Wearable Sensor Fusion for Rapid Traumatic Brain Injury Detection
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Solution Overview
Problem
Diagnosing traumatic brain injuries (TBIs) following traumatic events is challenging without understanding the context of the event, necessitating rapid and accurate identification of the event and its impact.
Innovation Solution
A system utilizing wearable sensors, such as smart contact lenses, earplugs, and adhesive patches, collects data to detect traumatic events and assess TBI through a model that correlates sensor measurements with event types and injuries, enabling rapid diagnosis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If wearable sensors are used to collect data, then the ability to detect traumatic events is improved, but the device complexity increases
Solution Approach 1:
The system divides the complex detection task into multiple specialized sensor components, each measuring specific parameters (acceleration, overpressure, biometric data). This segmentation allows each sensor to be optimized for its specific function while collectively providing comprehensive traumatic event detection capability.
Solution Approach 2:
The wearable sensor system is designed to perform multiple functions: detecting acceleration forces, measuring overpressure waves, monitoring biometric data, and identifying various types of traumatic events. This multi-functionality reduces the need for separate specialized devices while maintaining comprehensive detection capability.
2Measurement precision
If a model is applied to correlate data values with traumatic events, then the diagnostic accuracy is improved, but the loss of time in data processing increases
Solution Approach 1:
The system pre-processes and structures sensor data in real-time according to expected traumatic event patterns, preparing the data for rapid model analysis. This preliminary organization of acceleration, overpressure, and biometric data enables the diagnostic model to quickly correlate values with potential TBIs without extensive processing delays.
Solution Approach 2:
The system continuously compares sensor measurements against the correlated model values and provides real-time feedback on detected traumatic events. This feedback mechanism allows for rapid iterative analysis, where the model is continuously refined based on incoming data streams, improving diagnostic speed and accuracy simultaneously.
Data Source
AI summary
A method, a structure, and a computer system for traumatic event detection. The exemplary embodiments may include collecting data using sensors worn by a user and identifying a traumatic event based on applying a model to the data, wherein the model correlates values of the data with traumatic events and traumatic brain injuries. The exemplary embodiments may further include identifying the traumatic brain injury resulting from the traumatic event.