Stress Detection via Resting-State Physiological Baselines
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Solution Overview
Problem
Existing methods for determining an individual's stress level using physiological parameters require a learning phase where the individual is placed in stressful situations, which is restrictive and can be compromised by physiological variabilities, and calibration often necessitates being in a state of stress, making the process complex and unreliable.
Innovation Solution
A method that measures physiological parameters to establish a membership function based on resting state values, allowing for stress level determination without requiring the individual to be in a stressful state during calibration, using a sensor and processor to define stress levels through a range of variation and threshold distances, enabling continuous and simple calibration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a learning phase with stressful situations is implemented for calibration, then stress level determination accuracy is improved, but the complexity and restrictiveness of the calibration process increases
Solution Approach 1:
The patent inverts the conventional calibration approach by determining stress levels based on resting state measurements rather than stressful state measurements. Instead of calibrating during stress (conventional method), the system calibrates during rest and then detects deviations from this baseline to infer stress levels, thereby simplifying the calibration process while maintaining accuracy
Solution Approach 2:
The system performs preliminary calibration during resting states before actual stress detection is needed. By establishing baseline physiological parameters during calm periods in advance, the system prepares the membership functions and ranges of variation beforehand, eliminating the need for complex stressful calibration sessions later
2Measurement precision
If calibration is performed during stressful states, then the stress level determination is more accurate, but the ease of operation during calibration deteriorates
Solution Approach 1:
The patent reverses the calibration condition from stressful states to resting states. The system collects physiological data during calm periods to establish baseline ranges of variation, then uses these baselines to detect stress-induced deviations, making calibration as easy as remaining at rest while maintaining the ability to accurately detect stress
3Reliability
If individual physiological variability is accounted for, then the reliability of stress determination improves, but the complexity of the method increases
Solution Approach 1:
The patent applies local quality by creating individualized membership functions and ranges of variation specific to each person's physiological characteristics. Instead of using universal thresholds, the system adapts to each individual's baseline physiology during calibration, allowing reliable stress detection tailored to personal variability without requiring complex population-based models
Solution Approach 2:
The system performs self-calibration by automatically establishing individual baseline ranges of variation from the user's own resting state measurements. The membership functions are generated autonomously based on personal physiological data, eliminating the need for manual configuration or complex external calibration procedures while maintaining high reliability
Data Source
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AI summary
The invention is a method for determining an individual's stress level based on a physiological parameter of the individual, the method comprising: a) measuring a value of the physiological parameter at different calibration periods during a calibration time period; b) defining a range of variation for the values of the physiological parameter measured during the calibration periods; c) based on the range of variation, establishing a membership function that determines the individual's stress level as a function of the physiological parameter value, the stress level determined by the membership function being able to vary between: - a resting level, corresponding to the individual's resting state; - a stress level, corresponding to the individual's stressful state; - and at least one intermediate level, between the resting level and the stress level;d) following step c), measurement of a value of the physiological parameter during a measurement period, and determination of the individual's stress level by applying the membership function to the value of the measured parameter;