Non-contact Microphone Breathing Analysis via Expiratory Sound Derivation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for monitoring and modifying biorhythmic activity, such as breathing patterns, face challenges in accurately measuring inspiration time and filtering background noise, especially in noisy environments and with standard non-contact microphones.
Innovation Solution
A method using a standard non-contact microphone to measure breathing parameters, applying algorithms to derive unmeasurable parameters like inspiration time, and calibrating signal detection parameters by guiding users through breathing phases to filter background noise effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a standard non-contact microphone is used to monitor breathing patterns, then the device complexity is reduced and ease of operation is improved, but the measurement precision deteriorates due to inability to directly measure inspiration time and susceptibility to background noise
Solution Approach 1:
The patent uses expiratory sounds as an intermediary measurable parameter to indirectly determine inspiration time. Since inspiration sounds are too quiet to detect with standard microphones, the system measures the louder expiratory phase and uses algorithmic derivation to calculate the unmeasurable inspiration duration, thus resolving the measurement precision issue while maintaining ease of operation
Solution Approach 2:
The patent replaces direct acoustic measurement of inspiration with an algorithmic computation system. Instead of relying on the microphone to directly capture and measure inspiration sounds, the system substitutes mechanical/acoustic detection with electronic signal processing and mathematical algorithms that derive inspiration time from expiratory phase measurements
2Measurement precision
If signal detection parameters are calibrated by guiding users through breathing phases, then the measurement precision is improved, but the productivity decreases due to additional calibration time required
Solution Approach 1:
The patent implements preliminary calibration procedures where users are guided through specific breathing phases before actual monitoring begins. This preliminary action establishes accurate signal detection parameters and noise filters in advance, ensuring high measurement precision during subsequent use while the initial time investment is made only once per user or session
3Measurement precision
If algorithms are applied to derive unmeasurable parameters like inspiration time, then the measurement precision is improved, but the device complexity increases
Solution Approach 1:
The patent replaces complex hardware modifications with software-based algorithmic solutions. Instead of adding specialized sensors or complex acoustic chambers to directly measure inspiration, the system uses computational algorithms running on standard microprocessors to derive inspiration time from readily available expiratory phase data, thus improving precision without significantly increasing device complexity
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 accurate determination of breathing patterns, including inspiration time, even in noisy conditions, improving biorhythmic signal detection and allowing for breathing pattern modification techniques to be effectively applied.
Implementation Method 1
using a non-contact microphone, detecting airflow sounds of the respiration, and converting the sounds into a signal
Data Source
AI summary
A method is provided for analyzing respiration of a subject (20). Using a non-contact microphone (22), a raw signal indicative of airflow sounds of the respiration is generated. The raw signal is analyzed to determine a first set of one or more parameters of the respiration. An algorithm is applied to the first set of parameters to derive a second set of one or more estimated parameters of the respiration that are not generally directly measurable in the raw signal. Other embodiments are also described.