Noise Source Identification in Implantable Medical Systems
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Solution Overview
Problem
Implantable medical systems, such as cardiac pacing and defibrillation devices, face challenges in identifying and isolating potential sources of noise within their components, which can lead to inappropriate therapy delivery due to oversensing of non-cardiac signals.
Innovation Solution
A method and apparatus that detect noise in implantable medical systems by analyzing electrocardiogram (EGM) signals using a flow chart process, involving the collection and comparison of EGM samples from various electrode pairs to determine the presence and source of noise, allowing for the identification of potential noise sources within the system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If EGM signals are analyzed to identify noise sources in implantable medical systems, then the reliability of therapy delivery is improved, but the complexity of the diagnostic process increases
Solution Approach 1:
The diagnostic process is segmented into distinct analytical steps: collecting EGM samples from multiple electrode pairs, comparing signals between sensing and recording pairs, identifying discordant samples, and isolating noise sources. This segmentation transforms a complex diagnostic challenge into manageable, systematic steps that can be executed automatically by the device.
Solution Approach 2:
The patent introduces intermediary analytical processes including signal comparison mechanisms and discordance detection algorithms that act as mediators between the raw EGM signals and the final noise source identification. These intermediaries process and interpret the complex signals, reducing the burden on clinicians while maintaining diagnostic accuracy.
2Measurement precision
If multiple EGM samples are collected and compared from various electrode pairs, then the precision of noise source identification is improved, but the time required for analysis increases
Solution Approach 1:
The system performs preliminary actions by automatically collecting and pre-processing EGM samples from multiple electrode pairs before clinical review. The device prepares discordance analyses and noise source candidates in advance, so when a clinician needs to diagnose noise, the preparatory work is already completed, reducing the time required for final assessment.
Solution Approach 2:
The patent replaces manual signal analysis with automated computational methods. Algorithms automatically compare EGM samples, identify discordances, and isolate noise sources, substituting the mechanical process of manual review with electronic signal processing that is both faster and more precise.
3Productivity
If the system automatically analyzes EGM signals to detect oversensing and noise, then the productivity of noise identification is improved, but the device complexity increases
Solution Approach 1:
The implantable device performs self-service by automatically monitoring its own EGM signals, detecting oversensing events, and identifying noise sources without requiring external intervention. The device's processor autonomously executes the diagnostic algorithm, enabling the system to diagnose itself and reducing the need for manual clinical investigation.
Solution Approach 2:
The diagnostic system is integrated into the existing implantable device platform, allowing the same device to perform both its primary therapeutic function (pacing/defibrillation) and the secondary diagnostic function (noise detection and identification). This multi-functionality increases productivity by combining multiple capabilities in a single device rather than requiring separate diagnostic equipment.
Data Source
AI summary
A troubleshooting method can identify potential sources of noise emanating from an implanted portion of a medical system. The method, which may be carried out by the system, for example, according to pre-programmed instructions, includes a step of collecting at least one EGM sample from a sensing pair of electrodes, and an EGM sample from each of a plurality of recording pairs of electrodes. The sensing pair may be formed by first and second electrodes of an implanted lead, and the plurality of recording pairs include pairs formed by each of the lead electrodes and an electrode of an implanted device. Following collection, the EGM samples from the recording pairs may be analyzed for the presence or absence of noise and, then, potential noise sources may be determined.