Custom Sleep Parameter Generation via Biomarker Stimulation

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Solution Overview

Problem

Traditional techniques for measuring brain activity during sleep are limited in their ability to efficiently and effectively tailor custom sleep parameters for users, failing to utilize measurements of neural and heart activity to achieve specific sleep profile targets.

Innovation Solution

Systems and methods that receive input parameters via a user interface, process them to generate sleep parameters, and then stimulation parameters, which are applied to the user to modify biomarkers such as band activities and frequency spectra, with feedback loops to assess efficacy.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If traditional measurement techniques are used to measure brain activity during sleep, then measurements of neural and heart activity can be obtained, but the ability to efficiently and effectively tailor custom sleep parameters is limited

Engineering Contradiction:

Improveability to tailor custom sleep parametersVSAvoidcomplexity of measurement and processing system

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system segments the sleep parameter adjustment process into distinct stages: receiving input parameters, generating sleep parameters, generating stimulation parameters, and applying stimuli. This segmentation allows each component to focus on specific tasks, improving adaptability while managing system complexity through modular architecture.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system dynamically adjusts sleep parameters and stimulation parameters based on real-time measurement data and user input. The processing device generates customized parameters that adapt to individual user needs and sleep stages, enabling efficient tailoring of custom sleep parameters without requiring overly complex measurement systems.

Inventive Principle:

Principle #15Dynamics

2Productivity

If multiple measurements of brain activity and other physiological parameters are obtained during sleep, then comprehensive sleep profile data is available, but traditional techniques fail to efficiently utilize these measurements for custom tailoring

Engineering Contradiction:

Improveefficiency of utilizing measurement data for custom sleep parametersVSAvoidunderutilization of measurement data

Core Design Contradiction:

ProductivityVSLoss of information

Solution Approach 1:

The system incorporates feedback loops where measurement data from sleep stages is continuously monitored and used to adjust stimulation parameters. This feedback mechanism ensures that the system efficiently utilizes measurement data to achieve specific sleep profile targets, preventing information loss by actively incorporating all available data into parameter generation and adjustment.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system performs preliminary processing of measurement data to identify sleep stages and generate initial sleep parameters before applying stimulation. This preliminary action organizes and pre-processes the comprehensive measurement data, improving productivity by preparing customized parameters in advance rather than reacting to data after the fact.

Inventive Principle:

Principle #10Preliminary action

3Manufacturing precision

If custom sleep parameters are implemented through multiple processing steps, then specific sleep profile targets can be achieved, but the system complexity increases

Engineering Contradiction:

Improveprecision of achieving sleep profile targetsVSAvoidnumber of processing steps and parameters

Core Design Contradiction:

Manufacturing precisionVSDevice complexity

Solution Approach 1:

The system achieves precise sleep profile targets by systematically changing parameters through defined transformations. Input parameters are converted to sleep parameters, which are then converted to stimulation parameters. This parameter transformation approach maintains precision by using clear mapping relationships between parameter types, while managing complexity through standardized transformation rules.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The system introduces intermediary processing layers that translate between different parameter domains. The processing device acts as an intermediary that receives input parameters, generates sleep parameters as an intermediate representation, and then generates stimulation parameters. This intermediary approach simplifies the overall system by breaking down complex transformations into manageable stages with clear interfaces.

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS20240165371A1Systems, methods, and devices for custom sleep implementation

Publication Date: 2024.05.23 STIMSCIENCE INC

AI summary

Provided are systems, methods, and devices for implementation of custom sleep parameters. Methods include receiving, via a user interface, a plurality of input parameters associated with a sleep profile of a user, the plurality of input parameters representing at least one sleep profile target, generating, using one or more processors of a processing device, a plurality of sleep parameters based, at least in part, on the received plurality of input parameters, the plurality of sleep parameters representing one or more changes to one or more biomarkers of the user, and generating, using one or more processors of the processing device, a plurality of stimulation parameters based, at least in part, on the plurality of sleep parameters, the plurality of stimulation parameters representing stimuli configured to implement the identified changes for each of the identified biomarkers of the user's sleep profile.