Closed loop drug administration method and apparatus using EEG complexity for control purposes

Abstract

A closed loop method and apparatus for controlling the administration of an hypnotic drug to a patient. Electroencephalographic (EEG) signal data is obtained from the patient. At least one measure of the complexity of the EEG signal data is derived from the data. The complexity measure may comprise the entropy of the EEG signal data. The EEG signal data complexity measure is used as the feedback signal in a control loop for an anesthetic delivery unit to control hypnotic drug administration to the patient in a manner that provides the desired hypnotic level in the patient. An EEG signal complexity measure obtained from the cerebral activity of the patient can be advantageously used in conjunction with a measure of patient electromyographic (EMG) activity to improve the response time of hypnotic level determination and of the feedback control of drug administration. A pharmacological transfer function may be used, along with pharmacokinetic and pharmacodynamic models.

Description

CROSS REFERENCE TO RELATED APPLICATION[0001]The present application claims the priority of U.S. provisional application 60 / 291,873, filed May 18, 2001.BACKGROUND OF THE INVENTION[0002]The present invention is directed to a method and apparatus for controlling the administration of an hypnotic drug in “closed loop” fashion.[0003]An hypnotic drug may comprise an anesthetic agent and the hypnotic state induced in a patient by the administration of such a drug in one of anesthetization. An hypnotic drug typically acts on the brain to produce a lessening or loss of consciousness in the patient. The extent to which the patient is anesthetized is often termed the “hypnotic level” or “depth of anesthesia.” In the present invention, the existing hypnotic level, or depth of anesthesia, in the patient is sensed and used to control the hypnotic drug administration to the patient in the manner of a closed loop, or feedback, regulator to achieve and maintain a desired level in the patient.[0004]M...

AI Technical Summary

Benefits of technology

[0020]It is, therefore, an object of the present invention to provide an improved method and apparatus for controlling the administration of an hypnotic drug to a patient in closed loop fashion that employs an accurate and highly responsive indication of the hypnotic condition of the patient, thereby to improve the administration of the drug. The indication used in the present invention can be made rapidly responsive to changes in the hypnotic condition of the patient. This is particularly advantageous in alerting an anesthesiologist that the patient may be emerging from an anesthetized state to a conscious state.

[0021]It is a further object of the present invention to provide a closed loop control method and apparatus which is capable of operating over a wide range of hypnotic conditions in the patient ranging from no hypnosis, i.e. consciousness, to deep hypnosis or anesthesia.

[0022]The method and apparatus of the present invention is simple to set up, employing a simple array of electrodes on the head of the patient. No self-normalization procedure as required in earlier disclosed techniques, is required with the technique of the present invention.

[0023]Briefly, in the present invention, electroencephalographic (EEG) signal data is obtained from the patient. For this purpose, one or more pairs of biopotential electrodes may be applied to the forehead of the patient. At least one measure of the complexity of the EEG signal data is derived from the data. The complexity measure of the EEG signal data may comprise the entropy of the EEG signal data. An EEG signal complexity measure obtained from the cerebral activity of the patient can be advantageously used in conjunction with a measure of patient electromyographic (EMG) activity resulting from the muscle activity of the patient to improve the response time of hypnotic level determination and of the feedback control of drug administration. The EEG signal data complexity measure is used in as the feedback signal in a control loop for an anesthetic delivery unit to control hypnotic drug administration to the patient in a manner that provides the desired hypnotic level in the patient.

[0026]The control of drug administration provided by the present invention may be improved by the use of additional data obtained from the patient, such as his / her cardiovascular characteristics or the end tidal concentration of volatile hypnotic drugs.

Problems solved by technology

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 hypnotic drugs, most of which are expensive.

During anesthesia, the level of painful stimulation can vary drastically and cause rapid changes in the hypnotic level of the patient, i.e. wake the patient up.

Because of the time required to compute a BIS value, the bispectral index may not be sufficiently rapid to warn the anesthesiologist that this is occurring.

Also, the bispectral index is contaminated by electromyographic (EMG) activity which may lead to misjudgment of the hypnotic level of a patient.

While an AEP index has been shown to distinguish between the conscious and unconscious states of a patient in an accurate manner, the correlation with drug concentration is not as good and has been reported as poorer than that for the bispectral index.

This tends to lessen the utility of the AEP index for use in closed loop hypnotic drug administration.

Also, the technique requires placing earphones on the patient and is limited to patients having adequate hearing.

The need for the self-normalization procedure presents a disadvantage to this procedure in that the anesthesiologist may forget to carry it out or carry it out at the wrong plane of anesthesia.

Also, there is no published evidence that the particular EEG-derived parameters chosen for measurement correlate very well with hypnotic levels.

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