Dynamic Fever Threshold Detection Using Circadian Filters
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Solution Overview
Problem
Existing fever detection methods are prone to errors due to natural variations in body temperature caused by circadian rhythms, leading to inaccurate assessments of elevated body temperature as true fevers indicating physiological disease processes.
Innovation Solution
A temperature detection system that includes a temperature sensor and a processor, which adjusts temperature measurements using a circadian filter to determine a time-dependent fever threshold, improving the accuracy and sensitivity of fever detection by considering historical temperature data from a population to establish a corrected fever indication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a fixed temperature threshold is used for fever detection, then the detection method is simple and easy to implement, but the detection accuracy deteriorates due to circadian temperature variations
Solution Approach 1:
The patent applies dynamics by transitioning from a static fixed temperature threshold to a dynamic time-dependent threshold that varies according to circadian rhythm. The threshold is adjusted based on the time of day, allowing the detection criterion to adapt naturally to physiological temperature variations throughout the day, thus maintaining high detection accuracy without excessive complexity.
Solution Approach 2:
The patent changes the parameter of the temperature threshold from a constant value to a time-varying value that reflects circadian patterns. By modifying the threshold parameter dynamically based on temporal information, the system achieves accurate fever detection that accounts for natural temperature fluctuations while maintaining operational simplicity through pre-established threshold curves.
2Measurement precision
If temperature measurements are taken throughout the day to account for circadian variations, then detection accuracy improves, but the complexity of the detection system increases
Solution Approach 1:
The patent applies preliminary action by pre-establishing time-dependent temperature thresholds and circadian rhythm profiles before actual fever detection occurs. These reference standards are prepared in advance based on population data and physiological patterns, allowing the detection system to simply compare measured temperatures against pre-computed thresholds without requiring complex real-time analysis or multiple measurements throughout the day.
Solution Approach 2:
The patent introduces a circadian filter as an intermediary component that processes raw temperature measurements and adjusts them according to circadian rhythm patterns. This intermediary layer simplifies the detection process by automatically compensating for temporal variations, allowing the system to maintain high accuracy without requiring multiple measurements or complex decision logic.
3Reliability
If population temperature data is collected and processed to establish time-dependent thresholds, then fever detection sensitivity and specificity improve, but data processing requirements increase
Solution Approach 1:
The patent applies copying by creating simplified representations of complex population temperature data in the form of time-dependent threshold curves and circadian rhythm profiles. Instead of storing and processing individual temperature measurements from entire populations, the system uses aggregated statistical patterns captured in threshold models, dramatically reducing data storage and processing requirements while maintaining high detection reliability.
Data Source
AI summary
The present invention relates to more accurate indication of fever. Temperature data from a large population of individuals are obtained and the temperature data are processed to determine a threshold, at a fever bump, above a normal range of distribution. The fever threshold, along with an individual's temperature, is used to indicate if the individual has a fever. Further, circadian information may be utilized to adjust the temperature data for an individual or the population of individuals.