Atrial Fibrillation Complexity Scoring with ECG Electrical Burden
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Solution Overview
Problem
Current AF metrics, such as AF burden, do not adequately account for the complexity and severity of atrial fibrillation, limiting their effectiveness in clinical decision-making and patient risk assessment.
Innovation Solution
A complexity AF score is calculated using both AF burden and electrical burden scores derived from ECG data, integrating frequency and electrical properties of AF signals to identify the type of AF complexity and recommend targeted treatments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional AF burden metrics are used for risk assessment, then the assessment is simple to calculate, but the assessment does not adequately capture AF complexity and severity
Solution Approach 1:
The patent combines multiple AF assessment metrics (AF burden, electrical burden, and complexity metrics) into a unified complexity AF score. This merging of separate measurement dimensions into a composite score allows comprehensive risk assessment while maintaining clinical usability through a single integrated metric.
Solution Approach 2:
The complexity AF score functions as a composite metric that integrates multiple underlying components (time-based AF burden, electrical burden from ECG morphology, and complexity measures). This composite approach captures multiple aspects of AF severity simultaneously, improving assessment accuracy without requiring clinicians to evaluate multiple separate metrics.
2Loss of information
If intermittent and short rhythm monitoring is used, then the monitoring is practical and manageable, but limited information on total burden and temporal pattern of AF is obtained
Solution Approach 1:
The patent transforms the monitoring approach by changing key parameters: extending monitoring duration from intermittent/short to continuous/long-term, and shifting from simple presence/absence detection to comprehensive temporal pattern analysis. This parameter transformation enables capture of total AF burden and temporal characteristics while maintaining data manageability through automated analysis.
3Ease of operation
If qualitative patient response scales are used for risk assessment, then the assessment is easy to administer, but the assessment is challenging to use in everyday clinical practice
Solution Approach 1:
The patent replaces qualitative patient-reported measures with objective quantitative ECG-based metrics. By substituting mechanical/questionnaire-based assessment with automated ECG analysis, the system maintains ease of operation through objective data collection while dramatically improving measurement precision through quantifiable electrical burden and complexity metrics.
Data Source
AI summary
In a method of identifying a type of AF complexity and/or a treatment of AF based on the type of AF complexity, electrocardiogram (ECG) data associated with a patient is received, the ECG data includes AF signals corresponding to AF episodes. An AF burden (AFB) score is calculated using the ECG data based upon a frequency of the AF episodes or a duration of the AF episodes. An electrical burden (EB) score indicating a variation and distribution of electrical properties of the AF signals is calculated based on EB values of the ECG data in accordance with a plurality of approaches. A complexity AF score is calculated by summing the AFB and the EB scores. A type of AF complexity and/or a treatment is identified based on the complexity AF score. The complexity AF score, the identified type and/or the identified treatment is output on a display device.