Anomaly Detection in Hypnotic Level Monitoring
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Solution Overview
Problem
Current systems for monitoring the level of hypnosis during anesthesia face challenges in accurately interpreting EEG-based measurements due to external and internal interferences, and anomalies caused by medical conditions or drug interactions, which complicates the design of closed-loop drug administration systems.
Innovation Solution
A mechanism that utilizes drug effect information and autonomous nervous system (ANS) state information to detect anomalies by checking for consistency between changes in the measured hypnotic level and these information sources, alerting physicians and enabling safer control of drug administration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If EEG-based measurement is used to monitor hypnotic level, then the level of hypnosis can be monitored, but the measurement is vulnerable to external and internal interferences and anomalies
Solution Approach 1:
The system continuously monitors EEG signals and compares measured hypnotic levels against expected values based on administered drug concentrations. When discrepancies are detected, the system generates alerts to notify clinicians of potential anomalies or interference, enabling real-time correction and maintaining measurement reliability
Solution Approach 2:
The patent introduces an intermediary validation layer that cross-checks EEG-based hypnotic level measurements with pharmacokinetic models of drug concentration. This intermediary system acts as a mediator to identify and flag measurements that are inconsistent with expected drug effects, thereby filtering out false readings caused by interference or anomalies
2Extent of automation
If closed-loop drug administration system is implemented, then drug delivery can be automatically controlled, but the system complexity increases
Solution Approach 1:
The closed-loop system is segmented into distinct functional modules: EEG signal acquisition, hypnotic level calculation, drug concentration modeling, consistency validation, and automated drug delivery control. Each module operates independently with well-defined interfaces, reducing overall system complexity while maintaining full automation capability
Solution Approach 2:
The patent introduces an intermediary consistency check module that validates the relationship between measured hypnotic levels and expected drug concentrations before triggering automated drug administration adjustments. This intermediary layer simplifies the control logic by filtering out anomalous readings and providing a validated input stream to the drug delivery system
Data Source
AI summary
The invention relates to detection of anomalies related to a measurement of the hypnotic level of a subject. In order to detect when a measure indicative of the hypnotic level of a subject is anomalous either due to a medical reason or due to an interference, the measure is monitored and state information indicative of the activity of the autonomous nervous system of the subject and drug effect information indicative of the hypnotic drug effect in the subject are employed to check whether the measure fulfills a predetermined consistency condition requiring that the measure changes consistently with at least one of the drug effect information and the state information. An anomaly, indicative of an abnormal change in the measure, is detected when the measure fails to fulfill the predetermined consistency condition.