In Situ Pathogen Detection Using Hyperspectral and Plenoptic Imaging
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Solution Overview
Problem
Conventional methods for detecting pathogens and diseased cells are slow, invasive, and often produce false positives, as they require sample collection, culturing, and laboratory testing, which can take weeks and do not differentiate between live and dead cells, and may not accurately identify pathogens present on surfaces.
Innovation Solution
A system that uses a smartphone or similar device equipped with a scene-capture system, biologic detection system, environmental sensor system, and AI/ML/DL technology to analyze images of surfaces in real-time, identifying pathogens and diseased cells in situ without sample collection, using hyperspectral and plenoptic imaging, and nanophotonics to enhance detection accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional sample collection and laboratory testing methods are used, then pathogen detection can be performed, but the detection process is slow and takes weeks to complete
Solution Approach 1:
The patent replaces mechanical laboratory testing systems with optical imaging systems (hyperspectral and plenoptic cameras) that capture and analyze light interactions with biological cells in situ, eliminating the need for physical sample collection, transport, and laboratory culturing processes that traditionally took weeks
Solution Approach 2:
The system performs preliminary detection actions directly at the surface where pathogens are present, capturing images and analyzing cellular characteristics before any sample collection or laboratory processing occurs, enabling immediate identification of pathogens without waiting for laboratory results
2Measurement precision
If conventional culturing methods are used, then pathogen identification can be achieved, but the process is invasive and requires sample collection
Solution Approach 1:
The patent substitutes invasive mechanical sample collection and laboratory culturing with non-invasive optical imaging that captures hyperspectral and plenoptic data from surfaces, allowing pathogen identification through image analysis without physical contact or sample removal
Solution Approach 2:
The system enables surfaces to effectively self-report their contamination status by capturing optical signatures of biological cells directly in situ, eliminating the need for external sample collection and laboratory analysis services
3Reliability
If conventional laboratory testing is used, then pathogen detection can be performed, but false positives occur due to inability to differentiate live and dead cells
Solution Approach 1:
The patent applies different optical analysis methods to different characteristics of detected cells - using viability stains and metabolic activity assessment for live/dead differentiation, combined with morphological analysis and spectral signature recognition, allowing the system to evaluate multiple quality aspects of each detected cell locally and independently
4Reliability
If conventional detection methods are used, then pathogen presence can be determined, but the complexity of sample collection and laboratory testing increases device complexity
Solution Approach 1:
The patent merges multiple detection functions (hyperspectral imaging, plenoptic imaging, viability assessment, and pathogen identification) into a single integrated portable device that performs all analyses in situ, eliminating the need for separate sample collection tools, transport mechanisms, and laboratory equipment
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 rapid, accurate detection and identification of pathogens and diseased cells directly on surfaces, reducing the risk of false positives and eliminating the need for laboratory testing, allowing for immediate action to prevent disease spread and improving surface hygiene monitoring.
Implementation Method 1
using hyperspectral and plenoptic imaging, and nanophotonics to enhance detection accuracy
Implementation Method 2
using hyperspectral and plenoptic imaging, and nanophotonics to enhance detection accuracy
Implementation Method 3
using hyperspectral and plenoptic imaging, and nanophotonics to enhance detection accuracy
Data Source
AI summary
Techniques related to the detection or identification of biological cells or substances.


