Breath Sensor Array for Parkinson's Disease Diagnosis
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Solution Overview
Problem
Current methods lack a simple and reliable technique for early diagnosis and monitoring of Parkinson's disease, and there is an unmet need for effective breath biomarker-based management of the disease progression.
Innovation Solution
A system utilizing a sensor array comprising single-walled carbon nanotubes coated with cyclodextrin or derivatives and metal nanoparticles with organic coatings, in conjunction with a learning and pattern recognition algorithm, to analyze volatile biomarkers in breath samples for diagnosing, monitoring, and staging Parkinson's disease.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If blood sampling and metabolomic profiling are used for PD diagnosis, then diagnostic accuracy is improved, but the procedure becomes invasive and time-consuming
Solution Approach 1:
The invention extracts and detects volatile organic compounds (VOCs) from breath samples, which are easily obtainable non-invasive specimens. By focusing on breath-derived biomarkers rather than requiring blood or urine collection, the system achieves early PD detection while eliminating the invasiveness and complex laboratory processing associated with traditional metabolomic profiling
Solution Approach 2:
The invention replaces complex mechanical and chemical laboratory procedures (blood sampling, agitation, incubation, metabolomic profiling) with an electronic sensor array system that directly detects VOC patterns in breath. This substitution of mechanical/biological processes with electronic detection achieves comparable or superior diagnostic accuracy while dramatically simplifying the procedure
2Ease of operation
If clinical symptom-based diagnosis is used for PD, then the method is simple and accessible, but diagnostic reliability decreases outside specialist settings
Solution Approach 1:
The breath analysis system is designed to be操作简单 and self-contained, requiring minimal specialist training. The sensor array automatically detects VOC patterns and provides diagnostic information, enabling reliable PD detection even in non-specialist settings without requiring complex interpretation skills
Solution Approach 2:
The invention shifts the diagnostic parameter from subjective clinical symptom assessment to objective quantitative measurement of VOC concentrations and patterns in breath. This parameter change from qualitative clinical evaluation to quantitative chemical analysis maintains simplicity while dramatically improving diagnostic reliability and consistency across different settings
3Ease of operation
If breath analysis with sensor arrays is used for PD diagnosis, then the procedure is fast and non-invasive, but sensitivity and selectivity are initially limited
Solution Approach 1:
The invention employs a composite sensor array system combining multiple sensor types (metal oxide semiconductors, conducting polymers, carbon nanotubes) with different selectivity profiles. Each sensor material responds differently to various VOCs, and the combined array provides enhanced overall sensitivity and selectivity through pattern recognition algorithms that analyze the composite response profile
Solution Approach 2:
The invention transitions from detecting single VOC markers to analyzing multidimensional VOC pattern profiles. By measuring concentrations of multiple different VOCs simultaneously and analyzing their interrelationships, the system achieves superior sensitivity and selectivity, effectively adding dimensional complexity to the detection approach while maintaining operational simplicity
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 system provides enhanced sensitivity and selectivity for diagnosing and monitoring Parkinson's disease, enabling fast and reliable differential diagnosis and comprehensive disease management, including monitoring of disease progression.
Implementation Method 1
a sensor array comprising at least one sensor comprising a random network of carbon nanotubes coated with cyclodextrin or a derivative thereof and/or at least one sensor comprising metal nanoparticles capped with an organic coating
Data Source
AI summary
The present invention provides a system and method for diagnosing, monitoring, prognosing or staging Parkinson's disease using at least one sensor comprising carbon nanotubes coated with cyclodextrin or derivatives thereof or metal nanoparticles coated with various organic coatings in conjunction with a learning and pattern recognition algorithm.