Smartwatch Temperature Monitoring with Personalized Baselines
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Solution Overview
Problem
Existing body temperature measurement devices fail to accurately account for individual characteristics, daily rhythms, hormonal changes, and environmental factors, limiting their ability to provide precise temperature readings and disease prediction based on temperature data.
Innovation Solution
A smartwatch-based body temperature monitoring system that includes a baseline measuring unit, personal variable input unit, and controller to adjust temperature measurements for age, gender, circadian rhythms, hormonal changes, physical activity, stress, and environmental factors, enabling accurate temperature data collection and disease prediction by analyzing deviations from normal ranges.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing temperature measurement devices simply measure and record temperature without considering individual characteristics and environmental factors, then the device complexity is low and ease of operation is high, but measurement precision is insufficient
Solution Approach 1:
The system segments temperature monitoring into multiple functional modules: a wearable sensor unit for temperature detection, a mobile terminal for data processing and analysis, and a server for comprehensive management. This segmentation allows each module to focus on specific tasks, improving measurement precision while keeping individual components relatively simple.
Solution Approach 2:
The mobile terminal acts as an intermediary between the wearable sensor and the server, processing temperature data locally by comparing it with stored baseline values and personal variables. This intermediary approach enables sophisticated analysis without requiring the wearable sensor itself to be overly complex.
2Measurement precision
If temperature measurement systems only provide basic measurement and recording functions, then the device is simple to operate, but it cannot account for various environmental factors and personal variables affecting temperature
Solution Approach 1:
The system automatically collects personal variables (age, gender, weight, height) and environmental data, then performs baseline establishment and temperature analysis without requiring user intervention. The mobile terminal automatically compares current temperature readings against stored baselines and sends notifications when anomalies are detected, making the system self-sufficient and easy to use.
Solution Approach 2:
The system performs preliminary actions by establishing individual baseline temperature ranges during an initial monitoring period before actual disease detection begins. Personal variables and environmental factors are collected and stored in advance, enabling accurate temperature interpretation without requiring users to understand complex medical criteria.
3Loss of information
If existing systems only measure temperature without analyzing patterns over time, then the measurement process is simple, but the system cannot predict diseases or provide meaningful health insights
Solution Approach 1:
The system implements continuous feedback by monitoring temperature trends over time, comparing current readings against established baselines, and providing notifications when deviations occur. The mobile terminal analyzes temperature patterns and provides feedback to users through alerts and health insights, transforming raw temperature data into actionable health information.
Solution Approach 2:
The system performs comprehensive data analysis by collecting not only temperature readings but also personal variables, environmental factors, and lifestyle information. This excessive data collection enables sophisticated disease prediction algorithms to identify patterns that would be invisible with minimal data, providing valuable health insights while managing complexity through automated processing.
Data Source
AI summary
Disclosed is a body temperature monitoring system based on a smart watch, the system including: a baseline measuring unit configured to convert information on body temperature of a user, measured at predetermined intervals, into data; a personal variable input unit configured to store information on age and gender of the user; and a controller configured to compare and analyze a body temperature value converted by the baseline measuring unit and a normal body temperature range derived by the personal variable input unit. The controller is further configured to: determine whether the user's current body temperature falls within the normal body temperature range based on information produced from the baseline measuring unit and the personal variable input unit; and identify a disease type by analyzing a duration, a value, and a timing of deviation of the user's body temperature from the normal body temperature range.