Blepharometric Monitoring for Longitudinal Neurological Change Detection
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Solution Overview
Problem
Current technologies for monitoring neurological conditions through blepharometric data are limited by their ability to perform only point-in-time analysis, which is inadequate for degenerative and progressive conditions, and require specialized testing that is expensive and impractical for widespread use.
Innovation Solution
A system configured to collect blepharometric data periodically from subjects, using a sensor device mounted in vehicles to monitor passengers or operators, and processing this data through a blepharometric data monitoring system that includes modules for subject identification, data processing, historical data maintenance, and variation analysis to identify indicators of neurological conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If point-in-time analysis is used for neurological monitoring, then device complexity is reduced, but measurement precision and diagnostic value are insufficient for degenerative conditions
Solution Approach 1:
The system performs preliminary data collection and processing by capturing blepharometric data continuously or periodically and pre-processing it to extract relevant features. This preliminary action enables later comprehensive analysis without requiring complex real-time processing, thus resolving the contradiction between simple device operation and precise diagnostic capability.
Solution Approach 2:
The patent transitions from single-point temporal analysis to multi-dimensional analysis by incorporating historical data storage and comparison capabilities. This adds the dimension of time to the analysis, allowing detection of trends and patterns that single-point analysis cannot capture, thereby improving diagnostic precision without significantly increasing device complexity.
2Measurement precision
If specialized testing equipment is used for neurological analysis, then measurement precision is improved, but ease of operation and accessibility deteriorate due to cost and complexity
Solution Approach 1:
The system uses a camera, which is a universal and widely available device, to perform blepharometric analysis. By making the sensing component universal and commonly accessible, the system maintains ease of operation while achieving specialized neurological monitoring capabilities through software-based analysis of eyelid movement patterns.
Solution Approach 2:
Instead of requiring specialized medical testing equipment, the system creates a functional copy of clinical blepharometric analysis capabilities using commercially available cameras and image processing algorithms. This copying approach enables precise neurological monitoring without the need for expensive specialized equipment, improving accessibility while maintaining measurement precision.
3Measurement precision
If historical blepharometric data is collected and stored, then measurement precision for detecting neurological changes is improved, but loss of time and data storage requirements increase
Solution Approach 1:
The system extracts and stores only the essential blepharometric features and parameters needed for neurological analysis, rather than storing complete raw video sequences. This extraction approach reduces data storage requirements and processing time while maintaining the precision needed for detecting neurological condition changes through comparison with historical data.
Data Source
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AI summary
Technology described herein relates to extended monitoring and analysis of subject neurological factors via blepharometric data collection, for example including devices and processing systems configured to enable such extended monitoring. This may include hardware and software components deployed at subject locations (for example in-vehicle monitoring systems, portable device monitoring systems, and so on), and cloud-based hardware and software (for example cloud-based blepharometric data processing systems. The technology allows for user blepharometric data to be collected across a plurality of monitoring sessions, in some cases via different collection technologies, thereby to analyse changes over time. For example, this can assist in identifying risks of degenerative neurological conditions.