Motion Sensor Axis Configuration for Implantable Devices
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Solution Overview
Problem
Current implantable devices with motion sensors face challenges in accurately analyzing data from multiple axes, leading to inefficiencies in energy usage and potential malsensing issues, as they often require continuous monitoring of all axes which drains battery life and can result in inappropriate therapy delivery.
Innovation Solution
The implementation of a system that selectively disables or temporoarily disables less useful axes of the motion sensor based on posture and activity analysis, using conversion matrices to normalize sensor outputs to a patient's frame of reference, allowing for more efficient data analysis and reduced power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If continuous monitoring of all motion sensor axes is performed, then complete patient activity data is captured, but battery life is drained and energy consumption increases
Solution Approach 1:
The motion sensor data processing is segmented by disabling less useful axes selectively based on patient posture and activity analysis. Instead of continuously monitoring all axes, the system divides monitoring into essential and non-essential axes, reducing overall energy consumption while maintaining necessary monitoring coverage
Solution Approach 2:
The system dynamically adjusts which motion sensor axes are active based on real-time analysis of patient posture and activity. The configuration of enabled/disabled axes changes over time according to clinical conditions and patient state, optimizing the balance between data accuracy and energy consumption
2Reliability
If all motion sensor axes are continuously monitored, then comprehensive motion data is obtained, but device complexity and data analysis burden increase
Solution Approach 1:
The system extracts and disables less useful motion sensor axes from continuous monitoring based on posture and activity analysis. By taking out non-essential axes from the active monitoring set, the system reduces data processing complexity and computational burden while retaining essential motion data for accurate therapy delivery
Solution Approach 2:
Instead of monitoring all motion sensor axes continuously, the system applies partial monitoring by selectively enabling only the necessary axes for each clinical situation. This partial action approach reduces data processing complexity while providing sufficient information for accurate therapy delivery
3Measurement precision
If motion sensor data from multiple axes is analyzed, then patient activity level is accurately determined, but power consumption increases
Solution Approach 1:
The system applies local quality by selectively monitoring specific motion sensor axes based on their relevance to patient activity detection in different postures. Instead of uniformly monitoring all axes, the system identifies and monitors only the locally relevant axes for each clinical situation, reducing power consumption while maintaining activity detection accuracy
Solution Approach 2:
The system changes operational parameters by dynamically adjusting which motion sensor axes are enabled based on patient posture and activity analysis. This parameter change approach allows the system to optimize the balance between measurement precision and power consumption by adapting to different clinical conditions
Data Source
AI summary
Implantable devices having motion sensors. In some examples the a configuration is generated for the implantable device to use the motion sensor in an energy preserving mode in which one or more axis of detection of the motion sensor is disabled or ignored. In some examples the motion sensor outputs along multiple axes are analyzed to determine which axes best correspond to certain patient parameters including patient motion/activity and/or cardiac contractility. In other examples the output of the motion sensor is observed across patient movements or postures to develop conversion parameters to determine a patient standard frame of reference relative to outputs of the motion sensor of an implanted device.