Medical Imaging Panic Detection Using Multi-Sensor Emergency Levels
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Solution Overview
Problem
Current medical imaging technologies lack automated systems to detect and respond to patient panic attacks, relying on pre-examination checks and technologist alertness, which are unreliable and slow.
Innovation Solution
A system with sensors to monitor patient physiological and psychological conditions, using an emergency level determination algorithm to automatically detect panic attacks and adjust imaging unit operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If automated panic detection is implemented using sensors and algorithms, then patient safety and detection reliability are improved, but device complexity increases
Solution Approach 1:
The system divides panic detection into multiple independent sensor modules (ECG, respiratory, kinetic, camera) that each monitor specific physiological or behavioral parameters. This segmentation allows the complex detection task to be distributed across simpler, specialized components, improving overall reliability while managing system complexity through modular design.
Solution Approach 2:
The medical imaging unit is equipped with multiple sensors that serve dual purposes: acquiring medical images and monitoring patient panic conditions. This multi-functionality reduces the need for separate dedicated panic detection equipment, thereby improving detection reliability without proportionally increasing overall system complexity.
2Measurement precision
If multiple sensors are used to monitor patient conditions, then detection accuracy is improved, but device complexity and cost increase
Solution Approach 1:
Different sensor types (ECG, respiratory, kinetic, camera) are segmented to monitor specific aspects of patient condition (heart rate, breathing, movement, facial expressions). Each sensor targets particular panic indicators, improving measurement precision through specialized detection while keeping individual sensor complexity low.
Solution Approach 2:
The system continuously processes sensor data and provides real-time feedback about patient panic levels to the control unit. This feedback mechanism allows the system to adjust monitoring intensity and trigger appropriate responses, improving detection accuracy through dynamic adaptation rather than relying solely on hardware complexity.
3Reliability
If real-time panic detection is implemented during imaging, then patient safety is improved, but examination time and system responsiveness requirements increase
Solution Approach 1:
Sensors continuously monitor patient conditions throughout the examination process, detecting panic attacks in their early stages before they escalate. This preliminary detection allows for immediate intervention, improving patient safety by preventing severe panic episodes while minimizing examination delays through early warning.
Solution Approach 2:
The panic detection system operates continuously during the entire medical imaging examination, providing uninterrupted monitoring of patient conditions. This continuous action ensures no panic attack goes undetected, improving safety without requiring intermittent pauses in the examination process.
4Speed
If automated emergency level determination is used, then response promptness is improved, but algorithm complexity and processing requirements increase
Solution Approach 1:
The emergency level determination is segmented into discrete thresholds and decision rules for different physiological parameters (heart rate ranges, breathing patterns, movement frequencies). This segmentation transforms complex algorithmic processing into simpler, rule-based evaluations that can be executed quickly with minimal computational overhead.
Solution Approach 2:
The system automatically processes sensor data and determines emergency levels without requiring manual technologist intervention for each reading. This self-service capability improves response speed by eliminating human reaction time delays, while the automated processing uses simplified algorithms that reduce computational complexity.
Data Source
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AI summary
The invention relates to a system for acquiring medical images of a patient comprising: a medical imaging unit for acquiring the medical images; at least one sensor for acquiring sensor data of the patient; an input unit for receiving the sensor data; an emergency level determination unit for deriving at least one value concerning at least one attribute of the patient based on the received sensor data, and for determining an emergency level of the patient based on the derived at least one value using an emergency level determination algorithm; and an output unit for informing a technician using the medical imaging unit about the determined emergency level and/or for influencing the usage of the medical imaging unit based on the determined emergency level. In an advantageous manner, the system can automatically detect an emerging and/or existing panic attack of the patient.