Implanted Lead Analysis System for Noise Event Detection
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Solution Overview
Problem
Implanted medical device leads experience wear and tear, leading to inaccurate sensing and treatment due to noise issues, which can be attributed to either lead failure or electromagnetic interference, making it challenging for caregivers to accurately identify problematic leads while minimizing false positives.
Innovation Solution
A method and system that analyze medical device data from multiple sensors over time, applying noise detection criteria to differentiate between potential lead failures and electromagnetic interference by calculating the mean number of noise events and comparing them to thresholds, generating alerts for potential lead failures or electromagnetic interference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If noise detection criteria is applied to identify problematic leads, then lead failures can be detected, but false positives increase due to electromagnetic interference being misidentified as lead failure
Solution Approach 1:
The patent segments the noise detection process into two independent analysis streams: one analyzing lead portion data with first noise detection criteria, and another analyzing sensor data with second noise detection criteria. By comparing results from these segmented analyses, the system can distinguish between lead-specific noise and electromagnetic interference affecting multiple components, thereby reducing false positives while maintaining detection accuracy
Solution Approach 2:
The patent introduces a comparison mechanism as an intermediary between the two noise detection processes. This intermediary compares noise event counts from the lead portion and sensor, using the relationship between them to determine whether noise originates from lead failure or electromagnetic interference. This intermediary analysis layer resolves the contradiction by providing additional context that prevents misidentification
2Measurement precision
If multiple sensors and noise detection criteria are used to differentiate lead failure from electromagnetic interference, then accuracy improves, but system complexity increases
Solution Approach 1:
The patent implements multi-functional processing circuitry that performs multiple functions: collecting data from multiple sensors, applying different noise detection criteria to different data sources, counting noise events, calculating means, comparing results, and generating determinations. This universal processing unit handles all analysis tasks within a single system framework, improving accuracy through multiple analysis angles while managing complexity through integrated design
Solution Approach 2:
The system incorporates feedback loops where noise detection results from the sensor are fed back into the analysis process to refine lead failure determination. The comparison between lead portion noise events and sensor noise events creates a feedback mechanism that adjusts the interpretation of lead noise, improving accuracy while using the existing sensor network rather than adding separate complex subsystems
Data Source
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AI summary
Implanted medical device data is received, where the data was sensed by a first lead portion and a sensor over a time period. The number of detected noise events sensed by the first lead portion is counted based on applying first noise detection criteria to the data sensed by the first lead portion. The number of detected noise events over the sensor is counted based on applying second noise detection criteria to the data sensed by the sensor. The mean number of detected noise events is calculated for the first lead portion and sensor based on the number of noise events sensed by the first lead portion and the number of noise events sensed by the sensor. Potential lead failure in the first lead is recorded if the number of detected noise events over the first lead is greater than the mean number of noise events by at least 5%.