Eye State Monitoring with Dynamic Eyelid Gap Thresholds
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Solution Overview
Problem
Existing methods for determining a person's eye state, such as open or closed, are not sufficiently accurate, reliable, and robust, particularly in the presence of interfering factors like changes in viewing direction, lighting conditions, and variations in eye shape.
Innovation Solution
A method that dynamically determines eye state transitions by analyzing camera data for eyelid spacing, using a transition threshold value calculated from average values of falling and rising edges, and filtering out insignificant movements to ensure robustness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a fixed threshold value is used to determine eye state, then the determination process is simple, but accuracy deteriorates due to changes in viewing direction and lighting conditions
Solution Approach 1:
The patent implements dynamic threshold adaptation by continuously tracking the temporal progression of lid spacing and automatically adjusting the threshold value based on observed patterns. Instead of using a fixed threshold, the system adapts the threshold dynamically to account for changes in viewing direction, lighting conditions, and individual eye characteristics, thereby maintaining high accuracy across varying conditions while keeping the determination process computationally efficient.
2Measurement precision
If complex image processing is used to account for interfering factors, then measurement precision improves, but device complexity increases
Solution Approach 1:
The patent extracts only the essential feature needed for eye state determination - the temporal progression of lid spacing - from the complex image data. By focusing specifically on how lid spacing changes over time rather than analyzing all image features, the system achieves high measurement precision while avoiding the complexity of comprehensive image processing. This selective extraction of critical temporal information simplifies the overall system while maintaining accuracy.
Solution Approach 2:
The system performs preliminary analysis by continuously monitoring and storing the temporal progression of lid spacing before making eye state determinations. This preliminary tracking of lid spacing over time provides a foundation for accurate eye state assessment, allowing the system to distinguish between genuine eye closing and artifacts from lighting or viewing direction changes without requiring complex real-time processing.
3Device complexity
If traditional lid opening threshold methods are used, then device complexity is low, but reliability deteriorates due to false identifications from interfering factors
Solution Approach 1:
The patent implements a feedback mechanism where the system continuously monitors the temporal progression of lid spacing and uses this information to refine and adjust determination criteria. By analyzing the pattern of lid spacing changes over time and providing feedback to the determination process, the system reliably distinguishes between genuine eye closing and false signals from interfering factors such as lighting changes or head movements, thereby significantly improving reliability while maintaining relatively low system complexity.
Data Source
AI summary
A method and a monitoring device determine a binary eye state of a person. In the process, a monotonically decreasing slope with at least one specified minimum height is determined in a time curve of an eyelid gap which is determined in a camera-based manner. A current transition threshold for a change between an open and a closed eye is determined as a specified percentage value of the distance between the average value of a number of starting points of decreasing slopes and an average value of a number of corresponding end points. The eye is detected as being closed if the current eyelid gap is smaller than the current transition threshold. A monotonically increasing slope in the eyelid gap curve which has at least one specified minimum height is determined starting from the last end point. The eye is detected as being open if an end of the current increasing slope has been reached.