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New ARTA framework improves ECG interbeat interval estimation

Researchers have developed ARTA (Artifact-Robust Temporal Alignment), a novel graph-based framework for accurately estimating interbeat intervals from wearable electrocardiogram (ECG) signals. This method addresses challenges posed by motion artifacts, which can corrupt readings from conventional detectors. ARTA combines candidates from multiple ECG detectors, forming a directed acyclic graph where nodes represent potential R-peaks and edges represent physiologically plausible RR intervals. By using a beam-search dynamic programming approach, ARTA selects an optimal path through the graph, effectively suppressing false detections and recovering missed beats, achieving a significantly lower mean absolute error in heart rate estimation compared to baseline methods. AI

RANK_REASON The cluster contains an academic paper detailing a new method for signal processing. [lever_c_demoted from research: ic=1 ai=0.4]

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New ARTA framework improves ECG interbeat interval estimation

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The cluster contains an academic paper detailing a new method for signal processing. [lever_c_demoted from research: ic=1 ai=0.4]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Shovito Barua Soumma, Asiful Arefeen, Hassan Ghasemzadeh ·

    ARTA: Graph Combinatorial Optimization for Robust Interbeat Interval Estimation from Wearable Electrocardiogram Signals

    arXiv:2611.00011v1 Announce Type: cross Abstract: Accurate heart rate (HR) and interbeat interval (IBI) estimation from wearable electrocardiogram (ECG) is essential for continuous physiological monitoring, but motion artifacts can create false QRS-like peaks and obscure true R-p…