Automated Analyzer Noise Removal via Approximated Curve
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Solution Overview
Problem
Optical detection methods for blood clotting reactions often calculate erroneous clotting times due to noise in light intensity data, especially at the initiation of the reaction, and existing noise removal techniques are inadequate when noises occur among aggregated substances.
Innovation Solution
An automated analysis device that detects and removes noise from light intensity data by calculating an approximated curve and comparing it with the actual data, identifying and excluding noise points to accurately determine clotting time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If optical detection is used to measure light intensity during blood clotting reactions, then test throughput and precision are improved, but noise in the light intensity data causes erroneous clotting time calculations
Solution Approach 1:
The patent applies preliminary action by pre-calculating an approximated curve from the light intensity data before identifying noise points. The controller first generates a smooth approximated curve representing the expected light intensity progression, then compares actual data points against this curve to identify deviations caused by noise. This preliminary curve calculation establishes a reference framework that enables subsequent noise detection and removal, resolving the contradiction by preparing the data structure in advance to eliminate erroneous measurements.
Solution Approach 2:
The patent uses an approximated curve as an intermediary between the raw light intensity data and the final clotting time calculation. This intermediate representation smooths out noise while preserving the essential clotting reaction pattern. By introducing this intermediary layer, the system can accurately determine clotting time without being directly affected by noise in the original measurements, thus maintaining both precision and reliability.
2Reliability
If data before time T1 is excluded to remove initial noise, then early-stage noise is reduced, but noise occurring between T1 and T2 still causes erroneous results
Solution Approach 1:
The patent replaces the mechanical time-based filtering approach (excluding data before T1) with a mathematical comparison approach. Instead of mechanically removing data based on time thresholds, the system substitutes this with a curve-comparison method that identifies noise points based on their deviation from the approximated curve. This substitution allows the system to retain all necessary data points while still eliminating noise, improving measurement precision without sacrificing reliability.
Solution Approach 2:
The patent changes the parameter used for noise identification from time-based criteria (before T1) to deviation-based criteria (difference from approximated curve). By changing the identification parameter from temporal to mathematical, the system can detect noise at any stage of the reaction, not just in the initial phase. This parameter change enables the system to maintain high measurement precision while achieving reliable noise removal throughout the entire measurement period.
3Ease of manufacture
If approximation functions are used to process measured data, then data processing is simplified, but noise points within the approximation range still produce erroneous clotting times
Solution Approach 1:
The patent applies preliminary action by first calculating the approximated curve and then using it as a reference for noise identification. The controller pre-processes the data to establish the approximated curve, which serves as a template for detecting noise points. This preliminary step maintains ease of processing while improving precision, as the pre-established curve enables systematic identification and removal of noise points that would otherwise contaminate the clotting time calculation.
Solution Approach 2:
The approximated curve serves as an intermediary that bridges the gap between simplified data processing and precise noise removal. The curve acts as a mediator that preserves the essential reaction pattern while filtering out noise. By using this intermediary, the system achieves both ease of processing (through curve approximation) and measurement precision (through noise point identification based on curve deviation).
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 precise detection and removal of noise in blood clotting reactions, leading to high-precision analysis of clotting times by distinguishing and eliminating noise points from the data, thereby improving the accuracy of clotting time calculations.
Implementation Method 1
a measuring unit for illuminating the reaction solution in the reaction container with light and for measuring an intensity of light scattered by the reaction solution
Data Source
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Figure 2
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AI summary
Provided is technology for blood clotting reactions capable of analyzing a blood clotting reaction with a high degree of precision by precisely detecting and removing noise, regardless of the location where the noise is generated in the light intensity data. This automated analyzer approximates, with an approximation curve, time series data for transmitted light intensity or scattered light intensity of light emitted onto a sample, and, in this process, removes abnormal data points that deviate from the approximation curve (see FIG. 2).