Implantable Device Adaptive Signal Processing Artifact Cancellation
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Solution Overview
Problem
Implantable medical devices face challenges in distinguishing desired physiological signals from artifacts, especially in chronically implanted sensors with changing signal characteristics and power constraints, which complicates accurate monitoring and therapy delivery.
Innovation Solution
The implementation of Principal Component Analysis (PCA) to separate and cancel artifacts from physiological signals, allowing for the extraction of a reduced-dimensional signal that retains significant variation associated with the variable of interest, enabling efficient detection of patient conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Duration of action of stationary object
If chronically implanted sensors are used to monitor physiological conditions, then the device can provide long-term monitoring capability, but the signal characteristics change over time and artifacts increase making accurate detection difficult
Solution Approach 1:
The patent implements adaptive signal processing that dynamically adjusts to changing signal characteristics over time. The system continuously adapts its artifact cancellation algorithms to accommodate drift in sensor responses and changing patient conditions, maintaining measurement precision throughout the chronic implantation period
Solution Approach 2:
The system uses feedback mechanisms to monitor signal quality and artifact levels, then adjusts processing parameters accordingly. By continuously analyzing the incoming signals and adjusting artifact cancellation in real-time, the system maintains accurate detection despite changing conditions during long-term implantation
2Adaptability or versatility
If multiple physiological sensors are used to capture comprehensive signal information, then the monitoring coverage is improved, but the power consumption and device complexity increase
Solution Approach 1:
The patent extracts and processes only the most relevant signal components using adaptive artifact cancellation. By identifying and removing artifact signals, the system focuses computational resources on analyzing only the meaningful physiological variations, reducing overall processing power requirements while maintaining comprehensive monitoring capability
Solution Approach 2:
The system dynamically changes processing parameters based on signal quality and artifact levels. When artifacts are high, the system adjusts filtering and analysis parameters to reduce computational load, thereby managing power consumption while preserving essential monitoring functions
3Adaptability or versatility
If multiple physiological sensors are deployed to capture comprehensive data, then the monitoring capability is enhanced, but the number of sensors increases leading to higher power consumption
Solution Approach 1:
The patent implements a universal artifact cancellation framework that works across multiple sensor types and physiological parameters. This multi-functional approach allows the system to handle diverse sensor inputs through a unified processing architecture, reducing overall system complexity despite the presence of multiple sensors
Data Source
AI summary
A medical device having a sensor sensing an n-dimensional signal during a first known variable condition and during a second known variable condition different from the first known variable condition, a processor performing principal component analysis (PCA) on the sensed n-dimensional signal to generate a first template corresponding to a principal component of variation associated with the first known variable condition and a second template corresponding to a principal component of variation associated with the second known variable condition, a storage device storing the first template and the second template, and a controller detecting a patient condition in response to the stored templates.