Personalized Stress Classification Model Using Biometric and Survey Data
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Solution Overview
Problem
Conventional methods for determining stress using biometric signals lack accuracy as they do not consider subjective psychological stress and are optimized for general populations, leading to lower accuracy when applied to individuals, and they primarily focus on physical stress without accounting for individual variations in stress perception.
Innovation Solution
A system and method that generates a personalized stress classification model using both biometric and survey data, incorporating physical and psychological information to improve stress determination accuracy by creating a model tailored to each user, which includes collecting biometric data and survey data, generating a personalized model through machine learning, and determining stress using this model.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a general stress classification model based on biometric signals is used, then the system can analyze physical stress objectively, but the accuracy of stress determination for individual users is lowered because it does not account for individual variations in stress perception
Solution Approach 1:
The system performs preliminary actions by collecting survey data during a training period before final stress determination. Users complete stress perception surveys that capture their subjective stress experiences, which are then used to personalize the stress classification model for that individual user before actual stress monitoring begins
Solution Approach 2:
The system changes parameters by adjusting the stress classification thresholds and model parameters based on individual user data. The personalized model modifies the general biometric stress indicators by incorporating user-specific survey responses, transforming the fixed general model into an adaptive individualized model that accounts for personal stress perception variations
2Extent of automation
If only biometric signals are used for stress analysis, then the system can provide automated objective measurement, but psychological stress is not considered leading to low accuracy
Solution Approach 1:
The system merges two different types of data: objective biometric signals (heart rate, skin conductance, etc.) and subjective survey responses. By combining these complementary data sources, the system captures both the physiological and psychological aspects of stress, creating a more comprehensive and accurate stress assessment than either method could achieve alone
Solution Approach 2:
The survey acts as an intermediary that bridges the gap between objective biometric measurements and subjective stress perception. The survey data serves as a mediator that translates individual psychological experiences into quantifiable parameters that can be integrated with physiological data to improve overall stress determination accuracy
Data Source
AI summary
Provided are a system, apparatus, and method for determining stress. The apparatus according to the present invention includes a communication interface and a processor connected to the communication interface, wherein the processor collects biometric data and survey data of a user through the communication interface, generates a personalized stress classification model on the basis of the biometric data and the survey data, and determines whether the user is stressed using the personalized stress classification model.