Camera-Based Asthma Detection Using Respiratory Effort and Airflow Analysis
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Solution Overview
Problem
Current methods for predicting and managing asthma attacks are unreliable and often require expensive pulmonary examinations or access to specialized therapists, with a need for non-pharmacological approaches to improve asthma control and prevent serious attacks.
Innovation Solution
A device and system utilizing a combination of light and thermal sensors to monitor respiratory effort and airflow, along with audio input for stress analysis, to predict and detect asthma attacks, providing biofeedback-assisted personalized treatment and self-management tools.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If pulmonary examinations are used to detect impending asthma attacks, then detection reliability is improved, but cost increases
Solution Approach 1:
The patent replaces expensive mechanical pulmonary examination equipment with optical sensors (cameras) that capture respiratory movements. The system uses image processing algorithms to extract respiratory rate and effort information from video footage, substituting complex medical imaging machinery with accessible visual detection methods that maintain diagnostic reliability while dramatically reducing cost.
Solution Approach 2:
The system creates a visual copy of respiratory movements through camera imaging, then analyzes this optical replica to detect asthma attack patterns. By working with captured images rather than requiring direct physical examination equipment, the system achieves reliable detection at lower cost through information copying and computational analysis.
2Reliability
If specialized therapists are accessed for breathing control exercises, then asthma management effectiveness is improved, but accessibility deteriorates
Solution Approach 1:
The system enables patients to perform self-monitoring of their respiratory patterns using the camera-based device at home. The automated analysis provides immediate feedback on respiratory rate and effort, allowing patients to self-manage their asthma through breathing exercises guided by objective data, eliminating the need for specialized therapist intervention while maintaining management effectiveness and improving accessibility.
Solution Approach 2:
The system implements continuous feedback loops where respiratory parameters are monitored in real-time, analyzed by algorithms, and used to provide immediate guidance on breathing control. This automated feedback mechanism replaces manual therapist guidance, making effective asthma management accessible to anyone with the device without requiring specialized personnel.
3Measurement precision
If peak flow meters are used regularly to predict asthma attacks, then prediction accuracy is improved, but device complexity and user burden increase
Solution Approach 1:
The patent replaces manual peak flow meter usage with automated optical sensing. The camera-based system continuously captures respiratory movements and automatically extracts prediction-relevant parameters without requiring user intervention. This eliminates the need for patients to manually operate devices while maintaining or improving prediction accuracy through continuous automated monitoring.
Solution Approach 2:
The system performs self-monitoring by automatically capturing and analyzing respiratory patterns without user action. The device autonomously tracks respiratory rate and effort, processes the data through algorithms, and generates predictions, completely removing the user burden associated with manual peak flow meter operation while sustaining high measurement precision.
4Reliability
If multiple sensor types are combined for comprehensive monitoring, then detection reliability is improved, but device complexity increases
Solution Approach 1:
The patent merges multiple sensing capabilities (visible light imaging, infrared thermal imaging, audio recording) into a single integrated system. The camera unit simultaneously captures visual respiratory movements and thermal patterns, while the microphone records audio signals. This consolidation achieves comprehensive monitoring for improved reliability without proportionally increasing device complexity, as all sensors are integrated into one unified platform with centralized processing.
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 reliable, non-invasive, and cost-effective detection and management of asthma attacks, allowing for early prediction and prevention of severe episodes through self-monitoring and personalized treatment plans.
Implementation Method 1
a thermal sensor input for obtaining thermal sensor data of a scene including a subject while breathing, said thermal sensor data comprising thermal images in the longwave infrared spectrum
Implementation Method 2
a light sensor input for obtaining light sensor data of the scene, said light sensor data comprising images in the visible and/or infrared light spectrum
Data Source
AI summary
The present invention relates to a device (10, 10a, 10b), system (1, 2, 3) and method for detection of an asthma attack or asthma of a subject. For this purpose, the device comprises a light sensor input (11), e.g. a 2D camera, for obtaining light sensor data of the scene and a thermal sensor input (12), e.g. a thermal camera, for obtaining thermal sensor data of a scene including a subject while breathing. An analysis unit (13) obtains these data and derives respiratory effort information indicating respiratory efforts of the subject from the obtained light sensor data and/or the obtained thermal sensor data and derives airflow information indicating airflow during respiration of the subject from the obtained thermal sensor data. Further, the analysis unit (13) predicts or detects an asthma attack or asthma based on analysis of the respiratory effort information and the airflow information, said analysis evaluating deviations from predetermined or healthy correlations between respiratory efforts and airflow.