A Novel AMARS Technique for Baseline Wander Removal Applied to Photoplethysmogram

Area of Science:

• Biomedical Engineering
• Signal Processing
• Digital Filtering

Background:

• Conventional frequency selective filters inadequately address baseline wander (BW) in continuous signals.
• BW in biosignals like photoplethysmograms can obscure physiological information.
• Existing methods often leave residual BW, impacting signal integrity.

Purpose of the Study:

• To introduce and evaluate a novel digital filter, AMARS (aligning minima of alternating random signal), for effective BW removal.
• To assess the performance of AMARS in preprocessing photoplethysmograms.
• To demonstrate the repeatability and utility of AMARS in biosignal processing.

Main Methods:

• Derivation of the AMARS digital filter using trigonometric principles.
• Configuration of various filters and techniques for preprocessing photoplethysmogram signals.
• Application and testing of AMARS on ear and finger photoplethysmograms.

Main Results:

• AMARS successfully removed baseline wander from photoplethysmogram signals.
• The filter enabled the assembly of similarly aligned trends in processed signals.
• BW removal using AMARS was found to be repeatable on different sensor types.

Conclusions:

• AMARS is an effective tool for removing baseline wander from photoplethysmograms and other biosignals.
• Consistent removal of BW by AMARS helps retain essential structural, functional, and physiological properties of signals.
• The AMARS filter shows potential applicability to a broader range of biological and continuous signals affected by volatility.