Head Impact Sensing With CT/MRI Co-Registration
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Solution Overview
Problem
Existing technologies face challenges in accurately and precisely sensing impacts, particularly head impacts, due to issues like relative movement between sensors and the head, false positive data, and insufficient processing power, which hinder meaningful data analysis and assessment.
Innovation Solution
A method involving simulation-based comparison of impact data with video footage, co-registration of sensors using MRI or CT scans, and analytical filtration to identify true positive data, combined with data compression and calibration techniques to enhance accuracy and precision.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If sensors are coupled to a body part to sense impacts, then impact detection capability is improved, but relative movement between sensors and the body part causes measurement precision to deteriorate
Solution Approach 1:
The patent introduces an intermediary co-registration process using medical imaging (CT or MRI scans) to establish the precise spatial relationship between sensors and anatomical landmarks. This intermediary measurement system allows the sensors to be positioned accurately relative to the body part, compensating for relative movement and improving measurement precision while maintaining impact detection capability.
2Stability of the object's composition
If sensors are coupled tightly to the skull using a mouthguard, then sensor stability is improved, but false positive data increases due to impacts from chewing, dropping, or tethering
Solution Approach 1:
The patent applies preliminary action by performing co-registration before impact sensing begins. The spatial relationship between sensors and anatomical landmarks is established in advance using CT or MRI scans, allowing the system to distinguish between normal mouthguard movements (chewing, dropping) and actual head impacts based on pre-established baseline positions and expected motion patterns.
3Productivity
If processing power is increased to analyze impact data accurately, then data analysis capability is improved, but device size and complexity increase
Solution Approach 1:
The patent applies partial action by implementing selective processing of impact data based on pre-established co-registration information. Rather than processing all sensor data at full computational power, the system uses the pre-acquired anatomical reference data to filter and prioritize only the most relevant impact events for detailed analysis, reducing the computational burden while maintaining accurate assessment capability.
Data Source
AI summary
Methods of analyzing and assessing users that have experienced impacts may include methods of identifying or filtering false positives, methods of co-registration of sensors, algorithms for translating sensed kinematics to relevant locations, and methods of assessing users based on historical and collected impact data combined with assessment data.


