Article

Multiclass arrhythmia classification using multimodal smartwatch photoplethysmography signals collected in real-life settings

2024-12-05

Abstract excerpt

In the early stages of atrial fibrillation (AF), most cases are paroxysmal (pAF), making identification only possible with continuous and prolonged monitoring. With the advent of wearables, smartwatches equipped with photoplethysmographic (PPG) sensors are an ideal approach for continuous monitoring of pAF. There have been numerous studies demonstrating successful capture of pAF events, especially using deep learn...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: e2e55532-6198-5f5e-b35f-41af459c7be3
DOI: 10.1101/2024.12.03.24318445

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Multiclass arrhythmia classification using multimodal smartwatch photoplethysmography signals collected in real-life settingsDOI 10.1101/2024.12.03.24318445Read

Multiclass arrhythmia classification using multimodal smartwatch photoplethysmography signals collected in real-life settingsSemantic proximity Read

Lightweight Deep Learning for Atrial Fibrillation Detection from Single-Lead Wearable ECG: A Systematic Benchmark of Convolutional, Temporal, and State-Space ArchitecturesSemantic proximity Read

BeatAI: BiomEtrics for real-time Atrial Arrhythmia tracking using Transformer Artificial Intelligence from wearables after discharge from cardiac surgerySemantic proximity Read

BeatAI: BiomEtrics for Atrial Arrhythmia Tracking Using Artificial IntelligenceSemantic proximity Read

Your smartphone could act as a pulse-oximeter and as a single-lead ECGSemantic proximity Read

Machine Learning, Deep Learning, and Hybrid Approaches for ECG-Based Cardiac Arrhythmia Detection: Techniques, Challenges, and Future PerspectivesSemantic proximity Read

Exploring the Future of Artificial Intelligence-Enhanced Wearable Electronics for Real-Time Arrhythmia DetectionSemantic proximity Read

Advances in Interpretation of Electrocardiogram by Artificial IntelligenceSemantic proximity Read

Artificial Intelligence Driven Software Systems for Cardiovascular Disease Detection Using Physiological Signals: A Systematic ReviewSemantic proximity Read

CardioFM: A Multimodal Foundation Model for Joint ECG and PPG Representation LearningSemantic proximity Read

Interpretable Photoplethysmography Feature Engineering for Multi-Class Blood Pressure StagingSemantic proximity Read

RAGCBPNet: An Efficient Feature Fusion Framework for Wearable Cuffless Blood Pressure Monitoring and Long-term Validation in Real-world SettingsSemantic proximity Read