Research on Algorithm of Extracting PPG Signal for Detecting Atrial Fibrillation based on Probability Density...

Area of Science:

• Biomedical Engineering
• Signal Processing
• Cardiology

Background:

• Photoplethysmography (PPG) is a non-invasive optical technique to measure blood volume changes.
• Atrial fibrillation (AF) is a common cardiac arrhythmia requiring early detection.
• Existing methods for AF detection from PPG signals can be complex or require specialized equipment.

Purpose of the Study:

• To introduce a novel, accessible method for detecting atrial fibrillation (AF) using smartphone-based photoplethysmography (PPG).
• To validate the efficacy of a probability density function (PDF) and phase space diagram approach for AF identification.

Main Methods:

• PPG signals were acquired from human fingertips using smartphone cameras.
• Pulse wave periods were extracted and reconstructed into a PDF using a phase space diagram algorithm.
• Skewness of the PDF was analyzed to differentiate between normal sinus rhythm (NSR) and AF.

Main Results:

• The PDF reconstruction successfully separated pulse wave periods.
• Distinct PDF skewness patterns were observed between NSR and AF.
• The method demonstrated high viability for smartphone-based AF detection.

Conclusions:

• The proposed PDF and phase space diagram method offers a viable and accessible approach for AF detection using smartphones.
• This technique has the potential to facilitate widespread, opportunistic screening for cardiac arrhythmias.