Saliva Spectroscopic Analysis for Cognitive Disease Detection
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Solution Overview
Problem
Current diagnostic methods for Alzheimer's disease and mild cognitive impairment are invasive, expensive, and lack specificity, with cerebrospinal fluid analysis being invasive and imaging tests being costly and only useful for ruling out other diseases.
Innovation Solution
A method involving saliva sample spectroscopic analysis using Raman or vibrational spectroscopy to generate a sample spectroscopic signature, which is then analyzed using a predetermined statistical model to correlate with cognitive categories, enabling non-invasive and cost-effective detection of cognitive diseases.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If cerebrospinal fluid analysis is used for diagnosis, then diagnostic accuracy is improved, but the procedure becomes invasive and complex
Solution Approach 1:
The patent uses saliva as an intermediary medium to indirectly detect cognitive disease markers. Instead of directly analyzing cerebrospinal fluid, the method analyzes saliva samples that contain reflective information about cognitive health through spectroscopic detection of molecular vibrations, thereby avoiding invasive procedures while maintaining diagnostic capability
Solution Approach 2:
The patent replaces the mechanical invasive procedure of lumbar puncture with a non-invasive spectroscopic analysis method. Using Raman or vibrational spectroscopy on saliva samples substitutes for the mechanical cerebrospinal fluid collection and analysis process, eliminating the need for invasive procedures
2Reliability
If imaging tests are used for diagnosis, then disease elimination is achieved, but cost increases and specificity decreases
Solution Approach 1:
The patent replaces expensive imaging tests with spectroscopic analysis of saliva samples. By detecting molecular vibrations and spectral signatures in saliva, the method provides specific diagnostic information about cognitive disease markers without relying on costly imaging equipment that only serves to rule out other conditions
3Reliability
If conventional diagnostic methods are used, then comprehensive examination is achieved, but time consumption increases
Solution Approach 1:
The patent extracts and focuses on specific diagnostic markers through spectroscopic analysis of saliva samples. By targeting specific molecular vibrations and spectral signatures related to cognitive disease markers, the method isolates key diagnostic information without requiring the lengthy comprehensive examination of multiple test types
Solution Approach 2:
The patent performs preliminary spectroscopic analysis on saliva samples that can be collected easily and non-invasively. This preliminary testing approach allows for early detection and classification of cognitive diseases before more complex and time-consuming conventional diagnostic procedures are fully required
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
This approach allows for early, accurate, and less invasive detection of cognitive diseases, providing a quicker diagnosis compared to conventional methods and reducing the need for invasive procedures.
Implementation Method 1
subjecting at least a portion of the saliva sample to a spectroscopic analysis to produce a sample spectroscopic signature
Implementation Method 2
subjecting at least a portion of the saliva sample to a spectroscopic analysis to produce a sample spectroscopic signature
Data Source
AI summary
Systems and methods for detecting a cognitive diseases and/or impairments in humans are disclosed. The method may include providing a saliva sample from a human subject, and subjecting at least a portion of the saliva sample to a spectroscopic analysis to produce a sample spectroscopic signature. The method may also include analyzing the produced sample spectroscopic signature using a predetermined statistical model. The predetermined statistical model may be based on spectroscopic signatures for a plurality modeling samples, and the spectroscopic signatures for each of the plurality of modeling samples may be associated with one of a plurality of predetermined cognitive categories. Additionally, the method may include correlating the produced sample spectroscopic signature with one of the plurality of predetermined cognitive categories based on the spectroscopic signatures for each of the plurality of modeling samples of the predetermined statistical model.


