Defibrillator ECG Rhythm Detection With Variable-Time Analysis
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Solution Overview
Problem
Existing cardiac resuscitation systems take too long to identify shockable or non-shockable rhythms in ECG data, leading to potential delays in administering life-saving defibrillation shocks.
Innovation Solution
A defibrillator system that analyzes ECG data using pre-validated conditions with low false-positive rates to rapidly identify shockable or non-shockable rhythms by applying variable-length time segments and adjusting rule sets for accurate determination within seconds, allowing for immediate feedback to caregivers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional ECG analysis methods are used to ensure accurate identification of shockable rhythms, then measurement precision is improved, but loss of time increases due to longer analysis durations
Solution Approach 1:
The patent segments the ECG analysis process into multiple stages: initial rapid assessment using fewer clauses, followed by progressive addition of more clauses if needed. This segmentation allows the system to make quick decisions when possible while maintaining accuracy when necessary, resolving the contradiction between speed and precision.
Solution Approach 2:
The patent implements dynamic adjustment of analysis parameters, including variable clause selection based on signal quality and adaptive time segment lengths. The system dynamically determines the appropriate level of analysis depth based on real-time conditions, enabling fast identification when signal quality permits while ensuring accuracy when conditions are less favorable.
2Measurement precision
If more ECG data is collected and analyzed to improve rhythm identification accuracy, then measurement precision is improved, but productivity decreases due to longer analysis time
Solution Approach 1:
The patent applies preliminary filtering and assessment criteria to quickly evaluate whether the ECG signal meets basic quality thresholds and shows obvious shockable patterns. This preliminary action allows the system to make rapid determinations when signals are clear, reserving more comprehensive analysis for ambiguous cases, thus improving overall productivity while maintaining precision.
Solution Approach 2:
The patent changes analysis parameters dynamically based on signal characteristics, adjusting the number of clauses applied, time segment length, and analysis depth. This parameter adaptation enables the system to achieve high reliability with minimal analysis time for clear cases, improving the overall speed-defibrillation delivery productivity.
3Reliability
If the defibrillator waits for complete ECG analysis before delivering shock, then reliability of treatment is improved, but loss of time increases
Solution Approach 1:
The patent implements dynamic decision-making where the system continuously evaluates ECG data and can transition from rapid assessment to comprehensive analysis based on emerging signal characteristics. This dynamic approach allows the system to deliver shocks reliably when shockable rhythms are clearly identified early, while extending analysis only when necessary to maintain accuracy.
Solution Approach 2:
The patent uses continuous feedback from ECG signal quality assessment and intermediate analysis results to adjust the analysis trajectory. When feedback indicates clear shockable patterns, the system proceeds to rapid shock delivery; when feedback suggests ambiguity, the system extends analysis, thus maintaining reliability while minimizing time loss.
Data Source
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AI summary
Methods and systems that analyze electrocardiogram (ECG) data to identify whether it would be beneficial for a caregiver to administer an electric shock to the heart in an effort to get the heart back into a normal pattern and a consistent, strong beat. By conducting a running check for conditions that are pre-validated by a comprehensive patient database to have high predictive value (e.g., with a low false-positive rate), a shockable rhythm can be identified fast (e.g., less than 6 seconds, less than 3 seconds, possibly in less than a second) and without having to analyze ECG data for longer time segments than would otherwise be required using conventional methods.