Body Weight Correlation Analysis for Vital Sign Abnormality Detection
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Solution Overview
Problem
Existing remote monitoring systems for vital signs lack the ability to accurately assess the degree of abnormality in correlation relationships between different vital signs and body weight, limiting their effectiveness in providing comprehensive diagnostic support.
Innovation Solution
A weight measurement apparatus and biological information processing system that calculates the degree of abnormality in body weight and correlation relationships using a precision matrix, normalizes vital sign data, and generates diagnostic support information based on these calculations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional vital sign monitoring is used, then basic remote monitoring is possible, but the ability to assess abnormality in correlation relationships between vital signs and body weight is insufficient
Solution Approach 1:
The system segments the assessment of abnormality into two independent components: (1) assessment of individual vital sign abnormalities using a precision matrix, and (2) assessment of correlation relationship abnormalities between vital signs and body weight. This segmentation allows each component to be optimized independently, improving overall measurement precision without requiring complete system redesign.
Solution Approach 2:
The patent introduces a precision matrix as an intermediary mathematical tool that mediates between raw vital sign data and abnormality assessment. This precision matrix serves as a bridge, transforming correlation data into actionable abnormality degrees while maintaining system manageability and avoiding excessive complexity.
2Reliability
If comprehensive diagnostic support is provided, then diagnostic accuracy is improved, but the complexity of data processing increases
Solution Approach 1:
The data processing is segmented into distinct modules: (1) acquisition of vital sign data, (2) construction of precision matrix, (3) calculation of abnormality degree for individual signs, and (4) calculation of abnormality degree for correlation relationships. This modular segmentation reduces overall processing complexity by making each step independent and manageable.
Solution Approach 2:
The precision matrix is constructed in advance using normal data before actual diagnosis occurs. This preliminary action stores the correlation relationships between vital signs and body weight in a ready-to-use format, eliminating the need for complex real-time calculations during diagnosis and reducing processing complexity at the critical diagnostic stage.
3Adaptability or versatility
If correlation relationships between vital signs and body weight are analyzed, then diagnostic support is enhanced, but measurement precision requirements increase
Solution Approach 1:
Normal data is collected and the precision matrix is constructed in advance before actual diagnosis. This preliminary action establishes reference correlation relationships that can be directly compared against patient data, reducing the stringency of real-time measurement precision requirements while still enabling comprehensive diagnostic support.
Solution Approach 2:
The system transforms raw vital sign measurements into normalized values through the precision matrix, which adjusts parameters based on established correlation relationships. This parameter transformation allows the system to accommodate variations in measurement precision by normalizing data to a standard reference framework, thereby maintaining diagnostic capability without demanding extremely high measurement precision.
Data Source
AI summary
A weight measurement apparatus of the embodiment includes processing circuitry. A weight measurement apparatus includes the processing circuitry configured to acquire a body weight of a subject and biological information other than the body weight, calculate a degree of abnormality of the body weight based on a predetermined threshold, calculate a degree of abnormality of a correlation based on a correlation relationship between the body weight and the biological information, and output information indicating the degree of abnormality in the body weight and information indicating a degree of deviation between the correlation relationship used in the calculating of the degree of abnormality in the correlation and a reference correlation relationship.