Patient Risk Calculation via Circadian Temperature Correction
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Solution Overview
Problem
Existing risk calculation methods for patient health status are inaccurate due to variations in body temperature caused by factors unrelated to disease, such as circadian rhythms, basal metabolic rates, medication, and disease types, leading to incorrect risk assessments.
Innovation Solution
A risk calculation apparatus that adjusts body temperature measurements based on patient condition information, including circadian rhythms, basal metabolic rates, medication effects, and disease diagnoses, to provide a more accurate health status risk assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If body temperature is used directly for risk calculation without correction, then the calculation process is simple, but the risk assessment accuracy deteriorates due to variations from circadian rhythms and other factors
Solution Approach 1:
The system performs preliminary correction of body temperature measurements by calculating expected temperature values based on circadian rhythm patterns before comparing with reference values. This advance preparation eliminates the need for complex post-measurement adjustments and ensures accurate risk assessment from the start.
Solution Approach 2:
The patent introduces an intermediary correction mechanism that mediates between raw body temperature measurements and risk assessment. By using circadian rhythm models as an intermediary layer, the system translates complex biological variations into corrected temperature values that can be directly used for simple risk comparison.
2Measurement precision
If a fixed reference temperature is used for comparison, then the comparison process is straightforward, but the accuracy deteriorates when patient conditions vary (e.g., different diseases, age groups)
Solution Approach 1:
The reference temperature is transformed from a static fixed value to a dynamic value that automatically adjusts based on patient-specific factors such as age, disease type, and circadian phase. This dynamic adaptation maintains simple comparison logic while significantly improving accuracy across diverse patient populations.
Solution Approach 2:
The system applies different reference temperature standards tailored to specific patient conditions (e.g., different references for pediatric vs. adult patients, or for different disease states). This localized customization ensures each patient group is assessed against appropriate benchmarks without requiring a completely different system for each group.
3Reliability
If body temperature variations due to circadian rhythm are not corrected, then the measurement process remains simple, but the reliability of disease detection deteriorates
Solution Approach 1:
The system incorporates periodic circadian rhythm patterns into the correction process, using the known 24-hour cyclic nature of body temperature variations. By applying periodic correction functions that mirror natural circadian cycles, the system reliably distinguishes between normal rhythmic variations and pathological temperature changes.
Solution Approach 2:
The correction mechanism uses feedback from circadian rhythm models to continuously adjust temperature interpretations. By comparing measured temperatures against expected circadian-patterned values and applying corrective feedback, the system reliably identifies deviations that indicate disease without requiring complex diagnostic procedures.
Data Source
AI summary
A processor obtains a body temperature and patient condition information of a patient via a communication device. The processor calculates a comparison result by comparing the body temperature with a reference temperature obtained by the communication device and outputs a risk related to the health status of the patient based on the comparison result. The processor performs at least one of a process of correcting the body temperature based on the patient condition information when comparing the body temperature with the reference temperature, a process of setting the reference temperature based on the patient condition information when comparing the body temperature with the reference temperature, and a process of increasing or decreasing the comparison result based on the patient condition information.