Anesthesia monitoring system based on electroencephalographic signals

• US 6,317,627 B1
• Filed: 11/02/1999
• Issued: 11/13/2001
• Est. Priority Date: 11/02/1999
• Status: Expired due to Term

• Current Assignee: SEDLine, Inc. (Masimo Corporation)
• Original Assignee: Physiometrix, Inc. (Pfizer Inc.)
• Inventors: Ennen, David W., Jimenez, Jorge R., Marro, Dominic P.
• Primary Examiner(s): Lacyk, John P.
• Assistant Examiner(s): CARTER, RYAN CHRISTOPHER
• Application Number:
  US09/431,632
• Time in Patent Office: 742 Days
• Field of Search: 600/544-545, 600/26, 600/300
• US Class Current: 600/544
• CPC Class Codes: A61B 5/369 Electroencephalography [EEG] devices for psychotechnics A61B5/16
• CPC Class Codes: A61B 5/372 Analysis of electroencephalograms
• CPC Class Codes: A61B 5/4821 Determining level or depth of anaesthesia A61B5/1106 takes precedence
• CPC Class Codes: A61B 5/7203 for noise prevention, reduction or removal
• 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: A61M 16/01 specially adapted for anaesthetising A61M16/104, A61M16/18 take precedence
• CPC Class Codes: A61M 2230/10 Electroencephalographic signals
• CPC Class Codes: A61M 2230/60 Muscle strain, i.e. measured on the user
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

A system which classifies patients according to their level of awareness or consciousness using measures derived solely from electroencephalograph (EEG) signals. The system comprises multiple observers of characteristics of signals, including artifact detectors, especially magnitude artifact detectors, eye blink detectors, stationarity/RMS detectors, slew rate detectors, and burst suppression detectors, and determination of power in certain frequency bands. The system produces a single derived probabilistic measure of conscious awareness called the patient state index (PSI) and displays values of trends in that index and values of an artifact index, an EMG index, and a suppression ratio in order to give the operator current information on the quality of the signal input. The PSI is derived from a statistical analysis using empirically derived population norms and other parameters.

Claims

1. An apparatus for classifying the level of awareness or anesthesia of a patient using electroencephalograph (EEG) signals, comprising:

a. a plurality of patient electrodes whereby a plurality of patient EEG signals is acquired;

b. a patient module connected to the patient electrode set; and

c. an analysis unit connected to the patient module, said analysis unit comprising;

i. a plurality of modules comprising observers configured to produce measures of specific characteristics in the plural EEG signals; and

ii. an observer mediator which mediates among plural outputs of the plural observers according to a mediation logic, whereby the observer mediator produces at least one output parameter characterizing the patient'"'"'s state of awareness or anesthesia;

wherein one of the modules comprising an observer comprises a subsystem which constructs and sends to the observer mediator a statistical discriminant based on plural statistical variables derived from power and frequency information extracted from plural EEG signals.

2. The apparatus of claim 1 in which the plural modules comprising observers, other than the module comprising a subsystem which constructs a statistical discriminant, comprise plural classifiers which detect signatures within the plural EEG signals, which signatures are different from the statistical variables used to construct the statistical discriminant.

3. The apparatus of claim 2 in which the observer mediator weighs the output of the plural observers by monitoring each observer'"'"'s input signal quality and the context of the observation based on the patient'"'"'s state of awareness or anesthesia.

4. The apparatus of claim 1 in which one of the at least one output parameters is a Patient State Index which characterizes the patient'"'"'s state of awareness or anesthesia.

5. The apparatus of claim 2 in which the plural classifiers comprise a corresponding plurality of artifact detectors.

6. The apparatus of claim 5 in which the plurality of artifact detectors comprises at least a magnitude artifact detector, a slow eye blink detector, a fast eye blink detector, a stationarity/RMS detector, and a slew rate detector.

7. The apparatus of claim 2 additionally comprising an additional separate channel transmitting a duplicate of one of the plural EEG signals to a Beta5 observer, the output of which is also directed to the observer mediator.

8. The apparatus of claim 6 additionally comprising a suppression classifier.

9. An apparatus for classifying the level of awareness of a patient using electroencephalograph (EEG) signals, comprising:

a. a plurality of patient electrodes whereby a plurality of patient EEG signals is acquired;

b. a patient module connected to the patient electrode set; and

c. an analysis unit connected to the patient module,

in which the patient module and the analysis unit each comprises a plurality of channels corresponding to the plurality of patient electrodes;

in which each of the plurality of channels in the analysis unit comprises a plurality of modules comprising observers tuned to produce measures of specific characteristics in the plural EEG signals, the output of which observers is directed to a single observer mediator which combines the output of the plural observers in the plural channels into a single derived parameter; and

in which the observer mediator weighs the output of the plural observers in the plural channels by monitoring each observer'"'"'s input signal quality and the context of the observation based on the patient'"'"'s state of awareness or anesthesia.

10. The apparatus of claim 9 in which the plural classifiers in each of the plural channels comprise a corresponding plurality of artifact detectors.

11. The apparatus of claim 10 in which the plurality of artifact detectors in each of the plural channels comprises at least a magnitude artifact detector, a slow eye blink detector, a fast eye blink detector, a stationarity/RMS detector, and a slew rate detector.

12. The apparatus of claim 9 additionally comprising an additional separate channel transmitting a duplicate of one of the plural EEG signals to a Beta5 observer the output of which is also directed to the observer mediator.

13. The apparatus of claim 11 additionally comprising a suppression classifier in each of the plural channels.

14. An apparatus for electronically estimating the level of a patient'"'"'s awareness using electroencephalograph (EEG) signals comprising

a. a predetermined number of plural channels for EEG data;

b. a corresponding plurality of electrodes which acquire and transmit from the patient'"'"'s head a plurality of EEG signals corresponding in number to the plural channels;

c. an additional channel into which a duplicate signal of the signal in one of the predetermined plurality of channels is transmitted;

d. in the additional channel, an overlapped epoch buffer;

e. in the additional channel connected to the overlapped epoch buffer, a module producing the Beta 5 band power using a single channel fast fourier transform (FFT) generator and Beta 5 band binding;

f. a decimator, and a high pass filter in each of the plural channels of EEG signals;

g. a corresponding plurality of artifacter banks, one in each of the plurality of channels, each bank comprising a plurality of time domain artifact detectors;

h. a Raw Time Series Data Buffer comprising a corresponding plurality of buffers storing a corresponding plurality of epochs of signals from the plural channels, each of the plurality of epochs of signals comprising overlapped partial epochs of partial epoch length signals from the corresponding plural channels;

i. in each of the plural channels, an artifact type-categorizer;

j. in each of the plural channels, a magnitude artifact detector as one of the plurality of time domain artifact detectors;

k. in each of the plural channels, at least one eye-blink detector as at least one of the plurality of time domain artifact detectors;

l. in each of the plural channels, a stationarity/RMS detector as one of the plurality of time domain artifact detectors;

m. in each of the plural channels, a slew rate artifact detector as one of the plurality of time domain artifact detectors;

n. in each of the plural channels, a suppression detector/classifier as one of the plurality of time domain artifact detectors;

o. in each of the plural channels, an artifact index generator;

p. in each of the plural channels, an FFT generator producing a corresponding plurality of channels of complex frequency domain parameters;

q. an EMG Index generator comprising a Beta 2z band processor;

r. an EMG Beta-5 Observer;

s. an Artifact Index generator;

t. a Suppression Ratio generator;

u. a discriminant processor;

v. an observer-mediation module producing a patient state index (PSI) from the outputs of other observers;

w. a PSI trend averaging module;

x. a display apparatus displaying the Artifact Index, the PSI Trend Value, the EMG Index, and the Suppression Ratio.

15. A method of classifying anesthetized patients according to their conscious state as determined from an analysis of volunteer data using the OAA/S scale by performing the steps of:

a. analyzing artifacts in time domain EEG data resulting in the rejection of data contaminated by predetermined types of artifacts;

b. generating artifact labels and parameters;

c. generating the Fast Fourier Transform (FFT) of segments of EEG data resulting in a frequency domain representation of the EEG data and computing therefrom the signal power in predetermined frequency bands;

d. applying statistical analysis to various measures in the predetermined frequency bands to provide a probability of classification into aware and unaware groups, with reference to population norns obtained from statistical studies of large normative populations;

e. combining the results of statistical analysis with other observations of the patient state to provide a single quantitative index of the patient'"'"'s conscious state.

16. A method for monitoring the state of anesthesia of a medical patient using electroencephalograph (EEG) signals, comprising:

a. acquiring a plurality of EEG signals from a preselected corresponding plurality of channels electrically connected to a plurality of international standard locations on a patient'"'"'s head;

b. digitizing and decimating the EEG signals in each of the plurality of channels;

c. applying a plurality of time domain artifact detection modules to the signals in the plurality of channels;

d. applying an eye blink observer to the signals in each of the plurality of channels and determining from them epochs with eye blinks

e. applying a burst suppression observer to the signals in each of the plurality of channels and determining therefrom a suppression code;

f. storing overlapped half-epoch decimated EEG signals in a buffer;

g. performing a fast fourier transform with a resolution of 0.25 Hz or better on half epochs and epochs having no artifact label;

h. using the fast Fourier transform results to compute a predetermined plurality of power measures for predetermined frequency bands;

i. developing a classification probability by statistical analysis of the power measures;

j. applying an EMG Beta-5 observer to the power measures

k. determining a suppression ratio, an EMG index, and an artifact index;

l. applying mediation logic to the results of all observers and indices, resulting in the patient state index,

m. displaying the patient state index, the suppression ratio, the EMG index, and the artifact index on a display unit;

n. administering anesthesia to the patient;

o. repeating steps a. through l. at predetermined intervals and displaying the patient state index, the suppression ratio, the EMG index, and the artifact index on a display unit in a time ordered sequence;

p. adjusting the anesthesia administered to the patient so as to attain a plane of anesthesia selected by the anesthesiologist; and

q. adjusting the anesthesia administered to the patient in response to changes in the patient state index, the suppression ratio, the EMG index, and the artifact index.

17. A method for monitoring the state of anesthesia of a medical patient using electroencephalograph (EEG) signals, comprising:

a. decimating incoming EEG signals;

b. performing artifact analysis on the time domain EEG signals for validity and contamination;

c. setting artifact codes and calculating artifact-related quantities;

d. applying an eye blink observer and a suppression observer;

e. determining the Fast Fourier Transform coefficients of the EEG data for each of the four channels;

f. dividing the FFT spectral data into a plurality of frequency bands, and determining raw measures (either power or mean frequency) for the frequency bands;

g. applying an EMG Beta 5 observer to these raw measures;

h. applying statistical discriminant analysis to these raw measures, and determining a probability of correct classification into an aware population group;

i. combining the probability with the results of other observers of the patient state to produce the Patient State Index (PSI).

18. A method for monitoring the state of anesthesia of a medical patient independent of the anesthetic agent comprising the steps of

a. analyzing information in the frequency range of 0.5 Hz to 50 Hz;

b. removing noisy or invalid data so as to provide artifact free frequency domain representations of EEG signals;

c. extracting from the artifact free frequency domain representations specific frequency domain raw signal measures;

d. applying a set of observers to both the time-domain data and frequency-domain measures;

e. monitoring and evaluating these measures over time and providing statistical analysis of particular components of a montage of EEG signals;

f. deriving a set of four processed parameters every epoch;

the Patient State Index characterizing the relative state of consciousness of an anesthetized patient;

the Suppression Ratio indicating the relative amount of time that the patient'"'"'s EEG waveforms exhibit a characteristic Burst/Suppression pattern;

the EMG index (EMG) indicating muscle activity as a weighted percentage of half-epochs (over the past one minute) in which muscle activity, as measured by the power in the BETA-2 band, exceeds a predetermined threshold level; and

the Artifact Index indicating data quality or the amount of artifacts present in the data;

g. scaling the Patient State Index so that it has a range of 0 to 100; and

h. providing upper and lower thresholds of the patient state index within which the patient will be said to be in an appropriate level of unconsciousness.