Snoring Detection Using Wearable Sensor Correlation
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Solution Overview
Problem
Conventional wearable devices struggle to accurately determine whether a user is snoring and provide reliable sleep-related information, especially when multiple entities are present, leading to potential false positives and an inability to assess snore intensity accurately.
Innovation Solution
Combining audio data from microphones with sensor data from wearable devices, such as photoplethysmogram (PPG) signals and accelerometers, to correlate breathing patterns and determine if the user is snoring, while also accounting for distance and pose to improve snore metric accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If audio data from microphones is used to detect snoring, then snoring detection capability is improved, but false positives occur when multiple entities are present
Solution Approach 1:
The patent uses sensor data from the wearable device as an intermediary to verify and confirm snoring events detected by audio data. The sensor data acts as a mediator that distinguishes between actual user snoring and other sounds, resolving the false positive problem when multiple entities are present.
Solution Approach 2:
The patent combines audio data from microphones with sensor data from wearable sensors to create a more reliable snoring detection system. By merging multiple data sources and cross-validating them, the system improves detection accuracy and reduces false positives.
2Device complexity
If conventional wearable devices use basic sensors, then device complexity is reduced, but inability to assess snore intensity accurately
Solution Approach 1:
The patent makes existing wearable device sensors multi-functional by using them not only for their primary purposes but also for snoring detection and intensity assessment. The sensors serve multiple functions including motion detection, physiological monitoring, and snore verification, eliminating the need for additional specialized hardware.
3Device complexity
If audio data alone is used for snoring detection, then device complexity is minimized, but false positives and inability to correlate with user breathing patterns
Solution Approach 1:
The patent implements a feedback mechanism where sensor data from the wearable device provides continuous verification of snoring events detected by audio data. The breathing patterns captured by sensors feedback to confirm or reject audio-based snoring detections, significantly improving reliability.
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
This approach enables accurate identification of snoring activity and provides detailed snore metrics, including intensity and duration, reducing false positives and offering precise sleep-related insights for users.
Implementation Method 1
determine the breathing phase pattern based at least in part on one or more heart rate signals as determined from a photoplethysmogram (PPG) signal as captured by one or more PPG sensors in the electronic device
Implementation Method 2
determine the breathing phase pattern based at least in part on one or more motion-based measurements as captured by one or more accelerometers in the electronic device
Implementation Method 3
determine one or more breathing phase patterns over a period of time using audio data captured by at least one microphone. The audio data can include one or more snores.
Data Source
AI summary
Approaches described herein can determine one or more breathing phase patterns over a period of time using audio data captured by at least one microphone. The audio data can include one or more snores. A breathing phase pattern included within the period of time can be determined based at least in part on sensor data captured by one or more sensors in the electronic device. A determination can be made that a first breathing phase pattern represented by the audio data and a second breathing phase pattern represented by the sensor data are correlated. A determination can be made that the first breathing phase pattern represented by the audio data and the second breathing phase pattern represented by the sensor data both correspond to a user wearing the electronic device.