Aspiration Pressure Ratio for Clog and Viscosity Differentiation
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Solution Overview
Problem
Aspirated sample volumes in clinical analysis are increasingly smaller, leading to erratic pressure differential values for liquids with different viscosities, and pressure profiles of higher viscosity liquids do not reach stable end-point values, making it difficult to differentiate between clogged and high-viscosity samples during the aspiration process.
Innovation Solution
The method involves analyzing the aspiration pressure profile to confirm a minimum sample volume and calculating the standard deviation of residuals from a linear regression analysis, followed by determining the ratio between the maximum negative pressure and equilibrium pressure to differentiate between clogged and high-viscosity samples, utilizing the linear relationship between this ratio and liquid viscosity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If smaller aspirated sample volumes are used to increase productivity, then the output per unit time is improved, but the pressure differential values become erratic and measurement precision deteriorates
Solution Approach 1:
The patent changes the parameters used for clog detection from absolute pressure differential values to a ratio of pressure differentials (first pressure differential divided by second pressure differential). This parameter transformation makes the detection method insensitive to sample volume size, allowing accurate clog detection in both small and large volume aspirations. The ratio parameter remains stable across different viscosity samples and volume sizes, resolving the measurement precision issue while maintaining productivity benefits from smaller volumes.
2Device complexity
If traditional pressure differential methods are used to detect clogs, then the detection process is simple, but the ability to differentiate between clogged and high-viscosity samples deteriorates
Solution Approach 1:
The patent transforms the detection parameter from absolute pressure differential to a ratio of pressure differentials. This parameter change enables differentiation between clogged samples and high-viscosity samples because the ratio behaves differently in these two scenarios: in clogged samples, the ratio exceeds a threshold value, while in high-viscosity samples, the ratio remains within normal range. This maintains simplicity of the detection process while dramatically improving differentiation accuracy.
Solution Approach 2:
The patent implements a feedback mechanism where the ratio of pressure differentials is calculated and compared against a threshold value to determine sample status. The system uses the first pressure differential (during aspiration) and the second pressure differential (after aspiration stops) to compute the ratio, then feeds this ratio back into the decision-making process to identify clogs versus high-viscosity samples. This feedback loop enables accurate real-time differentiation without complex additional hardware.
3Reliability
If aspiration pressure profile analysis is performed to confirm minimum sample volume, then the reliability of aspiration is improved, but the complexity of the analysis process increases
Solution Approach 1:
The patent applies partial action by focusing analysis on specific portions of the aspiration pressure profile rather than the entire profile. It identifies critical time points (when aspiration starts and when it stops) and measures pressure differentials at these specific moments. This partial analysis approach confirms minimum sample volume and detects abnormalities without requiring complex analysis of the complete pressure profile, thus maintaining reliability while limiting the increase in process complexity to essential measurements only.
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 effectively differentiates between clogged and high-viscosity samples, ensuring accurate aspiration and analysis by identifying abnormalities in the aspiration process, thereby improving the reliability of liquid handling in automated diagnostic analyzers.
Implementation Method 1
a pressure transducer to provide aspiration pressure data
Implementation Method 2
the ratio between the maximum negative pressure during aspiration and an equilibrium pressure prior to dispensation is calculated. It has been discovered that this ratio is unexpectedly linearly related to the viscosity of aspirated liquid
Data Source
AI summary
A method for differentiating between a liquid sample having clogs therein and a liquid sample having an abnormally elevated viscosity during a liquid aspiration process by relating the ratio between the maximum negative pressure during aspiration and an equilibrium pressure prior to dispensation to viscosity.