Loop Recording Overlap Management in Implantable Medical Devices
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Solution Overview
Problem
Implanted medical devices face memory and battery capacity limitations, leading to the loss of important physiologic data due to insufficient memory allocation management, particularly in storing and reporting data related to neurological events.
Innovation Solution
An implantable medical device that stores loop recordings of waveform data with specified pre-event and post-event times, utilizing multiple sense channels and triggers such as seizure detection algorithms and manual patient inputs to selectively store relevant data, and manages memory by handling loop recording overlaps and prioritizing data storage based on event severity and relevance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If the implanted device continuously monitors and stores all physiologic data, then the completeness of neurological event data is improved, but the memory capacity is exceeded causing data loss
Solution Approach 1:
The system performs preliminary actions by detecting neurological events and automatically initiating loop recordings before memory is fully consumed. The device continuously monitors physiologic signals and pre-positions recording buffers, ensuring that when events occur, data is captured without waiting for memory availability. This proactive approach prevents data loss by maintaining ready-to-record state.
Solution Approach 2:
The system applies local quality by selectively storing only the most relevant physiologic data segments around neurological events rather than all continuous data. The loop recording mechanism focuses memory resources on pre-event, during-event, and post-event windows, discarding redundant continuous background data. This localized storage strategy maximizes useful information retention within limited memory capacity.
2Reliability
If the implanted device stores detailed waveform data for all detected events, then the reliability of treatment decisions is improved, but the battery capacity is depleted faster
Solution Approach 1:
The system applies partial action by recording only the necessary portion of physiologic data surrounding neurological events rather than continuous unlimited duration. The loop recording stores pre-event, during-event, and post-event windows, which is sufficient for treatment decisions without excessive energy consumption. This selective recording maintains reliability while extending battery life.
Solution Approach 2:
The system changes parameters by dynamically adjusting recording duration and data resolution based on event characteristics. The loop recording mechanism modifies storage parameters (duration, sampling rate) according to the specific neurological event type and severity, optimizing the balance between data sufficiency for treatment decisions and energy consumption. This adaptive parameter adjustment ensures reliability without excessive battery depletion.
3Device complexity
If the implanted device manages memory using simple FIFO buffer, then the device complexity is reduced, but important data is lost when memory is full
Solution Approach 1:
The system implements feedback by continuously monitoring memory status and event detection results to dynamically adjust recording behavior. When memory approaches capacity or when significant neurological events are detected, the system modifies its recording strategy in real-time. This feedback mechanism prevents data loss by adapting storage actions based on current memory state and event importance, while maintaining manageable complexity through algorithmic control.
Solution Approach 2:
The system applies dynamics by making memory management adaptive rather than static. The loop recording mechanism dynamically adjusts which data segments to store based on event detection, memory availability, and priority algorithms. This dynamic memory management ensures important neurological event data is preserved while avoiding the rigidity and data loss problems of simple FIFO buffers, achieving a balance between complexity and effectiveness.
4Loss of information
If the implanted device records all detected neurological events, then the completeness of event data is improved, but redundant data increases memory consumption
Solution Approach 1:
The system extracts only the essential portions of physiologic data surrounding neurological events from the continuous signal stream. The loop recording mechanism isolates and stores pre-event, during-event, and post-event windows, extracting meaningful segments while discarding redundant continuous background data. This extraction strategy maintains event data completeness while significantly reducing overall memory consumption.
Solution Approach 2:
The system applies segmentation by dividing the continuous physiologic signal into discrete temporal segments around neurological events. The loop recording stores segmented pre-event, during-event, and post-event portions separately, allowing selective retention of relevant segments while discarding irrelevant continuous data. This segmentation approach preserves event completeness while minimizing memory consumption through selective storage.
Data Source
AI summary
A method and apparatus is provided for handling multiple loop recordings that result from events in a limited memory implantable device. The events may include various automatic and manual triggers. The method provides a mechanism for deciding the amount of information to store associated with each overlapping loop recording.