Imminent Loss of Consciousness Detection System
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Solution Overview
Problem
Current methods fail to effectively detect imminent loss of consciousness in high-stress environments, such as for pilots, leading to potential damage, injury, or death due to inadequate monitoring of physiological and environmental parameters.
Innovation Solution
A system comprising respiratory and circulatory sensors, a processor, and a user interface that detects respiration and circulation parameters to predict imminent loss of consciousness and alerts the user with auditory coaching to prevent it, differentiating between conditions like hypoxia, G-induced loss of consciousness, and hypocapnia.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If no detection system is used, then the system is simple, but loss of consciousness cannot be detected leading to damage, injury, or death
Solution Approach 1:
The detection system is divided into multiple independent sensor modules (respiratory sensor, circulatory sensor, environmental sensor) that each monitor specific physiological parameters. This segmentation allows the complex monitoring task to be distributed across simpler, specialized components while maintaining overall system reliability.
Solution Approach 2:
The system performs preliminary detection of physiological parameters before loss of consciousness occurs by continuously monitoring respiration rate, heart rate, oxygen saturation, and environmental conditions. This early warning capability allows preventive action to be taken before the actual loss of consciousness event happens.
2Measurement precision
If multiple physiological parameters are monitored, then detection accuracy improves, but device complexity increases
Solution Approach 1:
The monitoring system is designed with multi-functional sensors that can detect multiple physiological parameters simultaneously or sequentially. The system can adaptively select which parameters to monitor based on the operational context, reducing the need for all sensors to be active at all times and thereby managing complexity while maintaining measurement precision.
Solution Approach 2:
The system dynamically adjusts which physiological parameters are monitored and at what frequency based on changing operational conditions and detected trends. This adaptive parameter selection allows the system to maintain high detection accuracy for critical parameters while reducing monitoring of stable parameters, thereby managing system complexity.
3Loss of time
If real-time monitoring is implemented, then loss of consciousness can be detected early, but energy consumption increases
Solution Approach 1:
The system implements periodic monitoring of physiological parameters at varying intervals rather than continuous monitoring. During normal stable conditions, parameters are checked at longer intervals to conserve energy. When anomalies or trends toward loss of consciousness are detected, the monitoring frequency automatically increases to provide real-time detection capability.
Solution Approach 2:
The system applies full monitoring intensity only to critical parameters and moments when risk is elevated, rather than maintaining maximum monitoring of all parameters continuously. This selective intensive monitoring approach ensures timely detection of loss of consciousness events while minimizing overall energy consumption during stable operational periods.
Data Source
AI summary
Aspects relate to methods and systems for detecting imminent loss of consciousness. An exemplary system includes at least a respiratory sensor configured to detect a respiration parameter associated with a user, at least a circulatory sensor configured to detect a circulation parameter associated with the user, at least a processor configured to receive the at least a respiration parameter and the at least a circulation parameter, detect a condition associated with the user as a function of the at least a respiration parameter and the at least a circulation parameter, and identify an imminent loss of consciousness event associated with the user as a function of the at least a respiration parameter and the at least a circulation parameter, and at least a user interface configured to alert the user as a function of the imminent loss of consciousness event.