Document Type

Article

Publication Date

2026

DOI

10.3390/s26020416

Publication Title

Sensors

Volume

26

Issue

2

Pages

416

Abstract

At-rest PPG signals have been explored for detecting atrial fibrillation (AF), yet current signal-processing techniques do not achieve perfect accuracy even under low-motion artifact (MA) conditions. This study evaluates the effectiveness of a single-degree-of-freedom time–frequency (SDOF-TF) method in analyzing at-rest PPG signals for AF detection. The method leverages the influence of MA on the instant parameters of each harmonic, which is identified using an SDOF model in which the tissue–contact–sensor (TCS) stack is treated as an SDOF system. In this model, MA induces baseline drift and time-varying system parameters. The SDOF-TF method enables the quantification and removal of MA and noise, allowing for the accurate extraction of the arterial pulse waveform, heart rate (HR), heart rate variability (HRV), respiration rate (RR), and respiration modulation (RM). Using data from the MIMIC PERform AF dataset, the method achieved 100% accuracy in distinguishing AF from non-AF cases based on three features: (1) RM, (2) HRV derived from instant frequency and instant initial phase, and (3) standard deviation of HR across harmonics. Compared with non-AF, the RM for each harmonic was increased by AF. RM exhibited an increasing trend with harmonic order in non-AF subjects, whereas this trend was diminished in AF subjects.

Rights

© 2026 by the Authors.

This article is an open access article under the terms and conditions of the Creative Commons Attribution 4.0 International (CC BY 4.0) License.

Data Availability

Article states: "The data in the MIMIC PERform AF Dataset [21] are used."

Original Publication Citation

Hasan, M., & Hao, Z. (2026). Atrial fibrillation detection from at-rest PPG signals using an SDOF-TF method. Sensors, 26(2), Article 416. https://doi.org/10.3390/s26020416 

ORCID

0009-0006-7544-5938 (Hasan), 0000-0003-2024-1947 (Hao)

Download

Share

COinS