Implantable Accelerometer Verification of Pathologic Episodes
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Solution Overview
Problem
Existing implantable medical devices (IMDs) with 3-D accelerometers face high energy consumption due to continuous data storage and monitoring, leading to reduced device lifespan, and often misinterpret normal activities as pathologic episodes.
Innovation Solution
A system utilizing an accelerometer to obtain and analyze three-dimensional point vectors from accelerometer data, distinguishing between control and activity vectors to verify pathologic episodes based on biological signals, reducing unnecessary data storage and energy consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the IMD constantly monitors and stores 3-D accelerometer motion data to verify pathologic episodes, then the accuracy of pathologic episode detection is improved, but the energy consumption increases
Solution Approach 1:
The system pre-records accelerometer data during normal activities before a pathologic episode occurs. This preliminary data capture allows the device to have motion reference information available when needed, eliminating the need for continuous monitoring and storage of all accelerometer data, thus reducing energy consumption while maintaining detection accuracy.
Solution Approach 2:
The system selectively processes and stores accelerometer data only during specific conditions - namely during normal activities and when a pathologic episode is detected. Instead of uniformly processing all accelerometer data continuously, the device applies different data handling strategies to different time periods, reducing overall energy consumption while preserving necessary diagnostic information.
2Reliability
If the IMD stores all 3-D accelerometer motion data for analysis, then the verification of pathologic episodes is improved, but the memory usage and device complexity increase
Solution Approach 1:
The system extracts only the essential information from accelerometer data by identifying and storing key motion characteristics and patterns rather than retaining all raw data. This extraction approach maintains the ability to verify pathologic episodes while significantly reducing memory requirements and simplifying the device architecture.
Solution Approach 2:
The system performs preliminary analysis of accelerometer data during normal activities to establish baseline motion patterns. This pre-processing creates a reference framework that simplifies subsequent analysis during pathologic episodes, reducing the computational and memory burden during critical verification moments.
3Measurement precision
If the IMD continuously analyzes accelerometer data to distinguish normal activities from pathologic events, then the reduction of false detections is improved, but the processing power and energy consumption increase
Solution Approach 1:
The system performs accelerometer data analysis periodically during normal activities rather than continuously. By scheduling analysis at specific intervals and under specific conditions, the device maintains the ability to distinguish normal activities from pathologic events while reducing the continuous processing burden and associated energy consumption.
Solution Approach 2:
The system applies enhanced analysis only to specific segments of accelerometer data that are most relevant for distinguishing normal activities from pathologic events. Instead of uniformly processing all data with the same computational intensity, the device concentrates processing power where it provides maximum value for reducing false detections.
Data Source
AI summary
A system for verifying a candidate pathologic episode of a patient is provided that includes an accelerometer configured to be implanted in the patient. The accelerometer is configured to obtain accelerometer data along at least one axis. The system also includes a memory configured to store program instructions, and one or more processors that, when executing the program instructions, are configured to obtain accelerometer data. The one or more processors are also configured to determine a plurality of control three-dimensional point vectors related to the accelerometer data, and obtain a biological signal and identify a candidate pathologic episode based on the biological signal. The one or more processors are also configured to analyze the plurality of control three-dimensional point vectors to identify a physical action experienced by the patient, and verify the candidate pathologic episode based on the physical action.