Head-Mounted Thermal Camera Stress Detection
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Solution Overview
Problem
Current methods for detecting stress levels through thermal measurements on the human face are hindered by the difficulty in collecting data while individuals engage in day-to-day activities, due to the bulkiness and expense of thermal cameras, as well as challenges with image analysis and movement compensation.
Innovation Solution
The use of inward-facing head-mounted thermal cameras positioned close to the user's head, which are lightweight and configured to take measurements from specific regions like the periorbital area, coupled with a computer that generates feature values and utilizes a model trained on stressed and non-stressed data to detect stress levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional thermal cameras are used to collect thermal measurements, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent replaces traditional complex thermal camera systems with a simplified sensor array that directly contacts facial regions. This mechanical substitution uses multiple simple temperature sensors positioned on different facial areas instead of a single complex thermal imaging camera, thereby maintaining measurement precision while reducing device complexity and cost.
2Ease of operation
If thermal cameras are positioned away from the face for external monitoring, then ease of operation is improved, but measurement precision deteriorates due to movement and distance
Solution Approach 1:
The patent divides the facial monitoring task into multiple segments by placing separate temperature sensors on different facial regions (forehead, cheeks, nose, etc.). This segmentation allows each sensor to remain close to its specific measurement point while the overall system remains easy to operate, as sensors can be integrated into everyday items like glasses or headbands rather than requiring a single external camera to track movement.
Solution Approach 2:
The patent embeds temperature sensors within structures that are already worn on the face, such as integrating sensors into eyeglass frames, headbands, or other facial accessories. This nesting approach allows the measurement system to be positioned close to the face for high precision while maintaining ease of operation, as the sensors move together with the wearer's natural movements rather than requiring separate positioning and tracking.
3Measurement precision
If multiple facial regions are monitored simultaneously, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent replaces a single complex thermal imaging camera with multiple simple contact temperature sensors distributed across facial regions. Each sensor is a simple temperature detection element rather than a complex imaging device, and their collective data provides enhanced measurement precision for stress detection while the individual sensor simplicity reduces overall system 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
Enables the collection of thermal measurements over extended periods while users perform various activities, providing accurate stress level detection with improved ease and cost-effectiveness by simplifying data acquisition and compensation for movement.
Implementation Method 1
utilize an inward-facing head-mounted thermal camera (CAM) located less than 10 cm from a user's head and configured to take thermal measurements of a region on a periorbital area (THROI1) of the user
Data Source
AI summary
Described herein are systems and methods for detecting a stress level of a user. In one embodiment, a system includes an inward-facing head-mounted thermal camera (CAM) and a computer. CAM takes thermal measurements of a region on a periorbital area (THROI1) of the user. The computer generates feature values based on THROI1, and utilizes a model to detect the stress level based on the feature values. The model was trained based on: previous THROI1 taken while the user was under elevated stress, and other previous THROI1 taken while the user was not under elevated stress. Some embodiments may utilize additional thermal cameras that take thermal measurements of other regions on the face, which may be utilized to detect the stress level.