Mobile Sleep Apnea Monitoring With Audio and Motion Sensing
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Solution Overview
Problem
Conventional methods for diagnosing obstructive sleep apnea (OSA) are unreliable, costly, and cumbersome, and existing smartphone-based solutions fail to provide a reliable and cost-effective monitoring of sleeping disorders and quality.
Innovation Solution
A method using a mobile device with a microphone and accelerometer to acquire audio and motion data, identifying silence events, classifying them as apneas or hypopneas, and associating positional information to monitor sleeping disorders, and using a pulse oximeter for oxygen saturation levels to enhance accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional polysomnography is used to accurately diagnose sleep disorders, then diagnostic precision is improved, but device complexity and cost increase significantly
Solution Approach 1:
The patent extracts and isolates the most critical measurement functions from the complex conventional polysomnography system. It focuses specifically on measuring respiratory effort, airflow, and oxygen saturation using simplified sensors, separating these essential functions from other comprehensive but non-essential monitoring parameters used in traditional sleep studies.
Solution Approach 2:
The patent uses consumer-grade wearable devices that replicate essential medical monitoring functions. These devices copy the core measurement capabilities of medical-grade equipment (respiratory monitoring, oxygen saturation sensing) but implement them using commercially available, less complex technology platforms.
2Measurement precision
If comprehensive sleep studies are conducted in sleep centers, then diagnostic accuracy is improved, but loss of time and convenience deteriorate
Solution Approach 1:
The patent enables patients to perform the sleep study in their own environment before formal medical intervention is needed. By providing portable monitoring devices that can be used at home, the system allows preliminary diagnosis and screening to occur in advance, reducing the need for time-consuming trips to sleep centers for initial evaluations.
Solution Approach 2:
The system allows patients to independently conduct their own sleep monitoring using portable devices. Patients can attach the monitoring equipment themselves, conduct the study in their own bedroom, and transfer data automatically, eliminating the need for technologists to set up and monitor studies in centralized sleep centers.
3Ease of operation
If consumer-grade wearables are used for sleep monitoring, then ease of operation is improved, but measurement precision deteriorates
Solution Approach 1:
The patent adapts multi-functional consumer wearable technology for specific medical monitoring purposes. These devices are designed to perform multiple functions (fitness tracking, heart rate monitoring, sleep analysis) but are configured and calibrated to provide medically relevant respiratory and oxygen saturation measurements, bridging the gap between consumer convenience and medical precision.
Solution Approach 2:
The system changes the measurement parameters and calibration standards of consumer devices to match medical requirements. By adjusting sampling rates, sensor sensitivity, and data processing algorithms, the patent transforms consumer-grade measurements into clinically relevant data without requiring complete redesign of the hardware.
Data Source
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AI summary
Monitoring a sleeping disorder in a subject person using a mobile device, such as smartphones or other wearable devices, and comprising: collocating the mobile device with the subject person; acquiring audio signals indicative of breathing of the subject person by means of a microphone of the mobile device; acquiring accelerometer signals including position, angular and movement information of the subject person by means of an accelerometer of the mobile device; measuring thoracic movement related to respiration and sleep-disordered breathing by means of the accelerometer of the mobile device; identifying a plurality of silence events by means of the audio signal; classifying the silence events into apnea or hypopnea; classifying apnea into plurality of apnea types by means of the thoracic movement recorded with the accelerometer sensor; and associating to a classified silence event the respective angular information by combining the audio and accelerometer signals.