Blood Sample Rotation Device for Automated Defect Detection
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Solution Overview
Problem
Automated blood sample processing systems lack an effective mechanism for prescreening defective samples, leading to improper processing and inaccurate results due to inadequate manual visual inspection opportunities.
Innovation Solution
A sample tube gripping and rotation device integrated with a specimen integrity monitor that uses sensors to capture color data from blood samples, processing it to identify defects such as hemolysis, clotting, and lipemia before they reach analyzers, and routing defective samples for manual inspection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated systems process blood samples without manual inspection, then productivity increases, but sample quality control deteriorates
Solution Approach 1:
The system performs self-inspection by automatically capturing images of samples and using image processing algorithms to detect defects such as hemolysis, clotting, and improper labeling. The automated system inspects itself without requiring manual intervention, maintaining both high throughput and quality control.
Solution Approach 2:
Manual visual inspection is replaced with an automated image capture and processing system. Sensors capture images of blood samples and the system uses computational algorithms to analyze sample integrity, substituting human mechanical inspection with automated optical and computational systems.
2Reliability
If manual visual inspection is performed on all samples, then sample quality control improves, but productivity decreases
Solution Approach 1:
Instead of inspecting every sample manually, the system applies automated inspection to all samples and only routes those flagged as potentially defective for manual review. This partial manual action combined with comprehensive automated screening maintains quality control while preserving productivity.
Solution Approach 2:
The system autonomously identifies and routes defective samples without requiring manual inspection of every sample. The automated image processing system performs the quality control function itself, freeing personnel from routine inspection tasks while maintaining high throughput.
3Productivity
If defective samples are processed without detection, then productivity is maintained, but measurement precision deteriorates
Solution Approach 1:
The system performs preliminary inspection of samples before they enter the main processing workflow. By capturing images and analyzing sample integrity upfront, the system identifies defective samples early and routes them separately, ensuring that only quality samples proceed to analysis and preventing inaccurate results.
Solution Approach 2:
The image processing system provides feedback about sample quality to the routing mechanism. When defects are detected through image analysis, the system immediately redirects those samples to appropriate handling procedures, creating a closed-loop quality control system that maintains result accuracy while preserving continuous processing.
Data Source
AI summary
Systems, methods, devices, and apparatus for detecting sample defects in blood samples processed in automated processing systems are described herein. One aspect describes an automated blood sample processing apparatus having a pre-analytic specimen integrity monitoring device. Another aspect describes devices, systems, and methods for identifying blood components and properties in blood samples. Further aspects relate to systems and methods for setting reference ranges for sample defects and interference in blood samples. Additionally, devices, systems, and methods for identifying defective samples are described.