Breath Sound Analysis for Non-Invasive Sleep Detection
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Solution Overview
Problem
Current methods for sleep detection in sleep apnea studies are invasive, cumbersome, and require multiple sensors, making them uncomfortable and prone to errors due to displacement of electrodes, which affects the accuracy of sleep apnea severity assessment.
Innovation Solution
A system and method for automatically characterizing digitized breath sounds to determine sleep status by analyzing breathing cycles, inter-breath intervals, and upper airway relaxation, using a wearable mask with a microphone and accelerometer to record breath sounds and positional data, allowing for non-invasive and accurate sleep apnea diagnosis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sensors and electrodes are used for sleep detection, then measurement precision is improved, but device complexity increases and ease of operation deteriorates
Solution Approach 1:
The patent combines multiple sensing functions (acoustic breath sound detection, airflow measurement, and positional data acquisition) into a single wearable mask device. This integration reduces the number of separate sensors and electrodes needed while maintaining comprehensive sleep apnea detection capability through coordinated data from the unified device.
Solution Approach 2:
The wearable mask serves multiple functions simultaneously: it detects breath sounds via microphone, measures airflow through pressure sensors, tracks positional information via accelerometer, and monitors snoring events. This multi-functionality eliminates the need for separate specialized sensors for each measurement type, reducing overall device complexity.
2Measurement precision
If multiple electrodes and sensors are deployed, then measurement precision improves, but ease of operation worsens due to displacement issues
Solution Approach 1:
By consolidating multiple sensing elements (microphone, airflow sensor, accelerometer) into a single wearable mask that stays in one location on the patient's face, the system eliminates the displacement problems associated with multiple separate electrodes. The unified device remains stable throughout the sleep period while continuously capturing all necessary physiological signals.
3Measurement precision
If invasive methods with multiple sensors are used, then measurement precision is improved, but object-generated harmful factors increase due to patient discomfort
Solution Approach 1:
The patent replaces traditional mechanical electrode-based detection systems with acoustic and optical sensing methods. The microphone captures breath sounds acoustically, the airflow sensor uses pressure differential measurement rather than direct contact, and the accelerometer optically or mechanically tracks mask position without skin contact. This substitution eliminates skin irritation and discomfort while maintaining diagnostic accuracy.
Data Source
AI summary
Described herein are various embodiments of a method and system for sleep detection. For example, in one embodiment, a method is described for automatically characterizing digitized breath sounds recorded from a subject over time as indicative of the subject being one of asleep and awake. This method comprises identify individual breathing cycles in a given segment of the recorded breath sounds; calculating one or more preset breathing cycle characteristics from the identified breathing cycles; evaluating a relative regularity of the calculated characteristics for the given segment; and upon the relative regularity satisfying a preset high regularity condition, outputting a sleep status indicator that the subject was likely asleep during the segment, otherwise outputting a wake indicator that the subject was likely awake during the segment.