Acoustic Pulmonary Monitoring via Phase-Shifted Signal Extraction
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Solution Overview
Problem
Conventional pulmonary health monitoring techniques face challenges in accurately diagnosing obstructive airway diseases, particularly in non-cooperative patients and those with unstable conditions, and are associated with high costs and noise rejection.
Innovation Solution
A system utilizing a blow device to generate a phase-shifted signal from breathe signals, which is processed to extract physiological features using a Locally Weighted Learning (LWL) based machine learning technique for pulmonary health analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional spirometry test is used for pulmonary disease diagnosis, then diagnosis can be obtained, but user cooperation is required which limits applicability to certain patient groups
Solution Approach 1:
The patent replaces the mechanical spirometry system requiring voluntary user action with an acoustic measurement system using microphones and signal processing to capture passive respiratory sounds, enabling monitoring of non-cooperative patients
Solution Approach 2:
The patent introduces acoustic sensors and signal processing algorithms as intermediaries to indirectly measure respiratory parameters without requiring direct user participation in the measurement process
2Measurement precision
If conventional spirometry test is used, then pulmonary function can be assessed, but high costs and noise rejection challenges are associated
Solution Approach 1:
The patent replaces expensive conventional spirometry equipment with low-cost acoustic sensors and computational algorithms, reducing hardware costs while maintaining diagnostic accuracy through advanced signal processing
Solution Approach 2:
The patent creates a virtual copy of spirometry functionality through acoustic measurements and machine learning models, achieving similar diagnostic capabilities without requiring expensive physical spirometry devices
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 accurate and cost-effective pulmonary health monitoring, capable of assessing pulmonary health without requiring voluntary effort from patients, reducing errors and operational costs.
Implementation Method 1
generate a phase shifted signal corresponding to a first signal
Data Source
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AI summary
A pulmonary health monitoring system aims at assessing pulmonary health of subjects. Conventional techniques used for pulmonary health monitoring are not convenient to the subjects and needs considerable cooperation from the subjects. But, there is a challenge in utilizing the conventional devices to the subjects not capable of providing considerable cooperation. The present disclosure includes a blow device applicable to all kind of subjects and doesn't need cooperation from the subjects. Further, in the present disclosure, the blow device generates a phase shifted signal corresponding to a breathe signal and the phase shifted signal is further processed to extract a set of physiological features. Further, pulmonary health of a subject is analyzed by processing the set of physiological features based on a ridge regression based machine learning technique.