Humidity-Corrected Drowsiness Estimation From Eyelid Movement
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Solution Overview
Problem
Existing drowsiness estimation systems suffer from accuracy degradation due to the influence of the surrounding environment, particularly humidity, which affects eyelid movements and leads to overestimation of drowsiness.
Innovation Solution
A drowsiness estimation system that incorporates humidity information to correct drowsiness estimation by using a camera to capture eyelid movements and a humidity sensor to adjust drowsiness estimation information based on environmental humidity, thereby reducing the impact of environmental conditions on accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If drowsiness estimation is performed based on eyelid movement information only, then the estimation process is simple, but the estimation accuracy degrades due to environmental humidity influence
Solution Approach 1:
The patent changes the parameters used for drowsiness estimation by introducing humidity information as an additional parameter. The correction unit modifies the drowsiness estimation value based on the relationship between humidity and eyelid movement characteristics, thereby improving accuracy without significantly increasing system complexity
Solution Approach 2:
The patent implements a feedback mechanism where the correction unit uses humidity information to adjust and correct the drowsiness estimation value. This feedback loop compensates for environmental influences on eyelid movement, improving measurement precision while maintaining a relatively simple estimation process
2Measurement precision
If humidity information is incorporated to correct drowsiness estimation, then estimation accuracy is improved, but device complexity increases due to additional sensors and processing
Solution Approach 1:
The patent segments the drowsiness estimation system into distinct functional units: an acquisition unit for collecting eyelid movement and humidity information, and a correction unit for processing this data. This segmentation allows the system to incorporate additional sensors and processing while maintaining clear functional separation and manageable complexity
Solution Approach 2:
The correction unit serves multiple functions: it receives both eyelid movement information and humidity information, processes their relationship, and outputs corrected drowsiness estimation values. This multi-functionality reduces the need for separate dedicated components for each function, thereby limiting the increase in device complexity
Data Source
AI summary
A drowsiness estimation information correction device includes: a drowsiness estimation information acquisition unit that acquires drowsiness estimation information that is based on an eyelid movement of a subject; and a drowsiness estimation information correction unit that calculates corrected drowsiness estimation information obtained by correcting the drowsiness estimation information with humidity information indicating humidity in a surrounding environment of the subject.