Adaptive White Noise Playback for Tinnitus and Sleep Support
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Solution Overview
Problem
There is no known cure for tinnitus, a sound heard by individuals with no external source, and existing treatments are inadequate.
Innovation Solution
An auditory device monitors background sound pressure levels and plays white noise when the levels are below a threshold, using machine-learning models to adjust thresholds and durations based on user profiles and activity data, and includes noise cancellation to reduce distractions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If white noise is played continuously to treat tinnitus, then treatment effectiveness is improved, but energy consumption increases and user annoyance increases
Solution Approach 1:
The system uses periodic monitoring of background sound pressure levels and plays white noise only during periods when the background SPL falls below the threshold, rather than continuous playback. This periodic activation based on environmental conditions reduces energy consumption while maintaining treatment effectiveness during necessary periods.
Solution Approach 2:
The system continuously monitors background sound pressure levels and uses this feedback to dynamically control white noise playback. When the monitored SPL rises above the threshold, playback stops; when it falls below, playback resumes. This feedback loop ensures energy is consumed only when treatment is needed.
2Reliability
If white noise is played continuously to treat tinnitus, then treatment effectiveness is improved, but user annoyance increases
Solution Approach 1:
White noise is played periodically based on background SPL conditions rather than continuously. This reduces user annoyance from constant noise exposure while maintaining treatment effectiveness during periods when background noise is insufficient to mask tinnitus.
Solution Approach 2:
The system automatically detects when white noise playback is needed by monitoring background SPL and autonomously activates or deactivates playback without user intervention. This self-regulating approach prevents user annoyance from unnecessary or mistimed playback while ensuring treatment occurs when needed.
3Adaptability or versatility
If machine-learning models are used to adjust white noise parameters, then adaptability to individual users is improved, but device complexity increases
Solution Approach 1:
The patent employs machine-learning models as intermediary components that process user profiles, activity data, and background SPL information to automatically determine optimal white noise parameters. These models act as mediators between raw sensor data and playback control, enabling sophisticated user adaptation without requiring complex manual configuration or processing logic in the main device.
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
The device effectively treats tinnitus and improves sleep quality by playing white noise only when necessary, reducing reliance on external noise and minimizing annoyance.
Implementation Method 1
playing, with a speaker of an auditory device, white noise
Implementation Method 2
monitoring a background sound pressure level (SPL)
Implementation Method 3
generating noise cancellation sound waves that are played along with the white noise to reduce distractions from the background SPL
Data Source
AI summary
A computer-implemented method monitors a background SPL. The method also determines that the background SPL is below a first SPL threshold. A speaker of an auditory device plays white noise. The method, responsive to determining that the white noise has played for a first length that meets a first time threshold or that the background SPL meets the first SPL threshold, stops playing the white noise. The method further includes continuing to monitor the background SPL until the background SPL is below the first SPL threshold.


