Automated Eye Tracking for Epilepsy Seizure Detection
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Solution Overview
Problem
Current methods for monitoring and managing epilepsy are hindered by inaccurate patient self-reporting, leading to delayed diagnosis, misdiagnosis, and ineffective treatment, resulting in prolonged seizures and increased healthcare costs.
Innovation Solution
A system that utilizes eye movement data and other patient monitoring data to determine seizure and side effect patterns, generating a personalized dose-response profile to guide treatment recommendations and optimize medication dosing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If patient self-reporting is used to monitor seizures, then data collection is simple and low-cost, but measurement precision deteriorates (accuracy drops below 50%)
Solution Approach 1:
The patent replaces the mechanical/manual self-reporting system with an automated optical monitoring system using eye-tracking technology. The system captures video footage of the patient's eyes and uses image processing algorithms to detect seizure-related eye movement patterns, thereby substituting human subjective reporting with objective automated detection.
Solution Approach 2:
The patent introduces an intermediary automated analysis system that processes video data of eye movements to detect seizures. This intermediary system acts as a mediator between the patient and the clinician, translating complex eye movement patterns into actionable seizure detection without requiring direct patient reporting.
2Device complexity
If conventional trial and error approach is used for medication selection, then device complexity remains low, but productivity deteriorates (takes up to 7 years for diagnosis and 18 years for surgery referral)
Solution Approach 1:
The patent implements a feedback mechanism where continuous monitoring of eye movement data provides real-time information about seizure occurrence and medication effectiveness. This feedback loop enables clinicians to adjust treatment plans based on objective data rather than waiting for prolonged trial and error periods.
Solution Approach 2:
The patent enables preliminary assessment of seizure patterns and medication response through continuous objective monitoring. By establishing baseline seizure characteristics and early treatment responses through automated eye-tracking analysis, clinicians can make more informed decisions earlier in the treatment process.
3Measurement precision
If additional tests are used to supplement poor data during treatment, then measurement precision improves, but loss of energy increases (costly and ineffective)
Solution Approach 1:
The patent makes the eye-tracking system multi-functional by using the same video capture and analysis infrastructure for multiple purposes: seizure detection, side effect monitoring, and treatment response assessment. This eliminates the need for separate specialized tests and reduces overall healthcare costs while maintaining high measurement precision.
Data Source
AI summary
Systems and methods for monitoring and managing neurological diseases and conditions are disclosed herein. In some embodiments, a method for monitoring a patient having a neurological disease or condition includes receiving, from one or more patient monitoring devices, first patient data for a baseline time period. The method can include determining, based on the first patient data, first seizure data and first side effect data during the baseline time period. The method can further include receiving, from the one or more patient monitoring devices, second patient data for a treatment time period, and determining, based on the second patient data, second seizure data and second side effect data during the treatment time period. The method can also include generating a personalized dose-response profile for the patient based on the first and second seizure data and the first and second side effect data.