Automatic Analysis Device Abnormality Detection and Factor Identification
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional automatic analysis devices for clinical examinations can determine measurement abnormalities but fail to identify the causative factors, making it difficult for operators to quickly address and improve measurement accuracy, especially when analyzing large numbers of samples.
Innovation Solution
An automatic analysis device equipped with an abnormality judgment unit and a factor judgment unit that utilize stored approximation formulas and factor information to detect abnormalities and determine the contributing factors, thereby reducing measurement accuracy deterioration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional automatic analysis devices determine measurement abnormalities using approximation formulas, then the occurrence of abnormalities can be detected, but the causative factors cannot be identified, making it difficult to quickly improve measurement accuracy
Solution Approach 1:
The patent segments the analysis into two distinct units: an abnormality judgment unit that detects whether measurement values are abnormal, and a factor judgment unit that identifies the specific causative factor. This segmentation allows the system to simultaneously perform abnormality detection and cause identification without increasing overall complexity, resolving the contradiction between detecting abnormalities and quickly identifying their causes.
Solution Approach 2:
The patent introduces a factor judgment unit as an intermediary component that bridges the gap between abnormality detection and causative factor identification. This intermediary unit uses stored factor information and approximation formulas to translate raw measurement data into meaningful diagnostic conclusions, enabling rapid identification of causative factors without compromising measurement precision.
2Reliability
If the device analyzes a large number of samples to determine abnormalities, then comprehensive measurement accuracy can be assessed, but it becomes extremely difficult for operators to quickly determine causative factors
Solution Approach 1:
The patent implements self-service functionality through the factor judgment unit, which automatically identifies causative factors without requiring operator intervention or complex manual analysis. The system uses stored factor information and approximation formulas to autonomously determine causes of abnormalities, maintaining high measurement reliability while significantly improving ease of operation even when analyzing large numbers of samples.
Solution Approach 2:
The patent applies preliminary action by pre-storing factor information and approximation formulas in the device memory before analysis begins. This allows the factor judgment unit to quickly retrieve and apply relevant data during operation, eliminating the need for operators to manually search through extensive sample data and enabling rapid causative factor identification while maintaining comprehensive analysis reliability.
3Difficulty of detecting and measuring
If conventional technology determines abnormality occurrence, then measurement issues can be detected, but there is no mechanism to determine the specific factor causing the abnormality
Solution Approach 1:
The patent applies universality by designing the factor judgment unit to handle multiple types of causative factors using a unified approach. The unit stores and processes various factor information types (reagent issues, sample problems, device malfunctions) through a single multi-functional system, making it easy to detect abnormalities and identify their specific causes without increasing system complexity or information loss.
Data Source
Figure 1~2
Figure 3
Figure 4~5
AI summary
An automatic analysis device includes: a factor storage unit 12b which stores each factor previously specified as a factor that could affect measurement accuracy of each of measurement items, while associating each factor with each measurement item; an abnormality judgment unit 103a which judges the presence/absence of an abnormality in a measurement value of each measurement item on the basis of an approximation formula and approximation formula parameters stored in an approximation formula storage unit 12a; and a factor judgment unit 103b which refers to the results of the judgment by the abnormality judgment unit 103a in a preset order, and would judge as an abnormality factor a factor stored in the factor storage unit 12b in association with a measurement item as an abnormality factor in a case where a plurality of measurement values regarding the measurement item have consecutively been judged to be abnormal. The operator is informed of the abnormality factor on the basis of the result of the judgment by the factor judgment unit 103b. With this configuration, deterioration in the measurement accuracy can be reduced through the detection of an abnormality in the measurement result and the determination of the causative factor.