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Motion Artifacts Removal from Measured Arterial Pulse Signals at Rest: A Generalized SDOF-Model-Based Time-Frequency
1Department of Mechanical and Aerospace Engineering, Old Dominion University, Norfolk, VA 23529, USA.
Sensors (Basel, Switzerland)
|November 13, 2025
Summary
This study introduces a novel time-frequency method to remove motion artifacts from arterial pulse signals. The technique accurately extracts heart rate and respiration parameters, improving signal analysis.
Area of Science:
- Biomedical Engineering
- Signal Processing
- Physiological Monitoring
Background:
- Motion artifacts (MA) significantly degrade arterial pulse signal accuracy.
- Existing methods struggle to differentiate MA from physiological signals like respiration.
- Accurate pulse signal analysis is crucial for diagnosing cardiovascular health.
Purpose of the Study:
- To develop a generalized time-frequency method for robust MA removal from arterial pulse signals.
- To accurately extract physiological parameters like heart rate (HR) and respiration.
- To improve the fidelity of arterial pulse waveform (APW) analysis.
Main Methods:
- A single-degree-of-freedom (SDOF) model representing MA as time-varying system parameters (TVSPs) was employed.
- A generalized SDOF-model-based time-frequency (SDOF-TF) method was developed to analyze signal harmonics.
- The method was validated on pulse signals acquired using tactile and photoplethysmography (PPG) sensors.
Main Results:
- The SDOF-TF method successfully reconstructed pulse signals with MA removal.
- Instantaneous harmonic parameters effectively distinguished MA from respiration effects.
- Instant initial phase provided more accurate respiration parameter extraction than instantaneous frequency.
- APW analysis was improved by using a constant HR, enhancing arterial index derivation.
Conclusions:
- The developed SDOF-TF method offers effective MA removal and accurate physiological parameter extraction.
- The approach enhances the reliability of arterial pulse signal analysis for clinical applications.
- Distinguishing MA from respiration using harmonic analysis is feasible and beneficial.
Keywords:
PPG sensorsarterial pulse signalsarterial pulse waveform (APW)harmonicsheart rate (HR)instant parametersmotion artifacts (MA)respiration modulationrespiration ratesingle-degree-of-freedom (SDOF)tactile sensorstime–frequency analysisMore Related Videos
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