Article

From Motion Artifacts to Clinical Insight: Multi-Modal Deep Learning for Robust Arrhythmia Screening in Ambulatory ECG Monitoring

2026-01-09

Abstract excerpt

Motion artifacts corruptwearable ECG signals and generate false alarms of arrhythmias, limiting the clinical adoption of continuous cardiacmonitoring. We present a dual-streamdeep learning framework formotionrobust binary arrhythmia classification throughmulti-modal sensor fusion andmulti-SNR training. ResNet-18 processes ECG spectrograms,while CNN-BiLSTMencodes accelerometermotion patterns; attention-gated fusion...

Topics

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

Identifiers and source

Literature Corpus work: 15819d56-31a8-569b-8ee1-b0f4fb9a7fe7
DOI: 10.20944/preprints202601.0739.v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

From Motion Artifacts to Clinical Insight: Multi-Modal Deep Learning for Robust Arrhythmia Screening in Ambulatory ECG MonitoringDOI 10.20944/preprints202601.0739.v1Read

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

Wavelet-Domain Multi-Representation and Ensemble Learning for Automated ECG AnalysisSemantic proximity Read

A Coordinated Adaptive Multiscale Enhanced Spatio-Temporal Fusion Network for Multi-lead Electrocardiogram Arrhythmia DetectionSemantic proximity Read

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

A Hybrid Model Combining 1D-CNN and BERT for Intelligent ECG Arrhythmia ClassificationSemantic proximity Read

Automated Detection of Poor-Quality Digital Heart Sound Recordings Using Noise InjectionSemantic proximity Read

Advances in Interpretation of Electrocardiogram by Artificial IntelligenceSemantic proximity Read

A Fast, Lightweight, and Generalizable Deep Neural Network for the Detection of Atrial FibrillationSemantic proximity Read

High-Reliability Signal Quality Validation for Biosignals Using Sensor Fusion and Software IndicesSemantic proximity Read

Ensemble Post-hoc Explainable AI for Multilead ECG: Identifying Disease-Relevant Features in Single-Lead InterpretationsSemantic proximity Read