later time;

(e) detecting patterns on an epoch by epoch basis in the extracted features to match the features with preselected pattern detecting criteria indicative of significant physiological events;

(f) classifying the state of a physiological function for the subject for each epoch based on a comparison between the detected patterns for such epoch and classification criteria;

(g) displaying to the operator in graphic format the results of the classification on a real time basis for each epoch including the most recently classified epoch; and

(h) after completion of the taking of physiological data from the subject, re-detecting patterns from the feature extracted data received from storage and reclassifying the detected patterns in accordance with a new classification criteria specified by the operator and displaying the results of the reclassification to the operator.

12. A method of analyzing physiological signals obtained from physiological sensors on a subject including at least one EEG signal, comprising the steps of:

(a) receiving the time varying physiological signals from the sensors on the subject;

(b) analyzing the physiological signal data to detect patterns therein indicating fluctuations in physiological function including at least the stages of sleep, and providing a classification of the stages of sleep over time based on the patterns detected when the patterns are matched with a set of classification criteria which denote the five stages of sleep and awake;

(c) displaying to an operator the results of the analysis including a hypnogram of sleep stages as a function of time;

(d) also displaying to an operator a matrix of emulated classification rules having characterizing parameters listed on one axis of the matrix and classes on the other axis of the matrix and wherein reference levels and rules are indicated in the matrix elements to the operator for the initial analysis which produced the initial sleep stage classification;

(e) receiving input from the operator to change a reference level or rule indicated in the elements of the matrix to a level or rule desired by the operator; and

the

(f) re-analyzing the data utilizing the new set of reference levels and rules as modified by the operator to carry out classification and redisplaying the results of the analysis including a hypnogram of sleep stages as a function of time.

13. A method of analyzing physiological signals obtained from physiological sensors on a subject, comprising the steps of:

(a) receiving the time varying physiological signals from the sensors on the subject;

(b) analyzing the physiological signal data to detect patterns therein indicating fluctuations in physiological function including at least the stages of sleep, and providing a classification of the stages of sleep over time based on the patterns detected when the patterns are matched with a set of classification criteria which denote the five stages of sleep and awake;

(c) displaying to the operator the classification of sleep in the various stages as a function of time in a hypnogram extending along one axis and simultaneously displaying to the operator indications of the time changes of various physiological signal patterns on axes which are parallel to the time axis for the hypnogram and correlated therewith in time, the physiological signals displayed being selected from the group consisting of EEG, Rapid Eye Movements over time epochs, EMG taken from the chin of the subject, EMG taken from the legs of the subject, intercostal EMG, heart rate, oxygen saturation level, carbon dioxide saturation level, respiration, and combinations thereof; and

(d) accepting a designation from the operator of a specific point in time along the correlated displays of the hypnogram and the other physiological functions and, at the command of the operator, providing an auxiliary display of the hypnogram and other physiological functions on an expanded time scale so that horizontal magnification is provided to increase the horizontal resolution of data in a selected vicinity of the point in time chosen by the operator.

14. A method of analyzing physiological signals obtained from physiological sensor on a subject, comprising the steps of:

(a) receiving the time varying physiological signals from the sensors on the subject;

(b) analyzing the physiological signal data to detect patterns therein indicating fluctuations in physiological function including at least the stages of sleep, and providing a classification of the stages of sleep over time based on the patterns detected when matched with a set of classification criteria which denote the five stages of sleep and awake;

(c) displaying to the operator the classification of sleep in the various stages as a function of time in a hypnogram extending along one axis and simultaneously displaying to the operator indications of the time changes of various physiological signal patterns on axes which are parallel to the time axis for the hypnogram and correlated therewith in time, the physiological signals displayed being selected from the group consisting of EEG, Rapid Eye Movements over time epochs, EMG taken from the chin of the subject, EMG taken from the legs of the subject, intercostal EMG, heart rate, oxygen saturation level, carbon dioxide saturation level, respiration, and combinations thereof; and

(d) accepting input from the operator to select a chosen point in time along the hypnogram and the other physiological functions displayed and, at the command of the operator, providing a display in time correlation along parallel axes of the raw data signals in the vicinity of the point in time selected by the operator which were received from the physiological sensors.

15. A method of analyzing physiological signals obtained from physiological sensors on a subject, comprising the steps of;

(a) receiving the time varying physiological signals from the sensors on the subject;

(b) analyzing the physiological signal data to detect patterns therein indicating fluctuations in physiological function including at least the stages of sleep, and providing a classification of the stages of sleep over time based on the patterns detected when matched with a set of classification criteria which denotes the five stages of sleep and wake;

(c) displaying to the operator the classification of sleep in the various stages as a function of time in a hypnogram extending along one axis and simultaneously displaying to the operator indications of the time change of various physiological signal patterns on axes which are parallel to the time axis for the hypnogram and correlated therewith in time, the physiological signals displayed being selected from the group consisting of EEG, Rapid Eye Movements over time epochs, EMG taken from the chin of the subject, EMG taken from the legs of the subject, intercostal EMG, heart rate, oxygen saturation level, carbon dioxide saturation level, respiration, and combination thereof, wherein among the signals displayed in time correlation with the hypnogram is at least one channel of EEG physiological functions, and wherein the EEG signal is displayed in a quasi-3 dimensional representation with a third dimensional display extending away from the time axis corresponding to frequency bands including the frequency bands conventionally associated with alpha waves, beta waves, delta waves, theta waves, and sleepspindles.

16. A method of analyzing physiological signals obtained from physiological sensors on a subject comprising the steps of:

(a) receiving the time varying physiological signals from the sensors on the subject;

(b) analyzing the physiological signal data to detect patterns therein indicating fluctuations in physiological function including at least the stages of sleep, and providing a classification of the stages of sleep over time based on the patterns detected when matched with a set of classification criteria which denote the five stages of sleep and awake;

(c) displaying to the operator the classification of sleep in the various stages as a function of time in a hypnogram extending along one axis and simultaneously displaying to the operator indications of the time changes of various physiological signal patterns on axes which are parallel to the time axis for the hypnogram and correlated therewith in time, the physiological signals displayed being selected from the group consisting of EEG, Rapid Eye Movements over time epochs, EMG taken from the chin on the subject, EMG taken from the legs of the subject, intercostal EMG, heart rate, oxygen saturation level, carbon dioxide saturation level, respiration, and combinations thereof, and wherein the analysis is preformed on a real time basis on the physiological signals and a display is provided of the hypnogram and the associated physiological functions in time correlation therewith in a cumulative fashion between the start of the test and the current time, and further including a display on an expanded time scale of the results of the analysis for a recent segment of input signals shown with the hypnogram on an expanded time scale and physiological therewith also on an expanded time scale.

17. The method of claim 16 wherein the method is performed on more than one subject simultaneously and the results are displayed to the operator on a CRT screen with the screen divided up so that separate sections of the screen displays the time correlated results for each of the subjects.

18. A method of analyzing and displaying physiological signals obtained from physiological sensors on a subject, comprising the steps of:

(a) receiving the time varying physiological signals from the sensors on the subject;

(b) digitizing the physiological signals to provide digital physiological signals data;

(c) storing the digitized physiological signal data in correlation with time and making such data available for later retrieval;

(d) simultaneously analyzing the physiological signal data on a real time basis to detect patterns therein indicating fluctuations in physiological functions;

(e) displaying to an operator the results of the analysis showing fluctuations in physiological function over time;

(f) accepting an indication from the operator of a point in time on the displayed analysis results and, at the command of the operator, providing a display on a CRT screen to the operator of the raw physiological data from the sensors, retrieved from storage, gathered in the vicinity of the point in time designated by the operator, the raw physiological data from each sensor being displayed in time correlated relationship with the data displayed for the other sensors, and, further, at the command of the operator, moving the physiological data displayed on the screen backwardly or forwardly in time to transfer representations to the screen of the physiological data at either an earlier or a later time under the control of the operator.

19. The method of claim 18 wherein the physiological signal data displayed to the operator moves continuously across the CRT screen to continuously scan the stored signal data and display it in contiunous motion to the operator at the operator'"'"'s command.

20. The method of claim 19 wherein the physiological signal data displayed to the operator at the operator'"'"'s command is moved in page-like time segments either backwardly or forwardly in time so that an entire CRT screen of physiological signal representations are changed each time the operator chooses to change the display signal data.

21. The method of claim 18 including the additional step of accepting operator input on an epoch by epoch basis to allow the operator to designate sleep stages within an epoch corresponding to the particular raw physiological signal data displayed on the screen.

22. A system for analyzing physiological signals obtained from physiological sensors on a subject, comprising:

(a) means for receiving the time varying physiological signals from the sensors on the subject and for digitizing the signals to provide digital physiological signal data;

(b) means for storing the digitized physiological signal data in correlation with time and making such data available for later retrieval;

(c) analysis means receiving the digital physiological signal data for analyzing the data on a real time basis to detect patterns therein indicating fluctuations in physiological function, wherein the analysis means includes means for extracting significant features from the background non-significant features of the time varying digital physiological signal data, means for comparing the extracted features with respect to model patterns to categorize the extracted features, and means for classifying a particular time epoch in which such categorized patterns are found into a class depending on which class has criteria which most closely match the categorized patterns for the particular time epoch;

(d) display means for displaying to an operator the results of the analysis from the analysis means on a real time basis;

(e) input means receiving commands from the operator for providing new criteria specifications from the operator to the analysis means such that the analysis means reanalyzes the physiological data stored for long term retrieval utilizing the new criteria determining fluctuations in physiological function.

23. The system of claim 22 wherein the means for feature extraction in the analysis means includes means for determining a threshold magnitude level and for saving those portions of the waveform data which have peaks above the amplitude threshold level.

24. The system of claim 23 wherein the means for determining a threshold level performs the determination over pre-selected periods of time constituting epochs, and wherein for each epoch the threshold is calculated as a function of the magnitudes of the peaks of the waveform in the EEG signal over the epoch.

25. A system for analyzing physiological signals obtained from physiological sensors on a subject comprising:

(a) means for receiving the time varying physiological signals from the sensor on the subject and digitizing the physiological signals to provide digital physiological signal data;

(b) means for extracting features from the digital physiological signal data which meet amplitude and frequency thresholds indicative of potential significant signal patterns during each epoch of selected duration during which the data is received;

(c) means for storing the extracted features for each epoch in correlation with the position of the epoch in time and making such data available for retrieval at a later time;

(d) means receiving the extracted features data for detecting patterns on an epoch by epoch basis in the extracted features to match the features with preselected pattern detection criteria indicative of physiological events;

(e) classification means for classifying the state of a physiological function for the subject for each epoch based on a comparison between the detected patterns for such epoch and classification criteria;

(g) display means for displaying to the operator in graphic format the results of the classification by the classification means; and

(h) means for re-detecting the patterns from the extracted features which are retrieved from storage after specification by the operator of new pattern detection criteria and for reclassifying the matched patterns with respect to the set of classification criteria for each epoch, and wherein the display means displays the results of the classification to the operator.

26. A system for analyzing physiological signals obtained from physiological sensors on a subject, comprising:

(a) means for receiving the time varying physiological signals from the sensors on the subject and digitizing the physiological signals to provide digital physiological signal data;

(b) means for extracting features from the digital physiological signal data which meet amplitude and frequency thresholds indicative of potential significant signal patterns on a real time basis during each epoch of selected duration during which the data is received;

(c) means for storing the extracted features for each epoch in correlation with the position of the epoch in time and making such data available for retrieval at a later time;

(d) means receiving the extracted features data for detecting patterns on an epoch by epoch basis in the extracted features to match the features with preselected pattern detection criteria indicative of physiological events;

(e) classification means for classifying the state of a physiological function for the subject for each epoch based on a comparison between the detected patterns for such epoch and classification criteria;

(g) display means for displaying to the operator in graphic format the results of the classification by the classification means initially on a real time basis for each epoch including the most recently classified epoch; and

(h) means for re-detecting patterns from the feature extracted data retrieved from the storage means and reclassifying the detected patterns in accordance with a new classification criteria specified by the operator, wherein the display means displays the results of the reclassification to the operator.

27. A system for analyzing physiological signals obtained from physiological sensors on a subject, comprising:

(a) means for receiving the time varying physiological signals from the sensors on the subject and digitizing the physiological signals to provide digital physiological signal data;

(b) means for extracting features from the digital physiological signal data which meet amplitude and frequency thresholds indicative of potential significant signal patterns during each epoch of selected duration during which the data is received, wherein the physiological signals which are received include at least one EEG signal, and wherein the means for extracting features includes means for separating the time varying EEG signal data into a plurality of signals corresponding to the frequency bands generally conforming to the frequencies of standard EEG waveform components, including delta waves, theta waves, alpha waves, beta waves, and sleepspindles;

(c) means for storing the extracted features for each epoch in correlation with the position of the epoch in time and making such data available for retrieval at a later time;

(d) means receiving the extracted features data for detecting patterns on an epoch by epoch basis in the extracted features to match the features with preselected pattern detection criteria indicative of physiological events;

(e) classification means for classifying the state of a physiological function for the subject for each epoch based on a comparison between the detected patterns for such epoch and classification criteria;

(g) display means for displaying to the operator in graphic format the results of the classification by the classification means; and

(h) means for re-detecting the patterns from the extracted features which are retrieved from storage after specification by the operator of new pattern detection criteria and for reclassifying the matched patterns with respect to the set of classification criteria for each epoch, and wherein the display means displays the results of the classification to the operator.

28. A system for analyzing physiological signals obtained from physiological sensors on a subject, comprising:

(a) means for receiving the time varying physiological signals from the sensors on the subject and digitizing the physiological signals to provide digital physiological signal data;

(b) means for extracting features from the digital physiological signal data which meet amplitude and frequency thresholds indicative of potential significant signal patterns during each epoch of selected duration during which the data is received;

(c) means for storing the extracted features for each epoch in correlation with the position of the epoch in time and making such data available for retrieval at a later time;

(d) means receiving the extracted features data for detecting patterns on an epoch by epoch basis in the extracted features to match the features with preselected pattern detection criteria indicative of physiological events;

(e) classification means for classifying the state of a physiological function for the subject for each epoch based on a comparison criteria, wherein the classification means for classifying compares the detected patterns for such epoch and classification criteria, wherein the classification means for classifying compress the detected patterns with classification criteria for the five stages of sleep and awake and classifies each epoch of time into one of the five classes of sleep or awake depending on which criteria are met by the detected patterns for that epoch;

(g) display means for displaying to the operator in graphic format the results of the classification by the classification means; and

(h) means for re-detecting the patterns from the extracted features which are retrieved from storage after specification by the operator of new pattern detection criteria and for reclassifying the matched patterns with respect to the set of classification criteria for each epoch, and wherein the display means displays the results of the classification to the operator.

29. A system for analyzing physiological signals obtained from physiological sensor on a subject which include at least one EEG signal, comprising:

(a) means for receiving the time varying physiological signals from the sensors on the subject and digitizing the physiological signals to provide physiological signal data;

(b) analysis means for analyzing the digital physiological signal data to detect patterns therein indicating fluctuations in physiological function including at least the stages of sleep, and providing a classification of the stages if sleep over time based on the patterns detected when the patterns are matched with a set of classification criteria which denote the five stages of sleep and awake;

(c) display means for displaying to an operator the results of the analysis performed by the analysis means including a display of a hypnogram of sleep stages as a function of time;

(d) the display means also displaying to an operator a matrix of emulated classification rules having characterizing parameters listed on one axis of the matrix and classes on the other axis of the matrix and wherein reference levels and rules are indicated in the matrix elements to the operator for the initial analysis which produced the initial sleep stage classification; and

(e) input means for receiving input from the operator to change the reference levels or rules indicated in the elements of the displayed matrix to a level or rule desired by the operator and providing these levels or rules to the analysis means, the analysis means re-analyzing the data utilizing the new set of reference levels and rules as modified by the operator to carry out classification and the display means displaying to the operator the results of the analysis including a display of a hypnogram of sleep stages as a function of time.

30. A system for analyzing physiological signals obtained from physiological sensors on a subject, comprising:

(a) means for receiving the time varying physiological signals from the sensors on the subject and digitizing the physiological signals to provide digital physiological signal data;

(b) analysis means for analyzing the digital physiological signal data to detect patterns therein indicating fluctuations in physiological function including at least the stages of sleep, and providing a classification of the stages over time based on the patterns detected when the patterns are matched with a set of classification criteria which denote the five stages of sleep and awake;

(c) display means for displaying to the operator the classification of sleep as a function of time in a hypnogram extending along one axis and simultaneously displaying to the operator indications of the time changes of various physiological signal patterns on axes which are parallel to the time axes for the hypnogram and correlated therewith in time, the physiological signals displayed being selected from the group consisting of EEG, Rapid Eye Movements over time epochs, EMG taken from the chin of the subject, EMG taken from the legs of the subject, intercostal EMG, heart rate, oxygen saturation level, carbon dioxide saturation level, respiration, and combinations thereof; and

(d) input means for accepting a designation from the operator of a specific point in time along the correlated displays of the hypnogram and the physiological functions and, at the command of the operator, providing control signals to the analysis means such that the analysis means and display means provide an auxiliary display of the hypnogram and other physiological functions on an expanded time scale so that horizontal magnification is provided to increase the horizontal resolution of data in a selected vicinity of the point in time chosen by the operator.

31. A system for analyzing physiological signals obtained from physiological sensors on a subject, comprising:

(a) means for receiving the time varying physiological signals from the sensors on the subject and digitizing the physiological signals to provide digital physiological signal data;

(b) analysis means for analyzing the digital physiological signal data to detect patterns therein indicating fluctuations in physiological function including at least the stage of sleep, and providing a classification of the stages over time based on the patterns detected when matched with a set of classification criteria which denote the five stages of sleep and awake;

(c) display means for displaying to the operator the classification of sleep as a function of time in a hypnogram extending along one axis and simultaneously displaying to the operator indications of the time changes of various physiological signal patterns on axis which are parallel to the time axes for the hypnogram and correlated therewith in time, the physiological signals displayed being selected from the group consisting of EEG, Rapid Eye Movements over time epochs, EMG taken from the chin of the subject, EMG taken from the legs of the subject;

(d) input means for accepting input from the operator to select a chosen point in time along the hypnogram and the other physiological functions displayed and, at the command of the operator, providing signals to the analysis means and to the display means so that the analysis means and display means provide a display to the operator in time correlation along parallel axes of the raw data signals in the vicinity of the point in time selected by the operator which were received from the physiological sensors.

32. A system for analyzing physiological signals obtained from physiological sensors on a subject, comprising:

(a) means for receiving the time varying physiological signals from the sensors on the subject and digitizing the physiological signals to provide digital physiological signal data;

(b) analysis means for analyzing the digital physiological signal data to detect patterns therein indicating fluctuations in physiological function including at least the stages of sleep, and providing a classification of the stages over time based on the patterns detected when matched with a set of classification criteria which denote the five stages of sleep and awake;

(c) display means for displaying to the operator the classification of sleep as a function of time in a hypnogram extending along one axis and simultaneously displaying to the operator indications of the time changes of various physiological signal patterns on axis which are parallel to the time axes for the hypnogram and correlated therewith in time, the physiological signals displayed being selected from the group consisting of EEG, Rapid Eye Movement over time epochs, EMG taken from the chin of the subject, EMG taken from the legs of the subject, intercostal EMG, heart rate, oxygen saturation level, carbon dioxide saturation level, respiration, and combinations thereof, wherein the display means displays in time correlation with the hypnogram at least one channel of EEG physiological functions, wherein the EEG signal is displayed in a quasi-3 dimensional representation with a third dimensional display extending away from the time axis corresponding to frequency bands including the frequency bands conventionally associated with alpha waves, beta waves, delta waves, and sleepspindles.

33. A system for analyzing physiological signals obtained from physiological sensors on a subject, comprising:

(a) means for receiving the time varying physiological signals from the sensors on the subject and digitizing the physiological signals to provide digital physiological signal data;

(b) analysis means for analyzing the digital physiological signal data to detect patterns therein indicating fluctuations in physiological function including at least the stage of sleep, and providing a classification of the stages over time based on the patterns detected when matched with a set of classification criteria which denote the five stages of sleep and awake;

(c) display means for displaying to the operator the classification of sleep as a function of time in a hypnogram extending along one axis and simultaneously displaying to the operator indications of the time changes of various physiological signal patterns on axis which are parallel to the time axes for the hypnogram and correlated therewith in time, the physiological signals displayed being selected from the group consisting of EEG, Rapid Eye Movements over time epochs, EMG taken from the chin of the subject, EMG taken from the legs of the subject, intercostal EMG, heart rate, oxygen saturation level, carbon dioxide saturation level, respiration, and combinations thereof, wherein the analysis means performs analysis on the physiological signals on a real time basis and provides control signals to the display means to provide a display of the hypnogram and the associated physiological functions in time correlation therewith in a cummulative fashion between the start of the test and the current time, and further the display means provides a display on an expanded time scale of the results of the analysis for a recent segment of input signal shown with the hypnogram on an expanded time scale and the physiological functions on an axis parallel thereto, in time correlation therewith also on an expanded time scale.

34. The system of claim 33 wherein input signals are received and digitized by the means for receiving and digitizing from more than one subject simultaneously, and where the analysis means analyzes the data from more than one subject on a real time basis and the display means displays the results of the analysis to the operator on a CRT screen with the screen divided up so that separate sections of the screen display the time correlated results for each of the subjects.

35. A system for analyzing and displaying physiological signals obtained from sensors on a subject, comprising:

(a) means for receiving the time varying physiological signals from the sensors on the subject and digitizing the physiological signals to provide digital physiological signal data;

(b) storage means for storing the digitized physiological signal data in correlation with time and making such data available for later retrieval;

(c) analysis means for analyzing the physiological signal data on a real time basis to detect patterns therein indicating fluctuations in physiological functions in the subject;

(d) display means for displaying to an operator the results of the analysis performed by the analysis means showing fluctuations in a physiological function over time;

(e) input means for accepting an indication from the operator of a point in time on the displayed analysis results and, at the command of the operator, providing control signals to the display means such that the display means provides a display on a CRT screen to the operator of the raw physiological data from the sensors, retrieved from the storage means, for data gathered in the vicinity of the point in time designated by the operator, the raw physiological data from each sensor being displayed in time correlated relationship with the data displayed for the other sensors, and, further, accepting commands from the operator to provide signals to the analysis means to cause the analysis means and display means to move the physiological data displayed on the screen backwardly or forwardly in time to transfer representations to the screen of the physiological data at either an earlier or a later time under the control of the operator.

36. The system of claim 35 wherein the displayed means displays the physiological signal data to the operator, at the operator'"'"'s command, to continuously scan the stored signal data and display it in continuous motion across the CRT screen as long as commanded by the operator.

37. The system of claim 35 wherein the display means displays the physiological signal data to the operator to move, at the operators'"'"'s command, in page-like time segments either backwardly or forwardly in time so that an entire CRT screen of physiological signal representations are changed each time the operator chooses to change the display signal data.