Respiration Signal Extraction Using Single Multi-Axial Accelerometer
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Solution Overview
Problem
Existing respiration monitoring systems, particularly in ambulatory settings, face challenges in accurately distinguishing respiration signals from unwanted motion artifacts such as walking or heartbeats, which are not effectively suppressed by filters with fixed frequency responses, and often require multiple accelerometer modules.
Innovation Solution
A method using a single multi-axial accelerometer positioned on the body to generate acceleration signals along different spatial axes, calculating a vector magnitude signal to identify and filter out non-respiratory motion contributions, allowing for the determination of respiration signals without external sensors, employing adaptive noise filtering techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a multi-axial accelerometer is used to measure respiration rate in ambulatory conditions, then respiration monitoring can be performed without obtrusive sensors, but the accelerometer signals are contaminated by unwanted motions such as whole-body movements and heart beat
Solution Approach 1:
The patent segments the accelerometer signal into respiratory component and non-respiratory motion component by analyzing the signal in different frequency ranges. The respiratory signal is isolated by filtering out frequencies associated with heart beat and whole-body movements, thereby separating the desired respiratory information from contaminating motions.
Solution Approach 2:
The patent applies different processing strategies to different frequency components of the accelerometer signal. By identifying that respiratory signals occupy specific frequency ranges distinct from heart beat and movement artifacts, the system applies targeted filtering and signal processing techniques to enhance respiratory signal quality while preserving comfort benefits.
2Measurement precision
If filters with fixed frequency response are used to suppress unwanted motions, then some motion artifacts can be reduced, but non-respiratory motions with frequency components in the same range as respiration cannot be suppressed
Solution Approach 1:
The patent transitions from fixed frequency response filtering to dynamic, adaptive signal processing. The system continuously analyzes the accelerometer signal to identify frequency components associated with respiratory motion versus non-respiratory motion, and dynamically adjusts filtering parameters to suppress unwanted motions while preserving respiratory signals across varying frequency ranges.
Solution Approach 2:
The patent changes the approach from fixed filter parameters to variable parameters that adapt based on the detected motion characteristics. By monitoring the frequency content and amplitude characteristics of the accelerometer signal in real-time, the system modifies filtering parameters to optimally separate respiratory signals from contaminating motions with overlapping frequency components.
3Measurement precision
If an array of four uni-axial accelerometer modules is used to isolate respiratory signals, then high signal-to-noise ratio can be achieved, but the device complexity and number of sensors increase
Solution Approach 1:
The patent combines the functionality of multiple uni-axial accelerometers into a single multi-axial accelerometer device. By integrating three orthogonal sensing axes into one unit, the system achieves equivalent or superior signal isolation capability without requiring separate accelerometer modules, thereby reducing device complexity while maintaining high signal-to-noise ratio for respiratory measurement.
Solution Approach 2:
The patent makes a single multi-axial accelerometer perform multiple functions that previously required separate sensors. The device simultaneously measures respiratory motion, suppresses heart beat interference, and filters whole-body movements by utilizing its multi-axis capability to capture and differentiate various motion components, eliminating the need for an array of specialized uni-axial modules.
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 efficient and comfortable respiration monitoring by accurately isolating respiration signals from unwanted motions, providing reliable respiration rate data even in dynamic conditions without the need for multiple sensors.
Implementation Method 1
A multi-axial accelerometer is a device that measures the acceleration in multiple sensing axes, and is used as an inclinometer to reflect the abdomen or chest movement caused by respiration.
Implementation Method 2
The isolation of a high signal-to-noise ratio respiratory signal is accomplished using an adaptive noise-cancellation algorithm that employs the least means square filtering technique.
Data Source
AI summary
The invention relates to a method and apparatus for determining a respiration of a subject (305) in which, with a single multi-axial accelerometer (310) positioned on a body of the subject (305), accelerometer signals are generated (101) indicative of the acceleration of the subject (305) along different spatial axes, a vector magnitude signal of the acceleration of the subject (305) along the different spatial axes is calculated (102) from the accelerometer signals, a non-respiratory motion contribution to the acceleration along the different spatial axes is identified (103, 203) from the vector magnitude signal, which non-respiratory motion contribution is not caused by the respiration, and a respiration signal indicative of the respiration of the subject is determined (104, 204) by filtering the non-respiratory motion contribution from at least one of the accelerometer signals. In this way a method is provided which determines the respiration of a subject (305) with a single accelerometer (310) in an efficient and, for a patient, comfortable way.