Camera-Based Stress Detection via Hemoglobin Analysis
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Solution Overview
Problem
Current methods for stress detection, such as self-report questionnaires and invasive physiological instruments like ECG, are unreliable or inconvenient, limiting their effectiveness in assessing stress levels in various settings.
Innovation Solution
A camera-based system that uses transdermal optical imaging and machine learning to determine stress levels by analyzing hemoglobin concentration changes in facial images, processing bitplanes to identify heart rate variability and calculate stress through standard deviations and transformations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If physiological instruments like ECG are used to measure stress, then measurement reliability is improved, but device complexity and ease of operation deteriorate due to invasive requirements and need for trained professionals
Solution Approach 1:
The patent replaces invasive physiological instruments (ECG requiring electrode attachment) with a camera-based optical imaging system. The system captures images of the face and analyzes hemodynamic changes through transdermal optical imaging, eliminating the need for physical contact, electrodes, or trained professionals while maintaining stress measurement reliability
Solution Approach 2:
The patent creates an optical copy (image) of the facial region and analyzes hemodynamic changes from the captured light patterns. By working with the optical information rather than direct physiological signals, the system avoids invasive procedures while maintaining measurement accuracy through analysis of blood flow patterns visible in the facial tissue
2Reliability
If physiological instruments like ECG are used to measure stress, then measurement reliability is improved, but device complexity worsens due to requirement for specialized equipment and trained professionals
Solution Approach 1:
The patent replaces complex physiological measurement equipment (ECG machines requiring electrode placement and signal processing) with a simple camera-based system. The imaging device captures facial images and a processing system analyzes hemodynamic changes, dramatically reducing equipment complexity and eliminating the need for trained professionals
Solution Approach 2:
The patent extracts the essential measurement function from complex physiological instruments by isolating the key indicator (hemodynamic changes in facial tissue) and measuring it through a simple optical system. This extraction allows stress measurement without requiring the full complexity of ECG equipment or specialized training
3Ease of operation
If self-report questionnaires are used to assess stress, then ease of operation is improved, but measurement reliability deteriorates due to susceptibility to response bias
Solution Approach 1:
The patent introduces an optical intermediary (camera-based imaging system) that objectively captures physiological information about stress. Instead of relying on subjective self-reporting, the system uses transdermal optical imaging to measure actual hemodynamic changes, providing reliable stress assessment without the response bias inherent in questionnaires
Solution Approach 2:
The patent replaces the psychological measurement approach (self-report questionnaires) with a physiological measurement approach using optical imaging. By measuring actual blood flow changes in the face, the system provides objective, reliable stress data without relying on subjective perceptions or responses
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 provides non-invasive, accurate, and cost-effective stress level measurement, comparable to ECG methods, allowing for regular monitoring without the need for specialized equipment or trained professionals.
Implementation Method 1
receiving an image sequence capturing a body part of the human individual
Implementation Method 2
determining a set of bitplanes in the captured image sequence for each ROI that represent HC changes of the human individual using a trained machine learning model
Data Source
AI summary
A system and method for camera-based stress determination. The method includes: determining a plurality of regions-of-interest (ROIs) of a body part; determining a set of bitplanes in a captured image sequence for each ROI that represent HC changes using a trained machine learning model, the machine learning model trained with a hemoglobin concentration (HC) changes training set, the HC changes training set trained using bitplanes from previously captured image sequences of other human individuals as input and received cardiovascular data as targets; determining an HC change signal for each of the ROIs based on changes in the set of determined bitplanes; for each ROI, determining intervals between heartbeats based on peaks in the HC change signal; determining heart rate variability using the intervals between heartbeats; determining a stress level using at least one determination of a standard deviation of the heart rate variability; and outputting the stress level.