Posture Sensor Automatic Calibration via Walking State Detection
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Solution Overview
Problem
Cardiac rhythm management devices face challenges in accurately calibrating posture sensors, particularly in distinguishing walking states from non-walking activities, which affects the reliability of subsequent posture data.
Innovation Solution
A system and method using a three-axis accelerometer to sense acceleration signals, detect walking states by extracting AC and DC components, and comparing them to templates to perform posture calibration, ensuring accurate orientation and consistency of gravity vectors for calibration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a three-axis accelerometer is used to detect posture, then posture information can be obtained, but the accuracy of posture detection is compromised due to inability to distinguish walking states from non-walking activities
Solution Approach 1:
The system performs preliminary calibration during a detected walking state before actual posture monitoring begins. The calibration process establishes baseline gravity vector orientation and accelerometer orientation relative to the body during a known posture (walking), which then serves as the reference for all subsequent posture calculations. This preliminary action ensures that the calibration is performed under controlled, identifiable conditions rather than attempting to calibrate during ambiguous states.
Solution Approach 2:
The system continuously monitors acceleration signals and uses feedback from the detected walking state to trigger calibration procedures. When the accelerometer detects the characteristic AC component pattern of walking, it provides feedback that initiates the calibration process. This feedback mechanism ensures calibration occurs at appropriate moments when the device can reliably identify the user's state, improving both accuracy and reliability of posture data.
2Measurement precision
If manual calibration procedures are used, then posture sensor accuracy can be improved, but the complexity and time required for calibration increases
Solution Approach 1:
The system performs automatic self-calibration by detecting the user's walking state and automatically executing the calibration algorithm without requiring manual user input or intervention. The accelerometer autonomously identifies when calibration should occur (during walking), performs the necessary calculations to determine orientation and gravity vectors, and stores the calibration data. This self-service approach maintains high measurement precision while eliminating the complexity and time burden of manual calibration procedures for the user.
Solution Approach 2:
The system changes the operational parameters of the accelerometer by switching between different measurement modes and signal processing techniques depending on the detected state. During walking detection, the system focuses on AC components to identify the gait pattern, then transitions to DC component analysis for gravity vector determination during calibration. These parameter changes enable the system to adapt its measurement approach to the current state, improving accuracy without requiring complex manual procedures.
3Productivity
If calibration is performed during arbitrary activities, then calibration speed increases, but the accuracy of calibration decreases due to motion artifacts
Solution Approach 1:
The system performs preliminary detection of the walking state as a prerequisite condition before initiating calibration. By first identifying the characteristic AC component pattern that signifies walking, the system ensures that calibration only begins when the user is in the appropriate state. This preliminary action filters out inappropriate calibration opportunities (during arbitrary or ambiguous activities) while maintaining efficient calibration execution once the correct state is confirmed, thus preserving both speed and accuracy.
Solution Approach 2:
The system uses feedback from continuous acceleration signal analysis to determine whether the current activity state is suitable for calibration. The feedback mechanism monitors for the specific pattern of AC components associated with walking and only triggers calibration when this pattern is detected. This feedback control ensures that calibration occurs during appropriate activities with minimal motion artifacts while maintaining efficient calibration speed by not delaying the process once the correct state is identified.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables automatic and precise calibration of posture sensors, improving the accuracy of posture data by distinguishing walking states from non-walking activities, thereby enhancing the reliability of cardiac rhythm management devices.
Implementation Method 1
sensing an acceleration signal from a patient using an accelerometer
Implementation Method 2
sensing an acceleration signal from a patient using an accelerometer
Data Source
AI summary
A system and method automatically calibrate a posture sensor, such as by detecting a walking state or a posture change. For example, a three-axis accelerometer can be used to detect a patient's activity or posture. This information can be used to automatically calibrate subsequent posture or acceleration data.