Drowsiness Estimation Using Ocular Temperature Correction
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Solution Overview
Problem
Conventional wakefulness detection methods based on blink count and eyelid droop are insufficient for early detection of drowsiness, as they often detect drowsiness too late for accident prevention, and struggle to accurately perceive the transition period between wakefulness and drowsiness.
Innovation Solution
A drowsiness estimation device that uses visible spectrum image data and surface body temperature distribution data to detect the ocular region temperature, applying corrections to estimate drowsiness by accounting for environmental temperature effects, allowing for earlier detection of the transition from wakefulness to drowsiness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional wakefulness detection using blink count and eyelid droop is used, then the detection method is simple and easy to implement, but the detection timing is too late for accident prevention
Solution Approach 1:
The patent changes the detection parameter from behavioral indicators (blink count, eyelid droop) to physiological parameter (ocular region temperature). Temperature changes in the ocular region occur earlier in the drowsiness transition period, enabling earlier detection while maintaining implementation feasibility through existing temperature sensing technology.
Solution Approach 2:
The patent replaces the mechanical/visual observation method (image processing of blink and eyelid movement) with a thermal detection method. This substitution enables detection of the transition period from wakefulness to drowsiness before visible behavioral changes occur, achieving earlier detection without significantly increasing system complexity.
2Reliability
If temperature parameter is used for drowsiness estimation, then early detection of transition period is enabled, but environmental temperature effects cause measurement errors
Solution Approach 1:
The patent introduces the ocular region temperature as an intermediary measurement point that reflects core body temperature changes associated with drowsiness. By measuring temperature at this specific location and using it to correct the drowsiness estimation temperature parameter, the system can distinguish between environmental temperature effects and physiological temperature changes, thereby improving measurement precision while maintaining early detection capability.
Solution Approach 2:
The patent implements a feedback mechanism where the ocular region temperature measurement is used to correct the temperature parameter for drowsiness estimation. This feedback loop compensates for environmental temperature influences by comparing the ocular region temperature (which is less affected by environment) with the target measurement location temperature, thereby improving measurement accuracy without sacrificing the ability to detect early drowsiness signs.
3Measurement precision
If ocular region temperature correction is applied, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent makes the ocular region temperature measurement serve multiple functions: it acts as both a direct indicator of drowsiness (through temperature changes) and as a correction reference for eliminating environmental temperature effects. This multi-functionality allows the system to improve measurement precision without adding separate correction mechanisms, thereby avoiding significant increases in device complexity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The device effectively determines the state of drowsiness by using temperature parameters corrected for the ocular region, enabling early detection and reducing the risk of accidents by monitoring drowsiness before the user enters a dozing state.
Implementation Method 1
an acquisition unit acquiring visible spectrum image data obtained by capturing a plurality of images of the person with visible spectrum wavelengths, and surface body temperature distribution data obtained by measuring a temperature distribution of a body surface of the person
Data Source
AI summary
A drowsiness estimation device comprises an imaging unit 1, a regional temperature calculation unit 6, and a weighted subtraction unit 7. The imaging unit 1 obtains visible spectrum image data in a visible spectrum capture mode and obtains infra-red image data indicating a surface body temperature distribution for a subject's body in an infra-red capture mode. The regional temperature calculation unit 6 detects a temperature of an ocular center region within the surface body temperature distribution indicated by the infra-red image data. The weighted subtraction unit 7 applies a correction to a temperature parameter for drowsiness estimation, based on the detected ocular center region temperature. A drowsiness estimation for the user is then performed according to the corrected parameter.