Blood Coagulation Analyzer Curve Abnormality Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional blood coagulation analytical apparatuses face challenges in accurately detecting and classifying abnormal reaction process curves due to unstable reaction curves caused by complex multi-step reactions and foreign matter interference, leading to potential inaccurate test results.
Innovation Solution
An automatic analytical apparatus that includes a reaction container, a measurement unit for light intensity data collection, a control unit for processing data using approximation functions to calculate approximate curves, and an output unit for detecting and classifying abnormalities based on deviation feature information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If optical detection scheme is used for blood coagulation analysis, then measurement precision and non-contact measurement are improved, but reliability deteriorates due to unstable reaction curves caused by complex multi-step reactions and foreign matter interference
Solution Approach 1:
The system performs preliminary classification of reaction curves into normal and abnormal categories before detailed analysis. By预先 categorizing curves based on deviation from reference patterns, the system prepares for subsequent targeted processing, ensuring that abnormal curves are identified and handled appropriately without compromising overall measurement reliability
Solution Approach 2:
The system establishes a feedback mechanism where measured reaction curves are continuously compared against reference reaction curves stored in memory. When deviations exceed predetermined thresholds, the system provides feedback signals to classify the curve as abnormal and triggers appropriate responses, thereby maintaining measurement reliability through continuous monitoring and correction
2Productivity
If automatic abnormality detection is implemented, then productivity is improved by eliminating manual visual confirmation, but device complexity increases due to additional processing requirements
Solution Approach 1:
The automatic detection system segments the analysis process into distinct modules: data acquisition, reference comparison, deviation calculation, classification decision, and output generation. Each module performs a specific function independently, which simplifies the overall system design and makes the complexity manageable through functional decomposition
Solution Approach 2:
The system implements self-service automation where the apparatus automatically compares measured curves against stored references, identifies abnormalities, and generates classification results without requiring operator intervention. This self-automating capability increases productivity while the modular architecture keeps device complexity controlled
3Ease of operation
If threshold-based abnormality detection is used, then ease of operation is improved by providing clear classification criteria, but measurement precision deteriorates due to inability to detect gradual reaction curve changes
Solution Approach 1:
The system applies partial threshold-based detection for clear classification while also implementing excessive monitoring through continuous deviation calculation. By combining both approaches - using thresholds for definitive classification and continuous monitoring for detecting gradual changes - the system maintains ease of operation while improving measurement precision for subtle abnormalities
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
Enables accurate detection and classification of abnormal reaction process curves, improving the reliability of blood coagulation tests by identifying abnormalities such as two-step reactions, drift, jump, and noise, thereby reducing the likelihood of inaccurate test results.
Implementation Method 1
a measurement unit that irradiates a reaction solution in the reaction container with light and measures the intensity of transmitted light or scattered light
Implementation Method 2
a measurement unit that irradiates a reaction solution in the reaction container with light and measures the intensity of transmitted light or scattered light
Data Source
Figure 1
Figure 2
Figure 3
AI summary
An automatic analytical apparatus includes a reaction container for mixing a sample with a reagent to react the sample to the reagent, a measurement unit that irradiates a reaction solution in the reaction container with light and measures the intensity of transmitted light or scattered light, a control unit that processes time-series light intensity data obtained through the measurement in the measurement unit, a storage unit that stores one or more approximation functions each approximating to a time-series change in the light intensity data, and an output unit that outputs a processing result of the control unit. The control unit selects any one of the approximation functions stored in the storage unit, calculates an approximate curve indicating a time-series change in the light intensity data using the selected approximation function, calculates deviation feature information based on deviation information between the light intensity data and the approximate curve, and detects and classifies an abnormality included in the light intensity data using the deviation feature information.