Atrial Fibrillation Detection

9 papers with code • 2 benchmarks • 2 datasets

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Most implemented papers

BayesBeat: Reliable Atrial Fibrillation Detection from Noisy Photoplethysmography Data

sarathismg/bayesbeat 2 Nov 2020

Smartwatches or fitness trackers have garnered a lot of popularity as potential health tracking devices due to their affordable and longitudinal monitoring capabilities.

Anomaly Detection in Time Series with Triadic Motif Fields and Application in Atrial Fibrillation ECG Classification

ydup/Anomaly-Detection-in-Time-Series-with-Triadic-Motif-Fields 9 Dec 2020

Considering the quasi-periodic characteristics of ECG signals, the dynamic features can be extracted from the TMF images with the transfer learning pre-trained convolutional neural network (CNN) models.

Construe: a software solution for the explanation-based interpretation of time series

citiususc/construe 17 Mar 2020

This paper presents a software implementation of a general framework for time series interpretation based on abductive reasoning.

Atrial Fibrillation Detection and ECG Classification based on CNN-BiLSTM

liweiheng818/ECG-Signal-Analysis 12 Nov 2020

It is challenging to visually detect heart disease from the electrocardiographic (ECG) signals.

End-to-End Optimized Arrhythmia Detection Pipeline using Machine Learning for Ultra-Edge Devices

vishaln15/OptimizedArrhythmiaDetection 23 Nov 2021

The feature engineering employed in this research catered to optimizing the resource-efficient classifier used in the proposed pipeline, which was able to outperform the best performing standard ML model by $10^5\times$ in terms of memory footprint with a mere trade-off of 2% classification accuracy.

Investigating Deep Learning Benchmarks for Electrocardiography Signal Processing

DeepPSP/torch_ecg 9 Apr 2022

In recent years, deep learning has witnessed its blossom in the field of Electrocardiography (ECG) processing, outperforming traditional signal processing methods in various tasks, for example, classification, QRS detection, wave delineation.

Efficient ECG-based Atrial Fibrillation Detection via Parameterised Hypercomplex Neural Networks

leibniz-future-lab/hypercomplexecg 27 Oct 2022

Atrial fibrillation (AF) is the most common cardiac arrhythmia and associated with a high risk for serious conditions like stroke.

Contrastive Self-Supervised Learning Based Approach for Patient Similarity: A Case Study on Atrial Fibrillation Detection from PPG Signal

subangkar/simsig 22 Jul 2023

In this paper, we propose a novel contrastive learning based deep learning framework for patient similarity search using physiological signals.