Drowsiness Sensing System Using Electro-Dermal Potential and Physiological Signals
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Solution Overview
Problem
Current systems fail to accurately detect drowsiness in drivers, leading to potential accidents, as they often rely on incomplete or unreliable methods, and lack effective measures to mitigate drowsiness-related hazards while driving.
Innovation Solution
An electro-dermal potential sensing system integrated into a vehicle seat, combined with physiological sensors and cameras, processes signals to determine a driver's drowsiness state, triggering alerts or autonomous driving modes when necessary, and adjusts vehicle systems like adaptive braking and collision avoidance to compensate for driver drowsiness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sensor types (electro-dermal, physiological, camera) are integrated to improve drowsiness detection accuracy, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system divides drowsiness detection into multiple independent sensing modules: electro-dermal potential sensors for skin conductivity, physiological sensors for heart rate and respiration, and cameras for eye movement tracking. Each module independently measures specific parameters, and their results are integrated by a controller to achieve comprehensive and accurate drowsiness detection while maintaining modular system architecture.
Solution Approach 2:
The patent combines multiple types of sensors (electro-dermal, physiological, visual) and their respective signals into a unified detection system. The controller integrates data from all sensor types to comprehensively determine drowsiness state, leveraging the complementary strengths of each sensing modality to improve overall measurement precision beyond what any single sensor type could achieve alone.
2Reliability
If the system integrates multiple sensing modalities to reduce false drowsiness detection, then reliability is improved, but device complexity worsens
Solution Approach 1:
The controller receives signals from multiple independent sensor types and cross-validates their outputs to determine the driver's drowsiness state. By comparing and correlating data from electro-dermal sensors, physiological sensors, and cameras, the system provides mutual feedback verification that reduces false positives and improves detection reliability while managing complexity through intelligent signal integration.
3Object-affected harmful factors
If the system adjusts vehicle operations (braking, collision avoidance) in response to detected drowsiness, then safety is improved, but device complexity increases
Solution Approach 1:
When drowsiness is detected, the system proactively adjusts vehicle operations in advance to prevent accidents. The controller modifies braking system parameters, adjusts collision avoidance sensitivity, and modifies object avoidance calculations before a hazardous situation develops, counteracting the negative effects of driver drowsiness through preemptive system adjustments.
Solution Approach 2:
The controller serves as an intermediary between the drowsiness detection system and vehicle operation systems. It receives drowsiness state information from sensors and translates this into appropriate adjustments of braking, collision avoidance, and object avoidance systems, mediating the connection between detection and action while managing system complexity through centralized control logic.
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 system effectively detects drowsiness and reduces the risk of accidents by providing timely alerts and adaptive vehicle responses, ensuring safer driving conditions by quantifying drowsiness levels and adjusting vehicle operations accordingly.
Implementation Method 1
An electro-dermal potential system is at least partially integrated into the seat and configured to output an electro-dermal potential signal
Implementation Method 2
a camera to sense an image of the driver and produce a video output
Data Source
AI summary
A system includes an electro-dermal potential sensing system to sense electro-dermal potential of a person and configured to output an electro-dermal potential signal, as well as at least one physiological sensor to measure at least one physiological state and output at least one physiological signal. The system also includes a controller to receive the electro-dermal potential signal from the electro-dermal potential sensing system and the at least one physiological signal to determine a drowsiness state of the person.