Near-field imaging sensor for microbead classification
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Solution Overview
Problem
Current methods for classifying microbeads in near-field imaging are limited in distinguishing a large number of classes based on their optical properties, such as absorption spectra, sizes, and shapes, which restricts the accuracy and complexity of analyzing samples containing multiple antigens or biomarkers.
Innovation Solution
A near-field imaging sensor system that utilizes a two-dimensional array of photosensitive elements to classify microbeads based on their absorption spectra, sizes, and shapes by capturing images under different source light spectra, allowing for the discrimination of a large number of classes through combinatorial relationships of these characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional imaging methods are used to classify microbeads, then the system is simple to operate, but the number of distinguishable classes is limited
Solution Approach 1:
The patent transitions from conventional wide-field imaging to near-field imaging, adding a new dimensional approach to light-matter interaction. By placing the sensor surface in direct contact with or extremely close to the microbeads, the system accesses evanescent fields and near-field optical effects that provide additional discriminative dimensions for classification, enabling thousands of distinguishable classes beyond conventional methods
Solution Approach 2:
The imaging sensor is divided into a two-dimensional array of photosensitive elements, with each element independently detecting optical properties at its specific location. This segmentation allows parallel detection of multiple microbead characteristics across the sample area, significantly increasing the number of distinguishable classes while maintaining system manageability
2Measurement precision
If multiple characteristics (absorption spectra, sizes, shapes) are used to classify microbeads, then classification accuracy improves, but the difficulty of detecting and measuring increases
Solution Approach 1:
The patent combines multiple detection capabilities (absorption spectra measurement, size detection, shape analysis) into a single near-field imaging sensor platform. By measuring all these characteristics simultaneously through one integrated system rather than separate instruments, the patent reduces operational complexity while maintaining high classification accuracy across thousands of microbead classes
Solution Approach 2:
The system utilizes changes in optical parameters (absorption spectra) under different illumination conditions to differentiate microbead characteristics. By varying the source light spectra and measuring the resulting near-field optical responses, the system extracts multiple characteristics (size, shape, composition) from parameter variations, improving measurement precision without proportionally increasing system complexity
3Adaptability or versatility
If near-field imaging is used to classify thousands of microbead classes, then the number of distinguishable classes increases, but the device complexity increases
Solution Approach 1:
The near-field imaging sensor utilizes the natural optical phenomena (evanescent fields, near-field light-matter interaction) that occur when the sensor surface is placed in direct contact with or extremely close to the microbeads. The system leverages these self-occurring physical effects without requiring complex external manipulation or additional components, enabling high-dimensional classification while keeping the device relatively simple
Solution Approach 2:
The near-field imaging sensor serves multiple functions simultaneously: it detects absorption spectra, measures microbead sizes, analyzes shapes, and classifies thousands of different microbead classes all through a single imaging operation. This multi-functionality reduces the need for multiple separate instruments and procedures, making the increased classification capability more manageable
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 the classification and location of thousands of microbeads, thereby determining the presence and concentration of various antigens or biomarkers with high accuracy, enhancing applications in cytometry, diagnostics, and multiplex assays.
Implementation Method 1
different absorption spectra, spatial arrangements of colorants in the microbeads that impart the different absorption spectra
Data Source
AI summary
Among other things, an imaging sensor includes a two-dimensional array of photosensitive elements and a surface to receive a sample within a near-field distance of the photosensitive elements. Electronics classify microbeads in the sample as belonging to different classes based on the effects of different absorption spectra of the different classes of microbeads on light received at the surface. In some examples, the number of different distinguishable classes of microbeads can be very large based on combinations of the effects on light received at the surface of the different absorption spectra together, spatial arrangements of colorants in the microbeads that impart the different absorption spectra, different sizes of microbeads, and different shapes of microbeads, among other things.