Atrial Fibrillation Burden Calculation Using Adaptive Sampling
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing ambulatory medical devices face limitations in recording and transmitting physiologic information due to hardware constraints, leading to incomplete data and potential false positive adjudications of atrial fibrillation episodes.
Innovation Solution
The system determines and records key metrics of atrial fibrillation at a lower sampling frequency, allowing for the calculation of atrial fibrillation burden without exceeding existing hardware limitations, and uses these metrics to compare with adjudicated episodes for accurate burden determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If physiologic information is recorded at a high sampling frequency to ensure accurate detection of atrial fibrillation episodes, then measurement precision is improved, but the device exceeds hardware limitations for storage and transmission capacity
Solution Approach 1:
The patent segments the recording process into two distinct stages: (1) initial high sampling frequency recording during detection windows to ensure accurate AF detection, and (2) subsequent lower sampling frequency recording for burden calculation. This segmentation allows the device to maintain detection accuracy while reducing overall data volume to fit hardware constraints.
Solution Approach 2:
The patent dynamically changes the sampling frequency parameter based on the recording stage and data threshold. The system transitions from a first sampling frequency (higher) during initial recording to a second sampling frequency (lower) for continued recording, thereby adapting the data generation rate to match hardware storage and transmission capabilities while maintaining sufficient measurement precision.
2Reliability
If data from all detection windows is included to improve accuracy of burden determination, then reliability is improved, but the device exceeds hardware limitations for storage and transmission capacity
Solution Approach 1:
The patent extracts only the essential information needed for burden calculation from the complete detection window data. By calculating burden metrics from representative samples and key parameters rather than storing and transmitting all raw physiologic data, the system achieves reliable burden determination while staying within hardware data volume limitations.
3Loss of information
If the device records physiologic information up to a data threshold to manage storage capacity, then loss of information is reduced, but false positive adjudications occur due to incomplete data
Solution Approach 1:
The patent performs preliminary high-frequency recording during detection windows to capture complete AF episode data before the data threshold is reached. This preliminary action ensures that sufficient data is available for accurate adjudication of individual episodes, while the overall burden calculation uses lower-frequency data from all windows to maintain reliability without exceeding storage capacity.
Data Source
AI summary
Systems and methods are disclosed to determine and record one or more key metrics of atrial fibrillation for a patient, including determining indications of atrial fibrillation of the patient in respective detection windows of a day using received physiologic information, recording first physiologic information of the patient at a first sampling frequency for the determined indications of atrial fibrillation of the patient up to and not exceeding a first threshold of the medical device system for transmission to a remote device, and determining and recording one or more key metrics of atrial fibrillation for the determined indications of atrial fibrillation of the patient at a second sampling frequency lower than the first sampling frequency without regard to the first threshold.