Analytical Sample Container Classification Through Readability Checks
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Solution Overview
Problem
Existing analytical sample container identification systems in IVD laboratories face inefficiencies due to damaged or incorrectly applied visual identifiers, leading to errors, manual rerouting, and potential system downtime, especially for urgent tests.
Innovation Solution
A computer-implemented method and system that utilize an optical identifier reader and/or camera to assess the ability of analytical system apparatuses to read visual identifiers, enabling proactive detection and correction of defects before sample containers enter the system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If visual identifiers are attached to sample containers for automated identification, then identification efficiency is improved, but errors due to damage or incorrect application occur
Solution Approach 1:
The patent applies preliminary action by checking the visual identifier (barcode/QR code) quality before the sample container enters the analytical system. The optical identifier reader and camera capture images of the visual identifier, and the system assesses whether the identifier can be successfully read by the analytical apparatus. This preliminary check prevents identification errors from occurring during the analytical process, thereby maintaining both high productivity and reliability.
2Reliability
If manual inspection is performed for damaged visual identifiers, then identification accuracy is improved, but system productivity decreases
Solution Approach 1:
The patent implements self-service by enabling the analytical system to automatically assess and identify problematic visual identifiers without requiring manual inspection. The optical identifier reader and camera work together with the processing system to automatically determine whether a visual identifier is damaged or incorrectly applied. This automated self-assessment maintains identification accuracy while preserving system throughput by eliminating the need for manual intervention in most cases.
3Reliability
If unidentifiable sample containers are rerouted for manual inspection, then identification accuracy is improved, but system complexity and processing time increase
Solution Approach 1:
The patent applies the taking out principle by extracting the identification assessment function from the main analytical workflow. The system separates the visual identifier quality check as a distinct preliminary step that occurs before samples enter the main analytical system. This extraction allows problematic identifiers to be identified and handled separately, reducing the complexity of the overall system workflow while maintaining high identification accuracy.
4Loss of time
If early detection of defective visual identifiers is implemented, then system downtime is reduced, but additional detection apparatus is required
Solution Approach 1:
The patent applies universality by designing the optical identifier reader and camera to serve multiple functions. These apparatuses not only perform their primary function of reading visual identifiers during the analytical process but also serve as detection devices for assessing visual identifier quality before samples enter the system. This multi-functionality enables early detection of defective identifiers without adding separate dedicated detection apparatus, thereby reducing system downtime while avoiding excessive device complexity.
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 reduces system downtime and increases throughput by allowing for early detection and correction of defective visual identifiers, minimizing delays in urgent tests and reducing the need for manual intervention.
Implementation Method 1
the at least one apparatus comprises an optical identifier reader and/or camera; classifying the sample container associated with the visual identifier by characterizing the ability of the optical identifier reader and/or camera of the at least one apparatus comprised in the analytical system to read the visual identifier
Data Source
Figure 1~1B
Figure 2~2D
Figure 3
AI summary
A computer implemented method (80) for analytical sample container classification, wherein the method comprises: - obtaining (82) a digital representation of a visual identifier (3A) associated with a sample container (1); - identifying (84) at least one apparatus (20PRE-1) comprised within an analytical system (20), wherein the analytical system (20) is intended to perform at least one analytical test using the sample container (1), wherein the at least one apparatus (20PRE-1) comprises an optical identifier reader; - classifying (86) the sample container (1) associated with the visual identifier (3A) by characterizing the ability of the optical identifier reader of the at least one apparatus (20PRE-1) comprised in the analytical system (20) to decode the visual identifier (3A) associated with the sample container (1), to thereby generate a corresponding classification result characterizing the sample container (1) associated with the visual identifier (3A); and - outputting (88) a message defining the classification result.