Implantable Device Data Storage Using Variability-Based Signal Filtering
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Implantable medical devices face challenges in physiological data storage and maintenance due to constraints in storage capacity, onboard power, and communication bandwidth, necessitating efficient data management to conserve battery power and optimize memory usage.
Innovation Solution
Implementing a system that selectively stores a subset of physiological data based on a feature value margin correlated to baseline signal variability, reducing memory usage and power consumption by storing only data that falls outside a predetermined feature value margin.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If physiological data is stored onboard in the IMD, then data availability for inspection and processing is improved, but memory capacity constraints are worsened
Solution Approach 1:
The patent extracts and transmits only the most critical physiological data (such as peak values, trough values, and abnormal readings) to the external device, leaving the IMD with a lighter memory load. This allows the system to maintain data availability for inspection while working around memory capacity constraints by offloading data externally.
Solution Approach 2:
Instead of storing all physiological data, the system stores only a partial subset that is most likely to be clinically relevant. This partial action approach reduces memory consumption while maintaining sufficient data for effective inspection and processing.
2Productivity
If physiological data is transmitted to external device, then data processing capability is improved, but transmission energy consumption is worsened
Solution Approach 1:
The system extracts only the most essential data points for transmission to the external device, significantly reducing the amount of data that requires energy-intensive transmission. This maintains data processing capability while minimizing transmission energy consumption.
Solution Approach 2:
The IMD performs preliminary processing and filtering of physiological data locally, identifying and preparing only the most critical data points for transmission. This preliminary action reduces the transmission burden and associated energy consumption while ensuring that the most important data is sent for further processing.
3Duration of action of stationary object
If battery power is conserved, then device longevity is improved, but data storage and transmission capabilities are worsened
Solution Approach 1:
By extracting and transmitting only critical data points rather than all data, the system reduces the energy consumption associated with data management operations. This conservation of battery power extends device longevity while maintaining sufficient data storage and transmission capabilities for effective operation.
4Quantity of substance
If feature value margin is used to filter data, then memory usage is reduced, but data completeness is worsened
Solution Approach 1:
The system uses a dynamically adjustable feature value margin parameter to control the filtering process. By optimizing this parameter, the system achieves an balance between memory usage and data completeness, ensuring that sufficient data is retained while reducing overall memory requirements.
Solution Approach 2:
The system incorporates feedback mechanisms to monitor and adjust data filtering based on actual usage patterns and clinical needs. This feedback allows the system to optimize the feature value margin to maintain appropriate data completeness while minimizing memory usage.
Data Source
AI summary
Systems and methods for storing and managing physiological data in implantable medical devices (IMDs) are disclosed. An ambulatory medical-device system includes a sensor circuit to sense a physiological signal from a patient, a memory circuit, and a controller circuit. The controller circuit determines a feature value margin based on a variability metric of baseline signal feature values from a physiological signal sensed during a baseline condition, determines test signal feature values from a physiological signal sensed during a test condition different from the baseline condition, and selectively stores in the memory circuit a subset, less than an entirety, of the determined test values that fall outside the feature value margin about a reference feature value. The stored test values of the signal feature can be transmitted to an external device for inspection or further processing.