Portable Respiratory Assessment via Sensor Biomarker Extraction
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Solution Overview
Problem
Existing methods for assessing respiratory conditions in humans are often expensive, cumbersome, and require clinical settings, making them inaccessible when needed most, especially during public health crises like the COVID-19 pandemic, and can exacerbate lung conditions due to their invasive nature or incorrect usage.
Innovation Solution
A portable device with embedded sensors and signal processing capabilities captures and analyzes biomarkers from lung activity, allowing for remote respiratory assessments, synchronizing signals from multiple devices to accurately determine lung conditions and providing notifications for further testing or medical attention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing respiratory assessment methods are used, then measurement precision is improved, but device complexity and accessibility worsen
Solution Approach 1:
The patent replaces complex mechanical respiratory assessment equipment with mobile electronic devices containing sensors that detect body movements during respiratory cycles. The system uses signal processing to extract biomarkers from accelerometer and gyroscope data, substituting sophisticated mechanical measurement systems with electronic sensing and computational analysis.
Solution Approach 2:
The system enables individuals to perform self-assessment of their respiratory conditions using their own mobile devices without requiring clinical settings or professional operators. The mobile device automatically captures sensor data, processes signals, extracts biomarkers, and provides respiratory condition assessment results, making the service self-sufficient and accessible.
2Measurement precision
If invasive assessment methods are used, then measurement precision is improved, but object-affected harmful factors worsen
Solution Approach 1:
The patent replaces invasive mechanical assessment procedures with non-invasive sensor-based detection using mobile devices. The system measures respiratory conditions by detecting external body movements and vibrations during respiratory cycles, eliminating the need for invasive lung function tests that could trigger bronchospasms or worsen existing conditions.
3Measurement precision
If clinical setting assessments are used, then measurement precision is improved, but ease of operation worsens
Solution Approach 1:
The patent utilizes mobile devices that serve multiple functions - they are not only communication tools but also respiratory assessment instruments. The same accelerometer and gyroscope sensors used for device orientation and motion tracking are repurposed to detect respiratory-related body movements, making the device universal and eliminating the need for specialized clinical equipment.
Solution Approach 2:
The system enables individuals to perform self-assessment of their respiratory conditions using their own mobile devices without requiring clinical settings or professional operators. The mobile device automatically captures sensor data, processes signals, extracts biomarkers, and provides respiratory condition assessment results, making the service self-sufficient and accessible.
4Measurement precision
If multiple sensor signals are captured, then measurement precision is improved, but data processing complexity worsens
Solution Approach 1:
The patent extracts specific respiratory-related biomarkers from complex multi-axis sensor signals by identifying and isolating movement patterns along preferred measurement axes. The system filters out irrelevant data and focuses on extracting meaningful respiratory indicators such as breathing rate, tidal volume, and respiratory rhythm from the raw accelerometer and gyroscope data.
Solution Approach 2:
The system transforms raw sensor data into meaningful respiratory biomarkers by changing the parameters of analysis - converting acceleration and angular velocity measurements into respiratory rate, tidal volume, and other clinically relevant parameters through signal processing and biomarker extraction algorithms.
Data Source
AI summary
Adaptive respiratory condition assessment can include capturing signals generated by sensors of a portable device positioned to sense a user's body. The sensors can generate the signals in response to sensor-detected movements of the user's body measured along multiple axes and corresponding to lung activity in the user's body during respiratory cycles. A preferred axis of measurement can be selected using signal processing performed by a signal processor embedded in the portable device. Waveforms generated from signals corresponding to signals generated in response to movements of the user's body measured along the preferred axis can be filtered for extracting biomarkers from the waveforms using the signal processor. The one or more biomarkers extracted correspond to the lung activity. Based on the biomarkers, a respiratory condition of the user can be determined. A notification based on the respiratory condition as determined can be generated and conveyed with the portable device.