Wearable Stress Sensor Integrating Multi-Parameter Physiological Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for stress monitoring are limited as they cannot automatically quantify stress levels using multiple non-invasive techniques simultaneously, making it difficult to provide accurate and continuous feedback on stress levels, especially in dynamic environments like critical care transport and emergency response situations.
Innovation Solution
A wearable device that integrates multiple non-invasive stress monitoring techniques such as heart rate variability analysis, biological impedance analysis, Galvanic Skin Resistance, body surface and core temperature analysis, muscle twitch analysis, and respiratory rate analysis, allowing for continuous data collection and individualized stress level assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple non-invasive stress monitoring techniques are integrated into a single device, then measurement precision and reliability of stress level assessment is improved, but device complexity increases
Solution Approach 1:
The patent combines multiple independent stress monitoring techniques (heart rate variability analysis, biological impedance analysis, body surface temperature analysis, body core temperature analysis, muscle twitch analysis, and respiratory rate analysis) into a single integrated wearable device. This merging allows simultaneous collection of multiple physiological parameters to comprehensively assess stress levels, resolving the contradiction by achieving high measurement precision through multi-technique integration while managing device complexity through unified system architecture.
Solution Approach 2:
The wearable device is designed with universal multi-functionality, capable of performing six different stress monitoring techniques simultaneously. Each sensor module serves multiple purposes: for example, the ECG electrodes not only measure heart rate variability but also contribute to overall physiological monitoring. This multi-functional design improves stress assessment accuracy without proportionally increasing device complexity, as shared components serve multiple analytical functions.
2Productivity
If continuous data collection from multiple sensors is implemented, then productivity of stress monitoring is improved, but use of energy increases
Solution Approach 1:
The device implements periodic sampling of physiological parameters rather than truly continuous monitoring. The processor collects data from all sensors at defined intervals and performs batch analysis. This periodic action maintains high productivity by regularly updating stress assessments while significantly reducing energy consumption compared to continuous real-time processing, as the system can enter low-power states between sampling cycles.
Solution Approach 2:
The device performs self-service through automated data processing and stress level calculation. The processor automatically analyzes raw sensor data, applies stress assessment algorithms, and generates results without requiring external intervention. This self-service capability improves monitoring productivity by enabling autonomous operation while managing energy use through efficient onboard processing rather than requiring constant external computation resources.
3Ease of operation
If automated stress level determination is implemented, then ease of operation is improved, but device complexity increases
Solution Approach 1:
The device implements automated feedback mechanisms where the processor continuously monitors physiological parameters and provides real-time stress level assessments. The system automatically adjusts monitoring based on detected stress patterns and provides actionable feedback to users. This feedback loop simplifies operation by eliminating manual interpretation of raw data while the automated processing handles the complexity internally, presenting simple stress level indicators to users.
Solution Approach 2:
The processor acts as an intermediary between the complex sensor array and the user. It translates raw physiological data from six different sensors into simplified stress level assessments and actionable insights. This intermediary function hides the underlying system complexity from users, who interact only with simplified stress indicators, while the processor manages the complex data fusion and analysis algorithms required to integrate multiple sensing modalities.
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 device provides a comprehensive and accurate assessment of stress levels over time, enabling better patient stabilization, health monitoring, and ongoing health assessments for both responders and patients in various settings, improving immediate medical needs assessment and treatment efficacy.
Implementation Method 1
an ECG sensor configured to measure a heartbeat of the subject
Implementation Method 2
an impedance sensor configured to measure skin impedance of the subject
Implementation Method 3
a temperature sensor configured to measure a body surface temperature of the subject
Implementation Method 4
an accelerometer configured to measure a muscle twitch of the subject
Implementation Method 5
a respiratory sensor configured to measure a respiratory rate of the subject
Data Source
AI summary
A system for non-invasively monitoring a stress level of a subject is presented. A sensor is configured to monitor an attribute of the subject. A housing is configured to removably attach to the subject, the housing includes a processor in communication with the sensor, the processor is configured to retrieve data from the sensor, and use the data retrieved from the sensor to determine a stress level of the subject.