Dynamic Snoring Masking Based on Sleep Stage and Noise Source
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Solution Overview
Problem
Existing sound masking technologies for sleep disruption due to ambient noises are ineffective as they operate at constant volumes and frequencies, failing to account for varying environmental noises and the subject's sleep physiology, and expose subjects to unnecessary masking sounds.
Innovation Solution
An audio device with a microphone, biosensor, and processing unit that detects and distinguishes between the wearer's and a partner's breathing noises, adjusting masking sounds based on sleep condition and noise patterns to minimize exposure to unnecessary sounds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a blanket masking sound is output at constant volume and frequency throughout the entire sleep period, then the subject is continuously protected from ambient noises, but the masking sound may itself disrupt the subject's sleep and exposes the subject to unnecessary sound exposure for long periods
Solution Approach 1:
The patent applies dynamics by transitioning from a static blanket masking sound to a dynamic masking sound that adapts in real-time. The system continuously monitors the subject's sleep stages through biosensors and adjusts the masking sound's volume, frequency, and duration accordingly. During light sleep, masking is more aggressive; during deep sleep, masking is reduced or stopped, preventing sleep disruption while maintaining protection when needed.
Solution Approach 2:
The patent implements parameter changes by modifying the masking sound's characteristics (volume, frequency, duration) based on monitored sleep parameters. The system changes the masking sound parameters dynamically according to the subject's sleep stage, transitioning between different masking intensities to optimize both protection effectiveness and sleep quality.
2Reliability
If a blanket masking sound is output throughout the entire sleep period, then continuous noise protection is provided, but the subject is exposed to masking sounds for long periods regardless of whether the mask is necessary
Solution Approach 1:
The patent applies periodic action by implementing intermittent masking based on sleep stage cycles. The system activates masking during specific periods when the subject is in light sleep stages vulnerable to noise disruption, and deactivates or reduces masking during deep sleep stages when the subject is less susceptible to noise. This periodic on/off pattern based on sleep cycles eliminates unnecessary sound exposure while maintaining protection when needed.
Solution Approach 2:
The patent implements feedback by continuously monitoring the subject's sleep stages through biosensors and using this information to control the masking sound output. The system adjusts masking based on real-time feedback from sleep stage detection, creating a closed-loop system that optimizes both protection and energy efficiency by avoiding unnecessary masking during appropriate sleep stages.
3Adaptability or versatility
If the masking sound volume and frequency are adjusted dynamically based on sleep physiology and environmental noises, then the masking effectiveness is optimized, but the device complexity increases
Solution Approach 1:
The patent applies universality by integrating multiple functions into a single sleep protection system. The device combines biosensors for sleep stage monitoring, environmental noise detection, masking sound generation, and adaptive control algorithms into one unified system. This multi-functional approach achieves high adaptability while managing complexity through consolidation rather than separate components.
4Measurement precision
If the masking sound is aligned with the time-frequency pattern of breathing noises, then the masking precision is improved, but the processing requirements and device complexity increase
Solution Approach 1:
The patent applies copying by creating a virtual model or representation of the breathing noise pattern through signal processing. The system analyzes the time-frequency characteristics of detected breathing noises and generates a corresponding masking pattern that mirrors these characteristics. This copying approach enables precise targeting of masking to actual noise sources while managing processing complexity through algorithmic pattern recognition rather than exhaustive analysis.
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
Effectively masks partner's breathing noises while reducing the subject's acoustic trauma by dynamically adjusting sound levels and frequencies, aligning with noise patterns, and minimizing unnecessary sound exposure.
Implementation Method 1
at least one microphone configured to detect audible breathing noises in a sleeping environment
Implementation Method 2
at least one speaker configured to output a masking sound to compensate for the detected audible breathing noises
Data Source
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AI summary
Aspects of the present disclosure provide methods, apparatuses, and systems for dynamically masking audible breathing noises determined to be generated by one or more sleeping partners. According to aspects, a subject's sleep is protected by detecting audible breathing noises in a sleeping environment, determining the audible breathing noises are not generated by the subject, and mitigating the perception of the audible breathing noises that are determined to originate from anther subject, such as a bed partner, pet, etc. The dynamic masking reduces the subject's exposure to unnecessary sounds and reduces the chances of masking sounds disturbing the subject's sleep.