Wearable Sensor System for Real-Time Dehydration and Thermal Stress Risk Assessment
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Solution Overview
Problem
Dehydration and thermal stress in subjects can lead to cognitive impairment and increased risk of injury due to delayed water replenishment and inadequate cooling, as the body loses 2% of its weight in water before awareness of dehydration, affecting decision-making and perception.
Innovation Solution
A system comprising sensors on the body to collect data on heart rate, oxygen consumption, motion, and ambient conditions, which calculates a risk value for thermal stress and dehydration by determining water loss, exertion, and ambient conditions, allowing for proactive prevention of negative effects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If water replenishment is delayed until the worker is aware of dehydration, then the worker's body has already lost 2% of bodyweight in water, but effective cooling cannot occur quickly enough to prevent thermal stress and cognitive impairment
Solution Approach 1:
The system performs preliminary action by continuously monitoring physiological parameters (heart rate, temperature, sweat rate) and environmental conditions to detect early signs of dehydration and thermal stress before the worker becomes aware of them. This allows proactive intervention with hydration recommendations and cooling alerts, preventing the 2% bodyweight loss threshold from being reached and eliminating the time delay associated with reactive water replenishment.
2Measurement precision
If multiple sensors are worn on the body to collect comprehensive data, then accurate risk assessment can be achieved, but device complexity and ease of operation are affected
Solution Approach 1:
The system applies universality by using a single integrated computing platform (smartwatch or mobile device) that performs multiple functions: it collects data from various sensors (heart rate, temperature, motion, environmental sensors), processes physiological and environmental data, calculates dehydration and thermal stress risk, and provides actionable recommendations. This multi-functional approach achieves accurate assessment without requiring separate dedicated devices for each function, thereby managing device complexity.
Solution Approach 2:
The system merges multiple data collection and processing functions into a single integrated platform. Rather than using separate devices for heart rate monitoring, temperature sensing, motion tracking, and environmental monitoring, the system combines all these functions into one unified system that processes multiple sensor inputs simultaneously to generate comprehensive risk assessment and hydration recommendations.
3Reliability
If continuous monitoring of physiological parameters is performed, then real-time risk values can be determined, but use of energy and data processing requirements increase
Solution Approach 1:
The system implements periodic action by updating physiological parameter monitoring and risk assessment at optimized intervals rather than continuously. The processor calculates dehydration and thermal stress risk values at regular intervals based on accumulated sensor data, balancing real-time detection needs with energy conservation. This allows the system to maintain reliable monitoring while reducing the energy consumption associated with constant data acquisition and processing.
Data Source
AI summary
Systems and methods to determine a risk factor related to dehydration and thermal stress of a subject are disclosed. Exemplary implementations may: generate output signals, by one or more sensors worn on a body of a subject, conveying information related to one or more of location of the subject, motion of the subject, temperature of the subject, cardiovascular parameters of the subject; store information related to the subject; obtain the output signals; determine in an ongoing manner, from the output signals, values of a water loss metric that correlates with estimated percentage of bodyweight of the subject lost in water; obtain heat index information for a contextual environment surrounding the subject; determine in an ongoing manner, from the output signals, values of an exertion metric that correlates with exertion of the subject due to work; and determine in an ongoing manner values for an aggregated risk factor of the subject.