Wearable EDA Stress Scoring With Sleep and Heart Signals
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Solution Overview
Problem
Conventional health monitoring devices are limited in accurately and automatically detecting stress levels of users, particularly due to limitations in collecting electro-dermal activity data.
Innovation Solution
A wearable device calculates a stress score using electro-dermal activity (EDA) data from external sensors, combined with sleep, activity, and heart features, to provide an accurate and automatic stress assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional health monitoring devices are used, then basic health parameters can be monitored, but accurate and automatic stress level detection is limited
Solution Approach 1:
The patent combines multiple data sources including electro-dermal activity data from external sensors, sleep features, activity features, and heart features into a unified stress score calculation system. This merging of diverse physiological parameters enables accurate and automatic stress level detection that overcomes the limitations of conventional single-parameter monitoring devices.
Solution Approach 2:
The wearable device is designed to perform multiple functions: monitoring electro-dermal activity, tracking sleep patterns, measuring activity levels, and calculating heart features. This multi-functional approach allows the device to collect comprehensive physiological data for stress assessment, enhancing both measurement precision and adaptability simultaneously.
2Measurement precision
If multiple physiological parameters are collected and processed, then stress assessment accuracy improves, but device complexity increases
Solution Approach 1:
The system automatically collects physiological data from multiple sensors, processes the information through integrated algorithms, and generates stress scores without requiring manual intervention. The device self-manages the complexity of multi-parameter integration by embedding the processing logic within the wearable unit itself, reducing the burden on external systems.
Solution Approach 2:
The patent introduces an intermediary processing layer that receives raw physiological data from various sensors, standardizes the information formats, and transforms multiple parameter types into a unified stress score. This intermediary processing mechanism simplifies the overall system architecture by centralizing the complexity management within a dedicated calculation module.
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 effectively determines stress levels by integrating various physiological and user-provided data, offering real-time stress monitoring and management capabilities.
Implementation Method 1
the stress score can be calculated using electro-dermal activity (EDA) data collected from an EDA sensor while the user is wearing the wearable device. More specifically, the sympathetic nervous system can trigger micro-perspiration throughout a person's body, so conductance between the EDA sensor on the wearable device and a hand or fingertip of the user will increase as the perspiration levels increase.
Data Source
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AI summary
Stress information can be determined for a user associated with a wearable device, such as a user wearing a wearable computing device including one or more sensors. At least some of this sensor data can be combined with relevant data provided by a user to calculate a stress score, such as may correspond to a current stress level or stress resilience level of that user. Changes in this stress score can be monitored over time, and appropriate actions taken, such as to provide information or recommendations to the user, or to modify operation of the wearable computing device.