Implantable Medical Device Monitoring via Adaptive Data Analysis
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Solution Overview
Problem
Current medical device monitoring systems face challenges in efficiently determining the operating status of implantable medical devices (IMDs) and patient physiological status, particularly in scenarios where network connectivity is limited or during routine and exception-based follow-ups, requiring improved diagnostic data analysis methods.
Innovation Solution
A computing device and system that receive diagnostic data from IMDs, determine appropriate use cases, and compare it with device characteristics data to assess the operating status, enabling both on-device and remote analysis, including manual and automated analysis platforms for technicians to evaluate IMD and patient health.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If diagnostic data is analyzed remotely with network connectivity, then analysis accuracy and reliability are improved, but system dependency on network infrastructure increases and fails in disconnected settings
Solution Approach 1:
The system dynamically adapts its analysis mode based on network availability. When connected, it performs remote analysis with comprehensive algorithms; when disconnected, it switches to on-device analysis with simplified algorithms, ensuring continuous operational capability across varying network conditions
Solution Approach 2:
The computing device serves as an intermediary between the IMD and remote systems. It can perform local analysis when acting as an standalone interrogator, or relay data for remote analysis when connected, mediating between the need for reliable analysis and network dependency
2Adaptability or versatility
If on-device analysis is performed without network connectivity, then system independence and operational flexibility are improved, but analysis complexity and processing requirements increase the computing device
Solution Approach 1:
The analysis functionality is segmented into two levels: comprehensive remote analysis algorithms stored in the computing device for when connected, and simplified on-device analysis capabilities for when disconnected. This segmentation allows the system to have full analytical capability without requiring all complexity to be present simultaneously in one location
Solution Approach 2:
The computing device contains copies of analysis algorithms that can be executed locally. These algorithm copies enable the computing device to function as an standalone analysis platform when network connectivity is unavailable, without requiring the full complexity of remote system infrastructure
3Measurement precision
If comprehensive diagnostic data collection is performed, then patient monitoring accuracy is improved, but data transmission requirements and processing time increase
Solution Approach 1:
The system performs partial analysis on-device for immediate critical parameters, and comprehensive analysis remotely when connected. This partial action approach provides timely results for urgent matters while maintaining overall monitoring accuracy through subsequent comprehensive remote analysis
Solution Approach 2:
The computing device performs preliminary analysis of diagnostic data locally before potential remote transmission. This preliminary action filters and pre-processes data, reducing transmission requirements and preparing results for faster remote review when connectivity is available
Data Source
AI summary
In some examples, a computing device may receive diagnostic data of a medical device implanted in a patient. The computing device may determine a use case associated with analyzing the diagnostic data out of a plurality of use cases for analyzing the diagnostic data. The computing device may determine, based at least in part on the use case, one or more device characteristics data to be compared against the diagnostic data. The computing device may analyze, based at least in part on comparing the diagnostic data with the one or more device characteristics data, the diagnostic data to determine an operating status of the medical device.