Respiration Rate Estimation via Multi-Stage Artifact Removal
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Solution Overview
Problem
Conventional methods for continuous estimation of respiration rate suffer from poor accuracy due to cardiac and motion artifacts, leading to potential missed critical events and false alarms, as manual measurement is cumbersome and lacks continuous monitoring.
Innovation Solution
A system and method that processes multiple physiological signals using cardiac-artifact removal, polynomial fitting for motion artifacts, spectral decomposition for noise removal, and subspace-based techniques to generate accurate respiration rate estimates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional signal processing methods are used to estimate respiration rate, then the system is simple to implement, but measurement precision deteriorates due to cardiac and motion artifacts
Solution Approach 1:
The patent segments the respiration rate estimation process into multiple distinct signal processing stages: cardiac artifact removal, motion artifact removal, and respiration rate estimation. Each stage addresses specific types of interference separately, allowing for more precise measurement without overwhelming complexity in a single processing step.
Solution Approach 2:
The patent introduces intermediate processed signals as mediators between the raw physiological signals and the final respiration rate estimate. These intermediate signals (e.g., cardiac-artifact-removed signals, motion-artifact-removed signals) serve as transitional representations that progressively refine the data quality before final estimation.
2Reliability
If manual respiration rate measurement is used, then the system complexity is low, but reliability deteriorates due to missed critical events during unmonitored periods
Solution Approach 1:
The patent implements continuous respiration rate monitoring by processing physiological signals continuously rather than through intermittent manual checks. The signal processing pipeline operates continuously to provide uninterrupted estimation, ensuring critical events are captured without gaps in monitoring.
Solution Approach 2:
The system uses the patient's own physiological signals (ECG, impedance, blood pressure) to automatically estimate respiration rate without requiring external manual intervention. The processing system self-manages the continuous monitoring and estimation process, reducing reliance on human operators.
3Measurement precision
If sophisticated signal processing techniques are applied to remove artifacts, then measurement precision improves, but loss of time increases due to computationally intensive processing
Solution Approach 1:
The patent applies preliminary artifact removal processing to the physiological signals before performing respiration rate estimation. By removing cardiac and motion artifacts in advance, the subsequent estimation process works with cleaner data, potentially reducing the computational burden and time required for the final estimation step.
Solution Approach 2:
The patent divides the signal processing into segmented stages that can be performed sequentially or in parallel. This segmentation allows computationally intensive artifact removal to be distributed across multiple processing steps, potentially enabling optimization of processing time through parallel execution or prioritization of critical processing stages.
Data Source
AI summary
A method for determining a respiration rate of a subject, includes receiving a first signal and a second signal, each signal being representative of a physiological parameter of the subject. The method includes removing a cardiac artifact signal from the first signal and the second signal to generate a first processed signal and a second processed signal respectively. The method includes removing a motion artifact signal from the first processed signal and the second processed signal to generate a first periodic signal and the second processed signal respectively. The method further includes removing a residual noise signal from the first periodic signal and the second periodic signal to generate a first noise free signal and the second noise free signal respectively. The method includes generating a combined value from a first value and a second value based on the first noise free signal and the second noise free signal respectively.