Reduced Attention State Estimation via Microsaccade Sharpness
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for assessing attention reduction, such as the Psychomotor Vigilance Test (PVT) and other eye movement-based indices, face limitations including long test durations, inability to continuously measure attention, and inability to detect mild or severe sleepiness levels accurately, and lack practicality for daily use.
Innovation Solution
A reduced attention state estimation system that measures eyeball movement and eyelid activity to calculate indices like microsaccade sharpness, eyelid opening standard deviation, short-time and long-time eye-closure rates, and uses Naive Bayes estimation to determine attention levels, allowing for continuous and accurate measurement of attention reduction levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the Psychomotor Vigilance Test (PVT) is used to measure attention reduction, then measurement precision is improved, but test duration increases to 10 minutes
Solution Approach 1:
The patent extracts specific eye movement parameters (microsaccade sharpness, eyelid opening standard deviation, eye-closure rates) from the comprehensive PVT protocol, allowing attention assessment without requiring the full 10-minute test duration. This extraction enables continuous monitoring while maintaining measurement validity.
Solution Approach 2:
The patent implements continuous eye movement tracking throughout the test period, replacing the traditional discrete PVT administration. This continuous measurement approach maintains measurement precision while eliminating the need for repeated 10-minute tests, thereby reducing time loss.
2Ease of operation
If traditional eye movement indices like PERCLOS are used, then ease of operation is improved, but measurement precision for mild sleepiness is insufficient
Solution Approach 1:
The patent analyzes different local characteristics of eye movements separately: microsaccade sharpness for mild sleepiness detection, eyelid opening standard deviation for attention fluctuations, and eye-closure rates for doze detection. This localized analysis enables precise detection across multiple sleepiness levels while maintaining operational simplicity.
Solution Approach 2:
The patent segments the eye movement analysis into distinct parameters (microsaccade sharpness, eyelid opening standard deviation, short-time eye-closure occurrence rate, long-time eye-closure occurrence rate), each targeting specific sleepiness levels. This segmentation allows comprehensive assessment while keeping each individual measurement simple and operational.
3Measurement precision
If multiple eye movement parameters are measured continuously, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent employs a single eye movement tracking device that simultaneously measures multiple parameters (microsaccade sharpness, eyelid opening standard deviation, eye-closure rates). This multi-functional approach achieves high measurement precision without proportionally increasing device complexity, as one device performs multiple assessment functions.
4Productivity
If PVT is administered repeatedly, then productivity of assessment is improved, but loss of time accumulates
Solution Approach 1:
The patent enables continuous eye movement monitoring throughout the work period, allowing repeated assessments without interrupting productivity. This continuous action eliminates the need to stop work for multiple 10-minute PVT administrations, thereby increasing assessment productivity while minimizing time loss.
Solution Approach 2:
By extracting specific eye movement parameters from the PVT protocol, the patent enables frequent assessments during normal work activities without requiring dedicated test time. This extraction allows productivity improvement through continuous monitoring while reducing the cumulative time loss that would result from multiple full PVT administrations.
Data Source
AI summary
A reduced attention state estimation system includes an eyeball movement and eyelid activity measurement unit that measures an eyeball movement and an eyelid activity of a subject to obtain eyeball movement and eyelid activity data, a section determination unit that determines an eye opening section, an eye closing section, an eye-blinking section and a cluster section based on the eyeball movement and eyelid activity data, an eyeball movement and eyelid activity-related information calculation unit that calculates a sharpness of microsaccade or the like for each eye opening section based on the eyeball movement and eyelid activity data, and an attention assessment unit that determines an attention assessment or the like for an eye opening/cluster section, which is an eye opening section and cluster section, based on the sharpness of microsaccade or the like.