Quantifying Nerve Stimulation Response via Airflow Synchronization
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Solution Overview
Problem
Current methods for assessing the effectiveness of nerve stimulation therapy for obstructive sleep apnea, such as polysomnography and drug-induced sleep endoscopy, are invasive, qualitative, or require lengthy data collection, making them unreliable and impractical for guiding therapy titration or predicting response.
Innovation Solution
A computer-implemented method that analyzes short-time physiological data to quantify the response to nerve stimulation by identifying airflow synchronization with stimulation events, calculating air volume ratios, and determining a 'hit rate' using PSG data, allowing for objective and quantitative assessment of therapy efficacy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If polysomnography is used to assess therapy effectiveness, then measurement reliability is improved, but loss of time increases due to requiring long-time data collection
Solution Approach 1:
The patent extracts and focuses on specific critical parameters (airflow signal, respiratory effort signal, stimulation signal) from the comprehensive polysomnography data, analyzing only these essential signals to determine therapy effectiveness. This extraction approach maintains measurement reliability while significantly reducing the time required for data collection and analysis compared to traditional comprehensive PSG assessment.
2Measurement precision
If traditional PSG-based AHI/ODI scoring is used, then measurement precision is improved, but device complexity increases due to requiring multiple nights of sleep studies
Solution Approach 1:
The patent segments the therapy assessment into distinct functional components: detecting stimulation events, identifying respiratory cycles, analyzing airflow patterns, and calculating synchronization metrics. This segmentation allows for precise measurement of therapy effectiveness through modular analysis of specific signal relationships, reducing the complexity of the overall assessment protocol while maintaining measurement precision.
Solution Approach 2:
The patent applies partial action by focusing on analyzing only the critical portion of PSG data necessary for therapy assessment - specifically the synchronization between stimulation events and respiratory cycles - rather than requiring complete multi-night studies with comprehensive scoring of all sleep parameters. This partial analysis approach achieves sufficient precision for therapy effectiveness determination with reduced protocol complexity.
3Ease of operation
If visual observation methods are used to assess tongue protrusion, then ease of operation is improved, but measurement precision deteriorates due to qualitative rather than quantitative assessment
Solution Approach 1:
The patent replaces the mechanical visual observation method with an automated signal processing system that quantitatively analyzes the synchronization between stimulation events and airflow/respiratory signals. This substitution transforms the qualitative visual assessment into an objective quantitative measurement, improving precision while maintaining ease of operation through automated computation of synchronization metrics.
Solution Approach 2:
The patent introduces signal processing algorithms as an intermediary between the raw PSG data and the therapy effectiveness assessment. This intermediary automatically detects stimulation events, identifies respiratory cycles, and calculates synchronization metrics, providing precise quantitative measurement without requiring manual visual observation while keeping the operation simple and automated.
Data Source
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AI summary
Disclosed herein is a Computer-implemented method for quantification of a level of response to nerve stimulation, the method comprising the following steps: a) transfer a stimulation parameter data to a data processing unit; b) transfer at least a subgroup of physiological data corresponding to a subject to the data processing unit; c) identify at least one physiological signal of the physiological data corresponding to the therapy's impact on the subject's airway opening; d) detect ON-instants and OFF-instants in a defined time segment of the physiological data, wherein each ON-instant corresponds to an instant of time in which the subject was stimulated and wherein each OFF-instant corresponds to an instant of time in which the subject was not stimulated; e) detect at least one breath cycle; f) for each breath cycle detected, analyze an airflow segment and check if it was synchronized with an ON-instant or with an OFF-instant; g) sort each airflow segment into one of two groups based on its respectively checked synchronization with an ON/OFF-instant, the two groups being an ON-group comprising airflow signals that are synchronized with ON-instants and an OFF-group comprising airflow signals that are synchronized with OFF-instants; h) for each of the two groups, separately determine an airflow curve from all airflow segments of each respective group; i) calculate an volume of air for each of the two airflows; j) determine an impact of stimulation based on visualization of the two airflows and/or on a ratio of the two volumes.