Method and apparatus for determining sleep states
An apparatus is provided for detecting Macro Sleep Architecture states of a subject such as WAKE, NREM and REM sleep from a subject's EEG. The apparatus includes an EEG digital signal assembly of modules arranged to convert analogue EEG signals into digital EEG signals. A bispectrum assembly is responsive to the EEG digital signal assembly and converts the digital EEG signals into signals representing corresponding bispectrum values. A bispectrum time series assembly, in electrical communication with an output side of the bispectrum assembly, generates at least one bispectrum time series for a predetermined frequency. A macro-sleep architecture (MSA) assembly is responsive to the bispectrum time series assembly and is arranged to produce classification signals indicating classification of segments of the EEG signals into macro-sleep states of the subject.
1. A method of processing an electroencephalogram (EEG) signal of a subject to determine Waking and Sleep states of the subject, the Sleep state comprising non-rapid eye movement (NREM) sleep and rapid eye movement (REM) sleep states, the method comprising:
obtaining the EEG signal from EEG electrodes applied to the subject;
electronically processing the EEG signal to generate a spectrum of third or higher order of the EEG signal;
electronically processing the spectrum to produce a first spectrum slice time series at a first frequency and a second spectrum slice time series at a second frequency, the first frequency being higher than the second frequency, the first frequency having been selected for discriminating between the Waking and Sleep states, and the second frequency having been selected for discriminating between the NREM sleep and the REM sleep states;
electronically processing the first spectrum slice time series and the second spectrum slice time series for compliance with predetermined criteria to produce a sleep state signal indicating segments of the EEG signal as being classified as corresponding to either Wake or NREM sleep or REM sleep states of the subject;
wherein said processing for compliance with predetermined criteria to produce the sleep state signal comprises:
calculating a median value of the first spectrum slice time series at the first frequency to determine a first threshold value,
calculating a minimum value of the second spectrum slice time series to determine a second threshold value,
for each of the segments of the EEG signal:
if the first spectrum slice time series for the first frequency has a value greater than or equal to the first threshold value, then tangibly classifying the segment as the Waking state,
or otherwise,
if the second spectrum slice time series for the second frequency has a value greater than or equal to the second threshold value, then tangibly classifying the segment as the NREM sleep state,
or otherwise,
tangibly classify the segment as the REM sleep state; and
causing the classification(s) to be output to a visual display.
2. A method according to claim 1 , wherein the spectrum comprises a bispectrum and the spectrum slice time series each comprise a respective bispectrum slice time series.
3. A method according to claim 2 , wherein the second frequency is less than or equal to 2 Hz and the first frequency is greater than or equal to 18 Hz and less than or equal to 23 Hz.
4. A method according to claim 3 , further comprising electronically smoothing the second spectrum slice time series prior to processing said second spectrum slice time series signal for compliance with predetermined criteria.
5. A method according to claim 1 , further comprising operating an alarm in response to tangibly classifying a segment of the EEG of the subject as the Sleep state.
6. A method according to claim 1 , wherein electronically processing the EEG signal to generate a spectrum of third or higher order of the EEG signal comprises an indirect estimation method.
7. A method according to claim 6 , wherein the indirect method includes applying a Fourier transform to cumulant values corresponding to the EEG signal.
8. A method according to claim 1 , wherein the EEG signal is electronically processed to create a bispectrum signal via a direct estimation method.
9. A method according to claim 1 , further comprising electronically processing a signal corresponding to the first spectrum slice time series to produce an index indicating sleepiness of the subject.
10. A method according to claim 9 , wherein the index is produced by electronically processing a signal corresponding to a first bispectrum time series, including determining a fraction of time over a predetermined period that said first bispectrum time series approaches a predetermined threshold value.
11. A non-transitory media readable by machine, tangibly embodying a program of non-transitory instructions executable by the machine to cause the machine to perform the method of claim 1 to determine sleep states from the EEG of the subject.