Pupil Metrics for Anesthesia Depth Detection
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Solution Overview
Problem
Current methods for measuring depth of anesthesia, such as the Bispectral index (BIS) monitor, are unreliable due to lack of physiological basis, insensitivity to anesthetic agents, and reliance on subjective human assessment, leading to potential human error and inadequate sedation or awareness monitoring.
Innovation Solution
A system using video cameras to process pupil size data over time, determining depth of anesthesia, cognitive activity, and anesthetic perfusion across brain hemispheres, allowing for automated adjustments or alerts to ensure optimal sedation levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If BIS monitor is used to measure depth of anesthesia, then anesthesia depth measurement is provided, but the measurement reliability is poor due to lack of physiological basis and insensitivity to anesthetic agents
Solution Approach 1:
The patent replaces the electrical signal processing approach of BIS monitors with optical measurement of pupil dynamics. Video cameras capture pupil size and shape changes, which are then analyzed to determine anesthesia depth. This optical-biological approach provides a more direct physiological basis for measuring consciousness and anesthesia depth, overcoming the limitations of electrical signal interpretation.
Solution Approach 2:
The patent monitors dynamic changes in pupil parameters (size, shape, response to light) rather than static values. By tracking how pupil metrics change over time in response to anesthetic agents, the system captures the physiological response to anesthesia more reliably. This dynamic parameter approach allows detection of anesthesia depth and awareness states that static or electrical measures miss.
2Adaptability or versatility
If subjective human assessment is used to gauge patient state, then multiple measures can be considered, but human error increases and objectivity decreases
Solution Approach 1:
The system enables automated, objective assessment by having the monitoring system itself perform the evaluation rather than requiring human interpretation. Video cameras continuously capture pupil metrics, and algorithms automatically analyze these data to determine anesthesia depth and detect awareness. This self-service approach eliminates human subjectivity and error while maintaining the ability to consider multiple physiological indicators simultaneously.
Solution Approach 2:
The system provides continuous feedback through automated analysis of pupil dynamics. Real-time monitoring of pupil size and shape changes feeds back to the anesthesia depth determination, allowing for ongoing objective assessment without human intervention. This feedback loop maintains versatility in measuring multiple parameters while ensuring objectivity through algorithmic rather than subjective evaluation.
3Reliability
If video cameras are used to measure pupil size, then objective and reliable anesthesia depth measurement is achieved, but device complexity increases
Solution Approach 1:
The patent uses video cameras, which are multi-functional devices already present in many surgical settings for other purposes. By repurposing these existing cameras for pupil monitoring, the system achieves reliable anesthesia depth measurement without adding dedicated specialized equipment. The same camera can serve multiple functions including surgical visualization and anesthesia monitoring, thereby reducing overall system complexity.
Solution Approach 2:
The system creates a visual copy of the pupil through video imaging rather than requiring direct physical measurement devices. This optical copying approach simplifies the measurement process by using standard video technology to capture and analyze pupil characteristics. The copied visual information can then be processed algorithmically to determine anesthesia depth, avoiding the need for complex direct measurement apparatus.
4Measurement precision
If computer-intensive calculations are performed by BIS monitor, then anesthesia depth is computed, but processing time and computational resources increase
Solution Approach 1:
The patent extracts and monitors specific, easily measurable pupil characteristics (size, shape) that directly correlate with anesthesia depth rather than performing intensive computations on complex electrical signals. By focusing on these key extracted features from video imagery, the system achieves accurate anesthesia assessment with minimal computational overhead and rapid processing time.
Data Source
AI summary
A video feed of one or more pupils of a patient can be received and processed to determine a raw measure of pupil size of the one or more pupils over time. Based on this raw measure, at least one of a) a depth of anesthesia for the patient, b) an index of cognitive activity for the patient, and c) a degree of perfusion of an anesthetic being administered to the patient to one or both hemispheres of a brain of the patient can be determined such that one or more actions can be caused to be performed. Related systems, methods, and article of manufacture are described.