Rider Headgear Attention Monitoring with EEG and PPG Sensors
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Solution Overview
Problem
Existing systems for detecting drowsiness in two-wheeled vehicle riders face challenges in measuring real-time fatigue levels without causing discomfort and complexity due to the need for multiple sensors.
Innovation Solution
A headgear equipped with a single EEG sensor positioned near the prefrontal cortex, a PPG sensor on the forehead, and an image sensor, all integrated with a processor that determines an attention score based on these signals and vehicle riding parameters, generating an alert if the score falls below a threshold.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sensors are attached to the rider's body to measure fatigue level, then the measurement accuracy is improved, but the rider's comfort and attention are deteriorated
Solution Approach 1:
The patent combines multiple sensor functions into a single integrated headgear unit that houses both EEG and PPG sensors. This merging approach maintains the ability to measure multiple physiological parameters (brain electrical activity and blood flow rate) while eliminating the need for multiple separate attachments to the rider's body, thus preserving comfort and attention while achieving accurate fatigue assessment
Solution Approach 2:
The headgear is designed as a multi-functional device that simultaneously performs EEG-based brain activity monitoring and PPG-based blood flow rate measurement. This universal design allows a single device to capture multiple indicators of fatigue level, replacing the need for multiple specialized sensors attached to different body parts
2Reliability
If multiple sensors are used to measure brain electrical activity and blood flow rate, then the reliability of drowsiness detection is improved, but the device complexity and cost are deteriorated
Solution Approach 1:
The patent integrates EEG sensors and PPG sensors into a single headgear unit with a unified control unit that processes both brain electrical activity signals and blood flow rate signals. This consolidation reduces the number of separate communication channels and data processing pathways, thereby lowering system complexity and cost while maintaining reliable multi-parameter monitoring for accurate drowsiness detection
Solution Approach 2:
The control unit is designed as a universal processor capable of handling multiple sensor types (EEG and PPG) through standardized communication protocols. This multi-functional control architecture simplifies the overall system design by eliminating the need for separate dedicated processing units for each sensor type, reducing both complexity and cost while preserving detection reliability
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 monitors rider alertness, reducing the risk of accidents by providing timely alerts while minimizing sensor count, thus maintaining rider comfort and reducing system complexity and costs.
Implementation Method 1
an electroencephalogram (EEG) sensor... The EEG sensor generates a first signal which is an indicative of state of a brain of a rider... the EEG sensor measures a voltage difference between an active point and a reference point
Implementation Method 2
a photoplethysmogram (PPG) sensor... The PPG sensor generates a second signal which is an indicative of blood flow rate in the rider's brain... the PPG sensor measures the blood flow rate using low intensity infrared light
Data Source
AI summary
A headgear includes a shell including a shell exterior and a shell interior; a visor connected to the shell; an electroencephalogram (EEG) sensor in the shell interior that generates a first signal indicative of state of a brain of a rider; a photoplethysmogram (PPG) sensor in the shell interior that generates a second signal indicative of blood flow rate in the rider's brain; an image sensor disposed in the shell interior that captures an image of the rider and generate image data; and a processor that: receives the first signal from the EEG sensor; receives the second signal from the PPG sensor; receives the image data from the image sensor; determines an attention score of the rider based on the first signal, the second signal, and the image data; and generates an alert signal when the attention score is below a pre-defined threshold value.