Methods and apparatus for monitoring consciousness

Abstract

The systems of the present invention provide improved accuracy in monitoring, analysing, detecting, predicting and/or providing alerts and alarms associated with depth of anaesthesia, depth of consciousness, hypnotic state, sedation depth, fatigue or vigilance of a subject, with as few as 3 surface electrodes. The systems incorporate real-time phase, amplitude and frequency analysis of a subject's electro-encephalogram. The systems weight outputs of various types of analyses to produce an integrated analysis or display for precise indication or alert to users of the systems including anaesthetists, nurses and other medical personnel, transport drivers and machine workers. The systems weight the outputs of one or more analysis algorithms including combinations of simultaneous, real-time R&K analysis, AEP spectral analysis-SEF-MF, Bi-coherence analysis, initial wave analysis, auditory response, arousal analysis, body movement analysis, 95% spectral edge analysis and anaesthetic phase and spectral energy variance measurement in association with a subject's state of consciousness.

1 . A method of monitoring consciousness of a sentient subject and automatically detecting whether the subject is in a transition from a conscious state to a less conscious state or vice versa, by reducing effects of frequency-based changes in neurological data from the subject, said method including:
 obtaining an electro-encephalogram signal from the subject;   performing a frequency-based analysis on the electro-encephalogram signal to obtain a frequency-based signal;   performing a phase-based analysis on the electro-encephalogram signal to obtain a phase-based signal;   detecting by comparing the frequency-based signal and the phase-based signal whether the subject is in transition from said conscious state to said less conscious state or vice versa; and   providing a warning signal when said subject is in said transition to said conscious state.   
     
     
         2 . The method according to  claim 1 , wherein said frequency-based analysis includes depth of sleep analysis, and wherein said phase-based analysis includes at least one of optimized bicoherence, bispectrum or triple product analysis. 
     
     
         3 . The method according to  claim 2 , wherein said depth of sleep analysis includes real-time optimized scoring of human sleep physiology. 
     
     
         4 . The method according to  claim 1 , wherein said step of detecting is augmented with optimized audio evoked potential. 
     
     
         5 . The method according to  claim 2 , wherein said step of detecting is augmented with optimized audio evoked potential. 
     
     
         6 . The method according to  claim 3 , wherein said step of detecting is augmented with optimized audio evoked potential. 
     
     
         7 . The method according to  claim 1 , including means for adapting the or each analysis to parameters specific to said subject, including body mass index, age and sex of said subject. 
     
     
         8 . The method according to  claim 2 , including means for adapting the or each analysis to parameters specific to said subject, including body mass index, age and sex of said subject. 
     
     
         9 . The method according to  claim 3 , including means for adapting the or each analysis to parameters specific to said subject, including body mass index, age and sex of said subject. 
     
     
         10 . The method according to  claim 4 , including means for adapting the or each analysis to parameters specific to said subject, including body mass index, age and sex of said subject.