Method and apparatus for determining the cerebral state of a...

Surgery – Diagnostic testing – Detecting brain electric signal

Reexamination Certificate

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C600S546000

Reexamination Certificate

active

06731975

ABSTRACT:

BACKGROUND OF THE INVENTION
The present invention relates to a method and apparatus for determining the cerebral state of a patient. One application of the method and apparatus is determining the extent of a hypnotic state of the patient resulting, for example, from the administration of an anesthetic agent. That extent is often termed the “depth of anesthesia.” In the method and apparatus of the present invention, changes in the cerebral state can be accurately and quickly determined.
In a simplistic definition, anesthesia is an artificially induced state of partial or total loss of sensation or pain, i.e. analgesia. For most medical procedures the loss of sensation is accompanied by a loss of consciousness on the part of a patient so that the patient is amnestic and is not aware of the procedure.
The “depth of anesthesia” generally describes the extent to which consciousness is lost following administration of an anesthetic agent. As the magnitude of anesthetization, or depth of anesthesia, increases, an anesthetized patient typically fails to, successively respond to spoken commands, loses the eyelid reflex, loses other reflexes, undergoes depression of vital signs, and the like.
While loss of consciousness (hypnosis, amnesia) and the loss of sensation (analgesia) are significant features of anesthesia, it should be noted that balanced high quality anesthesia must also consider muscle relaxation, suppression of the autonomous nervous system, and blockade of the neuro muscular junction. Sufficient muscle relaxation is required to ensure optimal operating conditions for the surgeon manipulating the patient's tissue. The autonomous nervous system, if not suppressed, causes the patient to respond to surgical activity with a shock reaction that effects heavily on hemodynamics and the endocrine system. To keep the patient completely motionless, the neuro muscular junctions transmitting orders from the brain to the muscles of the body need to be blocked so that the body of the patient becomes completely paralyzed.
While the need to determine the state of all five components of anesthesia is widely recognized, ascertaining and quantifying the state of hypnosis or depth of anesthesia in a reliable, accurate, and quick manner has been, and is, the subject of extensive attention. One reason for this is its importance. If the anesthesia is not sufficiently deep, the patient may maintain or gain consciousness during a surgery, or other medical procedure, resulting in an extremely traumatic experience for the patient, anesthesiologist, and surgeon. On the other hand, excessively deep anesthesia reflects an unnecessary consumption of anesthetic agents, most of which are expensive. Anesthesia that is too deep requires increased medical supervision during the surgery recovery process and prolongs the period required for the patient to become completely free of the effects of the anesthetic agent. A second reason for the continuing study and attention being given to monitoring the hypnotic condition of a patient arises because of its difficulty: that is, anesthetic agents alter the activity and state of the patient's brain and these changes are not always easy to detect.
A measure of the depth of anesthesia that may be used for research purposes is found in an Observer's Assessment of Alertness and Sedation or OAAS. The OAAS determines the level of consciousness or, conversely, the depth of sedation or anesthesia, based on a patient's response to external stimuli. One such assessment that classifies the depth of anesthesia in six levels, is summarized by the table below. The transition from consciousness to unconsciousness may be deemed to occur when the OAAS score changes from level 3 to level 2. Level zero corresponds to a state of deep anesthesia in which the patient shows no response to a very painful stimulus.
OAAS
Score
Distinctive Characteristics
5
Patient replies readily to spoken commands, eyes open, awake.
4
Patient is sedated, but replies to spoken commands, mild ptosis.
3
Patient ceases to reply to loud commands, eye lid reflect present.
2
Patient does not reply to spoken commands, no eye lid reflex.
1
Patient does not react to TOF stimulation (50 mA) with
movement.
0
Patient does not react to tetanic stimulation with movement.
“Ptosis” is a drooping of the upper eyelids. “TOF stimulation” (“train-of-four”) is a very short, painful electrical (50 mA) stimulus applied to the ulnar nerve in the arm of the patient, repeated four times to evaluate the intensity of muscular contraction. In “tetanic stimulation” the electrical current (50 mA) is applied continuously for a period of time, such as 5 seconds. The ulnar nerve is the nerve which, when pinched, gives rise to the well known “crazy or funny bone” effect.
While useful for research and other purposes, an OAAS scale provides only a limited number of scaling levels and is limited in practical use because of the attention required from the anesthesiologist and the use of painful stimuli.
It has long been known that the neurological activity of the brain is reflected in biopotentials available on the surface of the brain and on the scalp. Thus, efforts to quantify the extent of anesthesia induced hypnosis have turned to a study of these biopotentials. The biopotential electrical signals are usually obtained by a pair, or plurality of pairs, of electrodes placed on the patient's scalp at locations designated by a recognized protocol and a set, or a plurality of sets or channels, of electrical signals are obtained from the electrodes. These signals are amplified and filtered. The recorded signals comprise an electroencephalogram or EEG.
Among the purposes of filtering is to remove electromyographic (EMG) signals from the EEG signal. EMG signals result from muscle activity of the patient and will appear in electroencephalographic electrodes applied to the forehead or scalp of the patient. They are usually considered artifacts with respect to the EEG signals. Since EMG signals characteristically have most of their energy in a frequency range (40-300 Hz) which is different than that of the EEG, major portions of the EMG signals can be separated from the EEG signal.
A typical EEG is shown in
FIG. 1. A
macro characteristic of EEG signal patterns is the existence of broadly defined low frequency rhythms or waves occurring in certain frequency bands. Four such bands are recognized: Delta (0.5-3.5 Hz), Theta (3.5-7.0 Hz), Alpha (7.0-13.0 Hz) and Beta (13.0-32.0 Hz). Alpha waves are found during periods of wakefulness and may disappear entirely during sleep. The higher frequency Beta waves are recorded during periods of intense activation of the central nervous system. The lower frequency Theta and Delta waves reflect drowsiness and periods of deep sleep.
By analogy to the depth of sleep, it can be said that the frequency of the EEG will decrease as the depth of anesthesia increases, while the magnitude of the signal initially often increases. However, this gross characterization is too imprecise and unreliable to use as an indication of such a critical medical aspect as the extent of hypnosis. Further, EEG signal changes during anesthesia may not fully correlate with changes in the hypnotic state of the patient. For example, it has been reported that in a 12-18 Hz frequency band, EEG activity initially increases as anesthetic agents are administered and only thereafter decreases as anesthesia deepens.
The foregoing circumstance has led to the investigation and use of other techniques to study EEG waveforms to ascertain the underlying condition of the brain, including the depth of anesthesia to which a patient is subjected. It will be immediately appreciated from
FIG. 1
that EEG signals are highly random in nature. Unlike other biopotential signals, such as those of an electrocardiogram (ECG), an EEG normally has no obvious repetitive patterns, the morphology and timing of which can be conveniently compared and analyzed. Nor does the shape of the EEG waveform correlate well to specific underlying events in the bra

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