Sleep Induction System Using Binaural Beats and ASMR
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Solution Overview
Problem
Existing sleep induction technologies lack accuracy in determining sleep stages, particularly NREM sleep, and fail to provide personalized auditory stimuli based on individual frequency characteristics, leading to low reliability and quality of sleep improvement.
Innovation Solution
A closed-loop system that measures brain signals using EEG, calculates functional connectivity, determines sleep stages, and generates binaural beats with ASMR information to induce mental stability and adjust auditory stimuli according to sleep stage, ensuring accurate sleep stage identification and quality improvement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional sleep stage classification methods based on brain wave amplitude changes are used, then the classification process is simple, but the accuracy of sleep stage identification is low and cannot accurately identify NREM sleep stages
Solution Approach 1:
The patent segments the sleep monitoring approach by introducing multiple sensors (accelerometer, gyroscope, barometer, temperature sensor, humidity sensor) that measure different physiological and environmental parameters. Each sensor provides specific data about sleep stages, and the segmentation of analysis into multiple features (movement intensity, orientation changes, temperature variations) enables more accurate NREM sleep stage identification compared to conventional single-parameter methods
Solution Approach 2:
The patent uses environmental temperature and humidity as intermediary parameters to indirectly detect sleep stages. The temperature sensor detects body temperature changes and ambient temperature variations that correlate with sleep stages, while the humidity sensor detects moisture changes from breathing and sweating. These intermediary measurements provide additional information about NREM sleep stages without requiring complex direct brain wave analysis
2Reliability
If generic auditory stimuli are provided for sleep induction, then the implementation is simple, but the effectiveness is low due to lack of personalization
Solution Approach 1:
The patent applies local quality by providing different auditory stimuli tailored to specific sleep stages and individual user characteristics. The system analyzes movement patterns, orientation changes, and environmental conditions to determine the current sleep stage, then selectively applies appropriate auditory stimuli (white noise, nature sounds, music) with specific frequencies and intensities suited for that stage, rather than using a single generic stimulus for all stages
Solution Approach 2:
The patent dynamically changes auditory stimulus parameters (frequency, intensity, type) based on detected sleep stage and individual user responses. The system monitors movement intensity and orientation changes in real-time, and adjusts the auditory stimulus parameters accordingly to maintain effectiveness throughout different sleep stages, transforming the static generic stimulus into a dynamic personalized intervention
3Measurement precision
If multiple sensors and complex analysis are used to accurately identify sleep stages, then the measurement accuracy improves, but the device complexity and processing requirements increase
Solution Approach 1:
The patent implements multi-functionality by designing a unified processing system that handles data from multiple sensors (accelerometer, gyroscope, barometer, temperature sensor, humidity sensor) through a single set of processing units. The processor integrates data from all sensors and performs comprehensive sleep stage analysis, making the system versatile enough to accurately detect both NREM and REM sleep stages using a unified approach rather than requiring separate specialized systems for each sensor type
Solution Approach 2:
The patent merges multiple sensor inputs and processing functions into an integrated system. The processor combines data from movement sensors, orientation sensors, environmental sensors, and audio sensors into a unified analysis framework. By merging these diverse data streams and processing them together, the system achieves accurate sleep stage identification while avoiding the complexity of separate independent processing systems for each sensor type
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 system effectively evaluates sleep stages, including NREM sleep, and provides personalized auditory stimuli, increasing the reliability and quality of sleep by maintaining appropriate sleep stage proportions and inducing mental stability.
Implementation Method 1
acquiring brain signals of a user as sleeping time passes
Implementation Method 2
generating a binaural beat to induce the brain signals of the user to a target frequency
Data Source
AI summary
The method for inducing sleep by a sleep inducing system includes acquiring brain signals of a user as sleeping time passes; calculating a functional connectivity value between two channels for each frequency based on the acquired brain signals and performing brain network analysis; determining the stage of sleep of the user based on features of the analyzed brain network; determining a target frequency according to the determined stage of sleep and generating a binaural beat with which the brain signals of the user are induced to the target frequency; combining the generated binaural beat with ASMR information; providing the combined auditory stimulus information to the user; and determining whether the current stage of sleep of the user is maintained at an appropriate proportion with respect to total sleep time, determining whether or not to induce the next stage of sleep, and performing feedback according to the result of determination.