Microorganism Identification via Vibrational Spectrum Analysis
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Solution Overview
Problem
Existing methods for identifying microorganisms using vibrational spectroscopy face challenges such as signal saturation and distortion due to sample thickness and morphology, limited database coverage of microorganism species, and increased analysis time with larger databases.
Innovation Solution
A method utilizing multivariate analysis and pre-calculated models to compare the vibrational spectrum of an unknown sample with reference spectra, allowing for rapid identification of microorganisms across various categories and strains, without requiring high computing power or continuous internet connection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If transmission or reflection acquisition modes are used for spectral analysis, then the analysis can be performed on whole samples, but the signal becomes saturated or distorted due to sample thickness and morphology
Solution Approach 1:
The patent segments the sample analysis by using multiple detectors at different positions (front and rear sides of the sample) to capture spectral information from different regions. This allows the system to analyze whole samples while avoiding signal saturation and distortion by selecting optimal measurement positions and combining information from multiple segments.
Solution Approach 2:
The patent introduces a spatial dimension by using multiple detectors positioned at different locations relative to the sample. Instead of a single-point measurement that suffers from thickness-related saturation, the system uses distributed detection across the sample surface, effectively adding a spatial dimension to the spectral analysis.
2Measurement precision
If imaging approaches with multipixel detectors are used, then the resolution of individual spectra is improved, but the signal-to-noise ratio decreases per pixel
Solution Approach 1:
The patent merges the advantages of high resolution and high signal-to-noise ratio by combining multiple detectors that each capture spectral information from different spatial positions. The system integrates signals from multiple detectors, effectively pooling their signal strengths while maintaining the resolution benefits of individual pixel detection.
Solution Approach 2:
The patent creates a multi-functional detection system where each detector serves multiple purposes: providing spectral resolution, contributing to signal accumulation, and enabling spatial mapping. The system universally applies spectral analysis across the entire sample surface while maintaining both resolution and signal quality.
3Adaptability or versatility
If larger databases of reference spectra are used, then the coverage of microorganism species is improved, but the analysis time increases
Solution Approach 1:
The patent performs preliminary actions by pre-processing and organizing reference spectra into optimized data structures before actual analysis. The system pre-ranges and categorizes spectral data, creating lookup tables and reference frameworks that enable rapid comparison during actual microorganism identification, thus reducing real-time analysis time despite having comprehensive databases.
Solution Approach 2:
The patent uses spectral copying and pattern matching techniques where reference spectra are stored as templates and compared against unknown samples through efficient algorithms. The system creates spectral fingerprints and uses rapid pattern recognition to match unknowns against large reference databases, significantly reducing search time compared to traditional methods.
4Measurement precision
If multiple acquisitions are performed to remove water components, then the spectral quality is improved, but the analysis time and procedural complexity increase
Solution Approach 1:
The patent extracts and removes water components from spectral data through sophisticated signal processing techniques. Instead of requiring multiple physical acquisitions, the system mathematically separates water absorption bands from microbial spectral features using algorithms that identify and subtract water-related signals, thereby improving spectral quality without increasing procedural steps.
Solution Approach 2:
The patent replaces mechanical multiple-acquisition procedures with computational signal processing. Instead of physically repeating measurements to eliminate water interference, the system uses digital signal processing algorithms to remove water components from single acquisitions, substituting mechanical repetition with computational intelligence.
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
The method enables accurate and rapid identification of microorganisms, even with large databases, by reducing computing power requirements and eliminating the need for continuous internet connectivity, while improving the accuracy and precision of microorganism classification.
Implementation Method 1
Fourier transform infrared spectroscopy (FTIR) is a non-destructive analysis technique, which allows to obtain information on the chemical composition of a sample analyzed
Implementation Method 2
the ability of the FTIR technique to identify and classify unknown microorganisms was shown... different species, subspecies or sub-classifications of microorganisms are characterized by a precise biochemical composition... which is reflected in a distinct vibrational spectrum
Data Source
AI summary
A method of identifying microorganisms in a sample by evaluating the vibrational profile.