Automated Stress Score Calculation System
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Solution Overview
Problem
It is challenging to quantify an individual's chronic stress level effectively before they reach the burnout stage, as stress is contributed by various sources such as work commitments, e-mails, travel, and environmental conditions, making it difficult to manage and potentially leading to health issues like clinical depression, cardiovascular diseases, and cancers.
Innovation Solution
A computer-implemented method and system that collects and processes parameter data from various stress-contributing factors like e-mail correspondence, travel, tasks, appointments, ambient noise, and weather to calculate a stress-score, which is normalized and automatically transmitted, allowing for automated stress monitoring and management without human intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple stress factors are collected and processed to calculate a comprehensive stress-score, then the accuracy of stress quantification is improved, but the system complexity increases
Solution Approach 1:
The system divides the complex stress assessment into separate modular components: data collection modules for different stress factors (work, travel, environment), a normalization module that standardizes different parameter types, and a calculation module that aggregates results. This segmentation allows accurate multi-factor stress quantification while managing system complexity through modular architecture.
Solution Approach 2:
The system creates a universal stress-score calculation framework that can handle multiple different stress factors (email volume, travel distance, noise levels, weather conditions) through a single integrated process. The normalization and aggregation mechanisms work universally across different parameter types, enabling comprehensive stress assessment without requiring separate specialized systems for each factor.
2Productivity
If automated stress monitoring is implemented without human intervention, then productivity is improved, but the difficulty of detecting and measuring stress increases
Solution Approach 1:
The system performs self-service by automatically collecting stress factor data from various sources, normalizing the data, calculating the stress-score, and providing feedback without requiring human intervention. The automated pipeline handles the entire process from data gathering to interpretation, maintaining high productivity while the structured approach to data processing makes stress detection more systematic and less difficult.
Solution Approach 2:
The system implements feedback mechanisms where the calculated stress-scores and identified stress factors are automatically communicated back to the user. This feedback loop enables the system to monitor stress levels continuously and provide timely information, improving productivity while the structured feedback process makes stress detection more transparent and measurable through clear, actionable results.
Data Source
AI summary
There is shown and described a computer implemented system and method for analyzing an individual's personal stress level and providing a stress-score representing the individual's personal stress level. A plurality of parameters are received into a memory from at least one computing device and each of the parameters respectively represents a factor of the individual's life that contributes to a level of stress for the individual. The received parameter data is processed by executing code in a processor that configures the processor to normalize the parameter data by assigning, for each of the received parameters, a respective parameter score that represents a relative value of the parameter. The individual's stress-score is calculated as a function of the normalized parameter data, the stress-score is automatically transmitted to the at least one computing device, using code executing in the processor and free of human intervention.