Dual Identifier Optical Imaging for Sample Tracking
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Solution Overview
Problem
Manual tracking and validation of biological samples in automated systems are labor-intensive and prone to errors, especially with increasing sample volumes, and existing automated systems may misread or fail to read identifiers, leading to inaccuracies and inefficiencies.
Innovation Solution
A computer-implemented method and system that images objects-of-interest with both alpha-numeric codes and barcodes, determining their positions and identifying the samples accurately using optical sensors, providing dual confirmation for accurate tracking and validation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual tracking and validation of samples is performed, then operator control and validation are maintained, but labor intensity increases and error probability increases
Solution Approach 1:
The patent replaces manual mechanical tracking with an automated optical imaging system that captures images of identifiers (barcodes, alphanumeric codes) on sample containers and racks. The system automatically processes these images to track and validate samples, eliminating manual labor while maintaining accuracy through dual-identifier verification.
Solution Approach 2:
The system creates optical copies (images) of the identifiers on sample containers and racks. By capturing and processing these image copies, the system can track and validate samples without physical manual intervention, reducing labor intensity while maintaining identification accuracy.
2Ease of operation
If automated scanning systems are used to track samples, then labor intensity is reduced, but additional components are required and identifier misreading occurs
Solution Approach 1:
The patent divides the identification system into two independent segments: a first identifier (barcode) and a second identifier (alphanumeric code). Both segments are imaged and processed separately, then cross-validated against each other. This segmentation allows the system to tolerate failures in one reading method while maintaining overall accuracy through the complementary second identifier.
Solution Approach 2:
The system prepares for potential reading failures by implementing dual-identifier verification before final sample identification. By requiring both the barcode and alphanumeric code to match, the system cushions against misreading errors that might occur with a single identifier system, ensuring higher reliability in automated operation.
3Reliability
If dual identifiers are used on samples, then identification accuracy is improved, but device complexity increases
Solution Approach 1:
The patent employs a single optical imaging system that serves multiple functions: it captures both barcode identifiers and alphanumeric code identifiers, processes both types of data, and performs cross-validation. This multi-functional approach achieves high identification accuracy without requiring separate specialized devices for each identifier type, thereby limiting the increase in device complexity.
4Productivity
If high throughput sample processing is implemented, then productivity increases, but manual tracking becomes more time-intensive and error-prone
Solution Approach 1:
The patent implements continuous automated imaging and tracking of samples throughout the high-throughput processing workflow. The optical system continuously captures images of identifiers on containers and racks, maintaining uninterrupted tracking even as sample volume increases. This continuous automated action maintains tracking accuracy regardless of processing throughput, eliminating the error-prone manual tracking that would otherwise be required at high volumes.
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
Enhances the accuracy and efficiency of sample identification and validation, reducing operator errors and ensuring compatibility checks, particularly suited for high-throughput biological assays like PCR, by using dual identifiers for confirmation.
Implementation Method 1
imaging the first object-of-interest including the two identifiers, wherein the imaging generates a first set of image data
Data Source
AI summary
A computer-implemented method for identifying a first object-of-interest is provided. The first object-of-interest includes two identifiers and a sample portion. The method includes imaging the first object-of-interest including the two identifiers. The imaging generates a first set of image data. The method further includes determining a position of the first object-of- interest in the field-of-view of an optical sensor and determining the two identifiers from the first set of image data. The method includes identifying the first object-of-interest based on the two identifiers.