Anesthesia monitoring system based on electroencephalographic signals

• US 20020082513A1
• Filed: 11/13/2001
• Published: 06/27/2002
• Est. Priority Date: 11/02/1999
• Status: Abandoned Application

• Current Assignee: Physiometrix, Inc. (Pfizer Inc.)
• Original Assignee: Physiometrix, Inc. (Pfizer Inc.)
• Inventors: Ennen, David W., Jimenez, Jorge R., Marro, Dominic P.
• Application Number:
  US10/007,849
• Publication Number:
  US 20020082513A1
• Time in Patent Office: Days
• 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 observes 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 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, said patient module having a plurality of channels corresponding to the plurality of patient electrodes; and

c. at least one analysis unit connected to the patient module, said analysis unit having a plurality of channels corresponding to the plurality of patient electrodes, and said analysis unit comprising,

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

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

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, wherein the plural observers in each of the plural channels are plural classifiers which detect signatures within each of the plural EEG signals.

3. The apparatus of claim 1 in which the single derived parameter is a Patient State Index.