Optical Assay Homogeneity Imaging for Inhomogeneous Sensing Surfaces
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Solution Overview
Problem
Existing assays are impaired by inhomogeneities that affect the accuracy of optical measurements, particularly in biosensors, leading to incorrect results due to non-uniform binding spots, contamination, or optical path disturbances.
Innovation Solution
A method and sensor device that generate a homogeneity-image of the sensing surface, determine a homogeneity-indicator, and evaluate optical measurements based on this indicator to detect and correct for inhomogeneities, such as non-uniform binding spots, air bubbles, or optical path defects, by rejecting or correcting measurements accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If optical measurements are performed on the sensing surface, then assay results are obtained, but measurement accuracy deteriorates due to inhomogeneities such as non-uniform binding spots, air bubbles, or optical path defects
Solution Approach 1:
The patent applies preliminary action by capturing a homogeneity image of the sensing surface before performing the actual optical assay measurements. This preliminary imaging step identifies inhomogeneities (such as non-uniform binding spots, air bubbles, or optical path defects) in advance, allowing the system to exclude affected regions from subsequent measurements. By detecting and flagging problematic areas beforehand, the assay can proceed with only the homogeneous regions, thereby maintaining measurement accuracy while avoiding the time-consuming need to repeat entire assays.
2Reliability
If statistical processing is applied to sub-areas of spots to handle nonuniformities, then measurement robustness improves, but measurement precision deteriorates due to averaging effects that mask local inhomogeneities
Solution Approach 1:
The patent applies segmentation by dividing the sensing surface into multiple sub-areas or regions of interest (ROIs) and evaluating the homogeneity of each segment independently through homogeneity images. Rather than statistically processing entire spots as single units, the system segments the surface and assesses each segment's homogeneity separately. This allows precise identification of locally inhomogeneous regions, enabling selective exclusion of only the affected segments while retaining data from homogeneous segments, thereby maintaining both reliability and precision.
3Measurement precision
If homogeneity evaluation is performed on the sensing surface, then measurement accuracy improves, but assay time increases due to additional imaging and evaluation steps
Solution Approach 1:
The patent applies merging by combining the homogeneity evaluation function with the existing optical assay measurement system. The homogeneity image capture and evaluation are integrated into the same optical path and timing structure as the assay measurements themselves. By utilizing the existing imaging infrastructure and synchronizing homogeneity checks with assay readouts, the system performs both functions simultaneously or in tightly coupled sequence, minimizing additional time overhead while maintaining measurement accuracy through comprehensive homogeneity assessment.
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 of optical measurements by identifying and addressing inhomogeneities, ensuring valid and reliable assay results by excluding or compensating for inhomogeneous regions.
Implementation Method 1
An optical sensor unit for making optical measurements at the sensing surface, wherein the sensor unit comprises an image sensor by which images of the sensing surface can be generated
Data Source
AI summary
The invention relates to a method and a sensor device (100) for evaluating an assay with a sample. During the assay, optical measurements are made at a sensing surface (112), and at least one “homogeneity-image” of the sensing surface (112) is generated. From this image, an “homogeneity-indicator” is determined for at least one region of interest, and the optical measurements are then evaluated in dependence on said indicator. The homogeneity-indicator may for example be a binary value which indicates if an inhomogeneity was detected or not. If an inhomogeneity was detected, all optical measurements may be rejected, only measurements for the involved region of interest may be rejected, or measurements for a selected sub-area of the involved region of interest (ROI) may be rejected.


