AU632932B2 - Analysis system for physiological variables - Google Patents

Description

64329

AUSTRALIA

Patents Act COMPLETE SPECIFICATION

(ORIGINAL)

Class Int. Class Application Number: Lodged: Complete Spc'f'ication Lodged: Accepted: Published: Priority Related Art: see*@* *0 0000..

APPLICANT'S REF.: OF PK 0856) Name(s) of Applicant(s): DAVID BURTON ~'2lA12" Address(es) of Applicant(s): 8 Odessa Street, St. Kilda, Victoria, 3182, Australia "A 4187 WihGi404;,l-nthr ac,'

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coia, 3123, Actual Inventor(s): DAVID BURTON MURRAY WILLIAM JOHNS S S S S* S *5 Address for Servi(. C is: PHILLIPS, ORMONDE AND FITZPATRICK Patent and Trade Mark Attorneys 367 Collins Street Melbourne, Australia, 3000 Complete Specification for the inventlion entitled: ANALYSIS SYSTEM FOR PHYSIOLOGICAL VARIABLES

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The following statement is a full description of this invention, including the best method of performing it known to applicant(s); P19/3/84 ANALYSIS SYSTEM FOR PHYSIOLOGICAL VARIABLES The present invention relates to an analysis system for physiological variables. In particular the present invention relates to an improved method and apparatus for monitoring/analysing time varying signals representing physiological variables such as the electroencephalogram (EEG), the electro-oculogram (EOG) from each eye and the electromyogram (submental EMG) from muscles under the chin.

The method and apparatus of the present invention is especially suitable for monitoring and/or analysing sleep states and will hereinafter be described with reference to such applications. Nevertheless it is to be appreciated that it is not thereby limited to such applications. Thus the method and apparatus of the present invention may have 0.000 general applications such as in routine clinical or diagnostic investigations and in research.

When monitoring sleep states and wakefulness several physiological variables may be measured continuously including the EEG, the EOG from each eye and the submental EMG. Sleep is not a uniform state. It has been categorized into various stages which have been defined in terms of the pattern or waveform in the EEG, the type of eye movements (represented by the pattern or waveform in the EOG), and the level of activity in the submental muscles (represented by the pattern or waveform in the EMG). These sleep stages are respectively known as stages 1, 2, 3 and 4 and Rapid-eye-movement or REM sleep.

For many years the usual way of assessing sleep, especially in overnight studies in a sleep laboratory, has been to record these variables on paper with an ink-writing polygraph. A single 8-hour recording might involve 400 metres of paper. This was an expensive process and its visual analysis, page by page, was extremely time consuming.

In addition, visual scoring of data involved pattern recognition and subjective estimatesAprone to err-or.

Several attempts have been made during the past years to analyse sleep recordings by computer. These have 11 failed to a greater or lesser extent because they provided 2i 8 output data which could not be easily or reliably interpreted in terms of traditional visually scored sleep stages which remain the standard for comparison. To understand why previous attempts at computer analysis have not been adopted, it is necessary to consider some properties of Lhe physiological variables being measured, particularly the EEG.

The EEG is a continuously varying voltage recorded from electrodes on the scalp. This appears as a series of waves with positive and negative phases, frequencies in the range 0.5 to 30 Hz, and amplitudes up to 250 microvolts. The voltage points defining these waves can be considered as a time series, an important feature of which is that it is not a stationary time series. That is the pattern of waves is not constant, even over periods of 20 seconds.

An important parameter used in defining sleep stages is the percentage of time during a particular recording interval or epoch of the EEG taken up by waves in the frequency range of 0.5 to 3 Hz, known as delta-waves, whose amplitide exceed microvolts peak-to-peak. The occurrence of such delta-waves is not entirely regular. Nor is their frequency or amplitude const-ant. Stage 2 sleep has up to 20% of delta waves. Stage 3 has 20 to 50% of such waves and stage 4 has more than 50% (refer Fig. Stage REM sleep is characterized by the absence of such high-amplitude delta-waves in the EEG, the presence of rapid eye movements in the EOG, and a relatively low level of activity in the submental EMG,, Stage 1 EEG is similar to that of stage REM but with moderate levels of activity retained in the EMG and an absence o;f REMs in the EOG.

Similarly, the occurrence of waves known as spindles is sporadic. Spindles are discrete bursts of waves in the frequency range 12-16 Hz which may last 1 or 2 seconds. They do not occur during wakefulness, are most common in Stages 2 and 3 sleep, and are rare in Stage REM sleep.

Non-stationarity of the EEG limits the usef1ulness of traditional methods of time-series analysis which have been used to analyse the EEG by computer. One known method of EEG analysis is the Fast Fourier Transform. The Fast Fourier 39 Transform produces a spectrum of total power at each

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frequency within the bandwidth considered, during a particular period. However in this method one high-amplitude wave of a particular frequency may have the same power as, and may be indistinguishable from, several low-amplitude waves of the same frequency. Power spectral analysis of data in epochs of managable length (eg. 20 seconds) cannot distinguish between patterns in the EEG, but this is the very situation which arises during sleep. e.g. Stage 2 compared with Stage REM.

Another known method of EEG analysis calculated the "integrated amplitude" of delta-waves within each epoch by summing amplitude values between successive zero crossings of delta-waves (refer Fig. This latter method gave results which were very similar to those from power spectral *too*: analyses, and thus suffered the same limitations.

to Of the methods used in the past, each provided parameters which varied with sleep stages, but not in a way which enabled sleep during a particular epoch to be categorized consistently and objectively into one of the currently defined sleep stages.

A still further difficulty arises with attempts to automate scoring of sleep stages. This occurs because there exist several major sources of variation within the EEG, to between different subjects and within the same subject at different times. Some variations persist across sleep stages. Other variations arise from artefacts introduced by the particular recording method used eg. due to changes in the electrode contact with the skin when a subject moves, or from electrocardiograph (ECG) waves appearing in the EEG of !n* some subjects. Other sources of variation are still poorly understood.

Currently used visual scoring methods for sleep stages are relatively insensitive to differences between subjects.

It has been applicants experience that scorers consciously or subconsciously tend to isolate between subject differences, which may remain throughout a night sleep recording, as being less important than variations between sleep stages within each subject. By 'ontrast, visual scorers are often 39 more sensitive to other information in recordings which MJP 4 r '7 indicates presence of artefacts.

An object of the present invention is to provide a system for monitoring and/or analysing signals representing physiological variables which at least alleviates the disadvantages of the prior art. In the embodiment considered the time varying signals represent variables such as the EEG which may be related to discernible sleep stages. The system of the present invention may be adapted to output data in a form which may be directly and quantitatively related to sleep stages as currently defined.

The system of the present invention may be adapted to process data on-line or off-line if required. A variety of formats for output data from the system may be chosen depending on the extent to which such data is to be used for S further analysis and the reasons for monitoring sleep in the S first place. This may be a routine diagnostic investigation, or a particular research project requiring maximal compliance e g.

with visually scored methods which are still considered to be the standard.

The system of the present invention includes apparatus for monitoring and/or analysing physiological variables. The apparatus includes means for generating electrical signals or waveforms representing the physiological variables. The latter means may include one or more transducers suitable for attachment to a subject being monitored.

In one form the apparatus of the present invention may include, inter alia, means for: 1i. preamplifying signals from the or each transducer; 73. 2. preconditioning signals to provide a suitable input or inputs for the system; 3. digitizing the or each signal at sampling rates suitable for each type of signal; 4, displaying data on-line preferably on a high resolution monitor; storing data temporarily in suitable storage means such as hard disc or magnetic tape and for retrieving same when required; 39 6. storing data long-term, or permanently, if MJP 5 required in a fixed medium such as archive tape or optical disc for retrival; 7. processing the data as hereinafter described either on line ie. during recording, or at a later time; 8. displaying graphically or otherwise the results of such analyses preferably in summarized form, either during recording or later; and 9. storing numerically the results of such analyses eg. in a spreadheet, for further or higher levels of analyses.

The electrical signals or waveforms may be digitized during recording at sampling rates which in the case of EEG signals may vary between 250 and 2000 per sec. or •more. Intervals between successive zero level crossings •:go may be measured as "half-periods" for each wave. Absolute value voltage excursions between zero crossings may give i "half-peak amplitudes" of each wave. The zero level may be preset or it may be arranged to 'float' up and down over time. In one form the zero level may be adjusted automatically at regular time intervals, say each 1 second. In one form the zero level may be set according to the "average" signal level which prevailed during the immediately preceding time interval. An important difference between the method of the present invention and prior art methods based on period or amplitude analysis lies in the way this information is further processed.

According to one preferred embodiment of the present invention the half-periods may be processed or sorted into a0: various "period windows" equivalent or corresponding to wave-bands defined by frequencies as follows: Wave-band Frequency Range (Hz) Period Window(ms) Beta >16 <62.5 Sigma 12-16 62.5 83.3 Alpha 8-11.99 83.4 125 Theta-A 5-7.99 125.1 200 Theta-D 3.01-4.99 200.1 332.2 Delta 0.5-3.0 322.3 2000 39 Sub-delta <0.5 >2000 MJP 6 II I Theta-A refers to waves which behave like low-frequency alpha waves in their various changes during sleep and wakefulness. They are distinguishable from Theta-D waves which behave like high-frequency delta-waves.

Whilst the upper and lower limits for the wave bands noted above have been found useful in monitoring and/or analysing sleep states it is to be appreciated that they in no way restrict the present invention to any particular upper or lower limit for any particular wave band and the number of wave bands and their limits may be varied depending upon application.

According to a further preferred embodiment of the present invention delta-waves may be processed or sorted according to their amplitude as follows: Delta-L amplitude substantially 40 microvolts Delta-M substantially between 40-75 Delta-H substantially The upper and lower limits of the amplitude bands noted above have been found useful in monitoring and/or analysing sleep states. However as with the wave bands they in nc way restrict the present invention to any particular upper or lower limit for any particular amplitude band and the number of amplitude bands and their limits may be varied depending upon application.

i The means for processing electrical signals or wavefor according to the above noted wave-bands and/or amplitude bands may comprise analog and/or digital processing means. The processing means may include, inter alia, analog and/or digitally implemented high/low pass 30 and/or bandpass filter means comparator means, timing means and/or threshold detector means. In one form the processing means may include a suitably programmed microprocessor or microcomputer.

Data representing percent time in each recording segment or epoch take i up by waveforms in various i.equency and amplitude categories may be displayed in one form as coloured segments or lines on a color monitor screen. The said data may also be stored numerically in a 39 spreadsheet for all epochs and numbered consecutively.

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-7 cSI Additional information about the period and amplitude of each individual delta wave and the mean amplitude of waves in each frequency band may also be stored in the spreadsheet, although the latter information may not be used routinely.

The percent time Laken up by low-amplitude delta-waves (Delta-L and Delta-M) is a new parameter which has not previously been assessed quantitatively in EEG analysis methods, especially in power spectral analysis.

The latter has proven to be significant in distinguishing stage REM sleep.

The percent time taken up by Delta-H waves substantially 75 microvolts) is a parameter which is also useful in the definition of sleep stages.

Sub-delta waves are mainly due to movement artefacts ess. and should be distinguished whenever possible.

Information in addition to those provided by EEG analysis e' may be provided by the system of the present invention.

The system of the present invention may be adapted to provide such additional information, summarized for each epoch alongside the EEG analysis.

The additional information may include submental EMG amplitude. The EMG waveform may be digitized and its mean amplitude calculated from maximum absolute values between successive zero crossings. The mean amplitude may be determined at the end of each epoch of recording.

The additional information may include rapid eye movements. During each epoch those waves in each EOG whose amplitude is greater than a preset threshold and whose duration is less than a preset maximum may be detected. If they are coincident in each EOG channel (or nearly so, within 50 milliseconds) regardless of their phase, they may be interpreted as rapid eye movements.

According to the present invention the above information may be derived objectively and automatically eg. by computer analysis, for the first time.

In the present method of analysis spindles in the EEG may be detected. This may be done by passing raw EEG 39 data through high pacs filter means to filter out

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delta-waves. The higher-frequency waves in the EEG are mostly of much smaller amplitude than delta-waves upon which they are superimposed. The high-pass filtered EEG (>9Hz) may be digitized and in one form a software routine may be implemented to detect spindles by period-amplitude analysis. In one embodiment when a series of say, 10 out of 14 successive half-periods fall within the required frequency range, this may be interpreted to indicate spindles, and a courter may be incremented. The number of waves and their precise frequencies may be variable in software.

Period-amplitude analysis of the high-pass filtered EEG may also give the mean amplitude of all waves with frequencies greater than, say, 8 Hz in each epoch, this latter limit also being variable in software.

The apparatus of the present invention may be adapted to make available the results of the above analyses on line, ie.at the end of each epoch of recording. Alternatively the same analyses can be performed off-line at a later time, if required. A whole night's recording may be summarized graphically on eg. or 6 sheets of A4 paper, preferably printed in colour S" (refer Fig. These pages may also be displayed on a monitor screen, if required for further analysis.

With summaries of data, as shown in Fig. 7 a trained operator can assign each epoch of recording to a sleep stage within a few minutes, using the same criteria and definitions as are used in usual scoring of raw data.

However, scoring is speeded up because problems associated with handling large volumes of paper records are removed and because the necessary parameters have already been provided automatically. With a graphical summary displayed on a colour monitor an operator can move a cursor from epoch to epoch, assigning them to particular sleep stages. This can usually be done with large blocks of data at once by using a keypad to indicate only when a new sleep stage begins.

Computer assisted measurements of percent times, for 39 example may be much more accurate than subjective MJP 9

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estimates. However, artefacts in some recordings, such as ECG waves appearing in the EEG cannot be removed and allowance may have to be made for their effect in EEG analysis. In such situations raw data may be retrieved from hard disc and displayed in a few epochs to check the results of analysis.

Long-term differences in the EEGs of different subjects may often be more apparent during wakefulness, ie. before the onset of sleep. A skilled operator therefore proceeds to sleep stage analysis armed with such information gathered during wakefulness. The operator's interpretations of changes in the pattern of results eg.

deviations from the baseline may be modified according to S information gathered during wakefulness for a particular subject.

eoo The apparatus of the present invention may include t additional input channels. The additional input channels may include, inter alia, information concerning the esence of and number of leg mcvements during each epoch, the sleeper's position, the number of snoring noises, the presence of apneic episodes (when there is reduced or 9.S absent respiratory airflow), and the level of arterial ""oxygen saturation (SaO 2 Software analysis of the information associated with the or each additional input channel may provide clinically important information.

Once a particular sleep stage or wakefulness been assigned to each epoch, further analyses may be carried S*out automatically by the apparatus of the present invention. For example, differences in the incidence of snoring noises can be related to a particular sleep stage and the sleeper's position. Snoring is usually worst in sleep stages 2, 3 and 4 when lying supine.

Analysis also may be performed automatically to quantify the frequency and duration of sleep apneic episodes according to sleep stage and the sleeper's position.

According to one aspect of the present invention there is provided apparatus for processing a 39 non-stationary time varying signal representing a MJP -10 physiological variable, said apparatus comprising: means for dividing said signal into notional time intervals; means for assigning during each time interval, a zero level for said signal; means for measuring during each time interval, the duration of time segments between successive zero level crossings by said signal; means for sorting said measured time segments according to a plurality of wave bands, each wave band being defined by upper and lower frequencies corresponding to lower and upper time periods respectively; and means for displaying the relative frequency of occurrence of time segments in each defined wave band.

According to a further aspect of the present invention there is provided a method for processing a non-stationary time varying signal representing a :o physiological variable comprising the steps of: o dividing said signal into notional timo intervals; assigning during each time interval a zero level for said signal.; measuring during each time interval, the duration of time segments between successive zero level crossings4; sorting said measured time segments according to a plurality of wave bands, each wave band being defined by upper and lower frequencies corresponding to lower and upper time periods respectively; and displaying the relative frequency of occurrence of time segments in each defined wave band.

Referring to the drawings, Figure 1 shows typical EEG waveforms of wakefulness and various stages of sleep recorded from a unipolar parietotemporal electrode.

Average amplitude increases and the frequency decreases from stage 1 (ST 1) to stage 4 (ST4). Spindles are present in stages 2 and 3.

Figure 2 shows the pattern of stage changes during a typical night's sleep in a young adult.

Figure 3 shows rapid eye movements as recorded by an S electro-oculogram during stage REM or dreaming slr.ep.

11 Very little activity or slow pendular eye movements are seen during non-dreaming sleep.

Figure 4 shows a prior art integrated amplitude and spectral power density of delta waves plotted for successive epochs of sleep in a young adult.

Figure 5 shows a block diagram of apparatus according to one embodiment of the present invention.

Figure 6 shows a flow diagram representing one processing method according to the present invention.

Figure 7 is a multichannel graphical chart showing sleep stage data produced by a colour printer.

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Very little activity or slow pendular eye movement,.--a seen during non-dreaming sleep.

Figure 4 shows a prior art i -egated amplitude and spectral power density delta waves plotted for successive epochs eep in a young adult.

Fiq 5 shows a block diagram of apparatus a- c~rding to one embodiment of the present invent on.

The apparatus of Figure 5 includes electrodes shown generally at 50 attached to a subject 51 under ana3ysis.

Each electrode 50 comprises a suitable transducer and corresponds to a separate channel of the system. There may be up to 48 or more such channels in the system which S may handle two or more subjects simultaneously. Each S electrode or transducer is connected to preamplifier means 52. Preamplifiet means 52 includes a respective preamplifier for each channel of data and is adapted to amplify relatively weak voltage signals received from electrodes or transducers The output of preamplifier means 52 is connected to voltage conditioning means 53. Conditioning means 53 includes a conditioning circuit for each channel adapted to further amplify, scale and/or perform other wave S forming functions upon signals of each channel to provide S suitable analog inputs to analog to digital (A to D)convertor means 54.

A to convertor means 54 is adapted to digitize each channel of analog data suitable for processing by digital processing means S' Digital processing means 55 may comprise any suitable digital processor such as a micro-processor, micro computer or main frame computer. Processing means is adapted to process each channel of data and display the processed data via display means 56. Display means 56 preferably comprises a multichannel colour printer but may comprise any suitable means for displaying multichannel data in side-by-side relationship.

Processing means 55 is adapted, inter alia, to process data corresponding to an EEG channel according to its wave-band and amplitude cumponents. In particular 12 processing means 55 is adapted to calculate, inter alia, the percen, time in each epoch or recording interval taken up by waves in Delta H, Delta M and Delta L categories as described herein. The percent time in each category may be represented upon display means 56 as, say vertical lines or segments. Each category of wave or wave-band may be represented by a different colour. The colour of each line or segment may vary along its length whereby the relative length of each colour rtiresents the relative duration attributable to each category of wave or wave-band.

On line data associated with the or each channel may be displayed before or after processing via display means 57. In one form display means 57 may comprise a high o*oo resolution colour monitor.

Data associated with the or each channel may be stored temporarily before or after processing, in storage means 58. Storage means 58 may comprise any retrievable storage means such as a hard disc.

Data associated with the or each channel may be stored more permanently before or after processing, in storage means 59. Storage means 59 may comprise a fixed medium such as archive tape or optical disc.

I Figure 6 shows a flow diagram representing one method by which data may be processed via digital processing means 55. In the flow diagram establishment of zero level may be performed manually by the operator or it may be detected automatically. Automatic zero level may be detected for successive time intervals (eg. 1 second) by calculating the average signal level for a preceding time interval.

SHalf period analysis may be carried out by sorting each "half period" into one of the period windows or wave-bands set out on page 7. For example if for a detected or set zero level the time interval between two successive zero crossings is 500ms. the half-period associated with those two zero crossings is categorized as a Delta wave. Because the amplitude of delta waves is 39 significant for the purpose of distinguishing stage REM MJP 13 sleep the half-peak amplitude of the voltage excursion associated with the same two zero crossings may be calculated with reference to the zero level which was set for those zero crossings.

For example if the amplitude associated with the latter delta wave is calculated as 80mV, the half period is proces:ed, recorded and displayed as a Delta-H wave.

Successive half periods are analysed and sorted into one of the period windows or wave bands in similar fashion and the results are summarized in terms of percentage of epoch time taken up by waves in each period window.

A typical multichannel graphical chart showing sleep stage analysis data produced by a colour printer is shown in Figdre 7. In Figure 7 each channel of data represents respectively: left leg movement, right leg movement, arterial oxygen saturation (SaO apnea, use of accessory muscles, snores, sleeping position, EMG amplitude, spindles, REMs, light on/off and EEG time.

SThe channels of data are displayed simultaneously along i i 20 the vertical axis and time measured in epochs (20 second periods) is displayed along the horizontal axis.

The colour coding adopted in Figure 7 for the display of EEG time is as shown below but may be S" variable. Alternative visual coding techniques such a grey tone scale could be adopted for distinguishing between different wave-bands.

Wave-Band Colour Beta light red S" Sigma light blue Alpha black Theta A brown Al Theta D yellow Delta L light green Delta M dark green Delta H dark blue Sub.-Delta dark red Advantages of the system of analysis according to the present invention include the following: 39 1. Costs, difficulty and time associated with handling MJP 14

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and storing voluminous paper records may be greatly reduced; 2. Information required for analysis of sleep into recognized sleep stages may be provided accurately and objectively, with condensed summaries from which characteristics of a whole night's sleep can be rapidly assessed; 3. Most detailed analysis of associated variables, monitored during sleep to assess sleep disorders such as sleep apnea, can be done automatically; 4. Time involved in quantitative assessment of a night's sleep and associated disorders may be reduced from several hours to several minutes.

r" Finally, it is to be understood that various alterations, modifications and/or additions may be introduced into the constructions and arrangements of parts previously described without departing from the spirit or ambit of the present invention.

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Claims (12)

1. Apparatus for processing a non-stationary time varying signal representing a physiological variable, said apparatus comprising: means for dividing said signal into notional time intervals; means for assigning during each time interval, a zero level for said signal; means for measuring during each time interval, the duration of time segments between successive zero level crossings by said signal; means for sorting said measured time segments

6. according to a plurality of wave bands, each wave band being defined by upper and lower frequencies corresponding to lower and upper time periods respectively; and means for displaying the relative frequency of occurrence of time segments in each defined wave band. tee% so 2. Apparatus according to cliim 1 including means for measuring during each time segment, the amplitude of said signal relative to the zero level for the corresponding time interval, and means for further sorting said measured time segments according to a plurality of amplitude bands, each amplitude band being defined by lower and upper amplitude levels, and wherein said display means is .on adapted to display the relative frequency of occurrence of time segments in each defined amplitude band. 3. Apparatus according to claim 2 including means for sorting said measured time segments according to said defined wave and amplitude bands. 4. Apparatus according to claim 1, 2 or 3 wherein said zero level is assigned automatically on the basis of an IJ average level for said signal during a preceding time interval. Apparatus according to claim 1, 2 or 3 wherein said zero level is assigned manually by an operator. 6. Apparatus according to any one of the preceding claims including analogue to digital conversion means and means for digitally processing said time varying signal. 39 7. Apparatus according to claim 6 wherein said means MJP 16 Ii 1 i for digitally processing comprises a microprocessor.

8. Apparatus according to any one of the preceding claims wherein said display means comprises a colour printer and wherein each wave band is represented by a different colour.

9. Apparatus according to claim 8 wherein the relative frequency of occurrence of time segments which fall in a particular wave band is represented by the length of a line of corresponding colour.

10. Apparatus according to any one of claims 2 to 6 wherein said display means comprises a colour printer and wherein each amplitude band is represented by a different colour.

11. Apparatus according to any one of claims 3 to 6 wherein said display means comprises a colour printer and S wherein at least some wave and amplitude bands are 4C go represented by a different colour.

12. Apparatus according to claim 11 wherein the relative 4. toogens hchflli frequency of occurrence of time segments which fall in said at least some wave and amplitude bands is represented by the length of a line of corresponding colour.

13. Apparatus according to any one of the preceding claims wherein said display means is adapted to e simultaneously display data representing one or more of too% the following associated variables: left leg movement, right leg movement, aterial oxygen saturation, apnea, use of accessory muscles, S snores, sleeping position, EMG amplitude, spindles, REM's, Slight on/off, EEG time. S308, 14. A method for processing a non-stationary time varying signal representing a physiological variable comprising the steps of: dividing said signal into notional time intervals; assigning during each time interval a zero level for said signal; measuring during each time interval, the duration of time segments between successive zero level crossing sorting said measured time segments according to a 0fIA plurality of wave bands, each wave band being defined by 17 7'E I J upper and lower frequencies corresponding to lower and upper time periods respectively; and displaying the relative frequency of occurrence of time segments in each defined wave band. A method according to claim 14 including measuring during each time segment the amplitude of said signal relative to the zero level for the corresponding time interval, further sorting said measured time segments according to a plurality of amplitude bands, each amplitude band being defined by lower and upper amplitude values, and displaying the relative frequency of occurrence of time segments in each amplitude band.

16. A method according to claim 15 including sorting *e said measured time segments according to said defined wave and amplitude bands.

17. A method according to claim 16 including displaying the relative frequency of occurrence of time segments in at least some of said defined wave and amplitude bands.

18. A method according to any one of claims 14 to 17 including assigning said zero level on the basis of an average level for said signal during a preceding time interval.

19. Apparatus according to claim 1 substantially as herein described with reference to the accompanying drawings. A method according to claim 14 substantially as herein described with reference to the accompanying j drawings. DATED: 29 April 1991. SPHILLIPS ORMONDE FITZPATRICK ATTORNEYS FOR:- A DAVID BURTON LAW. ILL IA JOHU 1316u S 'E -o 113 39 MJP 18