Automated Analyzer Abnormality Detection via Reaction Curve Shape Analysis
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Solution Overview
Problem
Automated analyzers for clinical examinations face challenges in accurately detecting abnormalities in reaction processes due to vague evaluation of stirring quality and reagent degradation, leading to potential inaccuracies in measurement results.
Innovation Solution
The implementation of an automated analyzer that approximates time-series data using specific functions to calculate indices indicating shape features of absorbance changes, allowing for the detection of abnormalities by determining the presence or absence of deviations from a straight line, thereby evaluating the quality of stirring and reagent performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional detection methods (linearity check, ABS limit) are used, then the analysis can be performed with simple procedures, but the detection accuracy of abnormality is insufficient
Solution Approach 1:
The invention changes the parameter of abnormality detection from simple linearity checks and absorbance limits to shape feature quantities derived from approximation formulas. By calculating parameters such as curvature and inflection points from the reaction process curve, the system achieves more accurate abnormality detection while maintaining automated operation.
Solution Approach 2:
The invention replaces mechanical visual inspection methods with automated mathematical analysis. By using approximation formulas (such as polynomial fitting) to model the reaction curve and automatically calculating shape features, the system substitutes manual evaluation with computational analysis, improving both accuracy and automation.
2Reliability
If simple evaluation methods are used, then the operation is easy, but the stirring quality and reagent degradation cannot be accurately evaluated
Solution Approach 1:
The system performs self-evaluation by automatically analyzing its own reaction process data. The automated analyzer calculates shape feature quantities from its measured reaction curves and compares them against reference values, enabling the system to self-diagnose stirring quality and reagent status without external intervention.
Solution Approach 2:
The invention implements feedback by comparing measured shape feature quantities against reference values stored in the system. When deviations exceed predetermined thresholds, the system provides feedback indicating abnormality, allowing operators to take corrective actions based on objective quantitative data rather than subjective judgment.
3Measurement precision
If manual checking of reaction process data is performed, then the analysis procedure remains simple, but data reliability cannot be ensured
Solution Approach 1:
The invention replaces manual data checking with automated computational analysis. The system automatically fits approximation formulas to reaction process data, calculates shape feature quantities, and compares them against reference values, substituting human evaluation with systematic mathematical analysis that eliminates subjective bias and fatigue.
Solution Approach 2:
The system creates a mathematical model (copy) of the normal reaction process through approximation formulas. By comparing actual reaction curves against this idealized model, the system can automatically identify deviations without requiring manual interpretation of each data point, thereby ensuring consistent and reliable evaluation.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables reliable evaluation of both control and patient specimen measurements, ensuring accurate data reliability and proactive maintenance of the analyzer by quantifying stirring quality and detecting reagent degradation, thus preventing inaccurate results.
Implementation Method 1
The automated analyzer measures absorbance of a reaction solution throughout a certain time and calculates a concentration, an activity value, and the like of a measurement target substance based on a measurement result
Data Source
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AI summary
Provided are an automated analyzer and an automatic analysis method for highly accurately determining presence or absence of abnormality based on reaction process data obtained when concentration of a chemical component or an activity level of an enzyme is measured. The reaction process data is approximated by a function, and shape feature quantities indicating features of a shape of a curve section at an early stage of reaction are calculated. The obtained shape feature quantities are used to determine the presence or absence of abnormality.