Sample Analyzer Optical Detection for Platelet Type Mismatch
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Solution Overview
Problem
In platelet aggregation testing, there is a challenge in accurately distinguishing between samples with different platelet concentrations, such as PRP and PPP, which can lead to incorrect recognition of sample types, potentially causing errors in analysis.
Innovation Solution
A sample analyzer system that includes a measurement part for optical analysis, a processing part to calculate platelet aggregation, and an alarm part to alert operators of potential type mismatches based on measured optical information, allowing for accurate identification of sample types and prevention of errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If samples with various platelet concentrations are used for platelet aggregation testing, then the testing flexibility and applicability are improved, but the risk of incorrect recognition of sample types increases
Solution Approach 1:
The system changes the parameter of optical density measurement to automatically distinguish between PRP and PPP samples. By measuring the optical density of samples and comparing against predetermined thresholds, the system can identify sample types without relying on operator input, thus maintaining testing flexibility while eliminating recognition errors
Solution Approach 2:
The system implements feedback by continuously monitoring optical density measurements and automatically adjusting sample type identification based on measured values. The measurement results are fed back to the control unit, which then determines the correct sample type and proceeds with appropriate analysis parameters
2Device complexity
If manual sample type identification is performed by operators, then the device complexity is reduced, but the measurement precision and reliability of sample type identification deteriorates
Solution Approach 1:
The system performs self-service by automatically identifying sample types through optical density measurements without requiring operator intervention. The measurement unit measures the optical density, and the control unit automatically determines whether the sample is PRP or PPP based on predetermined criteria, eliminating human error while maintaining system simplicity
Solution Approach 2:
The system replaces manual mechanical identification methods with optical measurement and automated control. Instead of relying on operators to visually or manually identify sample types, the system uses optical density measurement and electronic control to automatically determine sample types, significantly improving precision
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
The system effectively determines the correct type of sample by analyzing optical information and actuating an alarm for potential mismatches, reducing the likelihood of incorrect recognition and ensuring accurate analysis results.
Implementation Method 1
a measurement part (10) for measuring optical information of a sample
Data Source
AI summary
A sample analyzer comprises an input to select a sample type to be measured from a plurality of platelet sample types of differing concentrations, a measurement part to obtain optical information of a sample, a processing part that calculates platelet aggregation information from the optical information, and an alarm part. The processing part determines whether the actual measured sample type differs from the inputted sample type based on the optical information from the measurement part, and actuates the alarm part accordingly.