Signal quality indices and data fusion for determining clinical acceptability of electrocardiograms

Physiological Measurement

Volumn 33, Issue 9, 2012, Pages 1419-1433

  Clifford, G D ^a   Behar, J ^a   Li, Q ^a,b   Rezek, I ^a  

^a UNIVERSITY OF OXFORD   (United Kingdom)

^b SHANDONG UNIVERSITY SCHOOL OF MEDICINE   (China)

Author keywords

ECG; machine learning; mHealth; neural networks; signal quality

Indexed keywords

BIOMEDICAL SIGNAL PROCESSING; CLASSIFICATION (OF INFORMATION); DATA FUSION; ELECTROCARDIOGRAPHY; MHEALTH; STATISTICAL TESTS; SUPPORT VECTOR MACHINES;

AUTOMATED ALGORITHMS; CLASSIFIEDS; INTENSIVE CARE; NEURAL-NETWORKS; PHYSIONET; QUALITY DATA; QUALITY INDICES; QUALITY METRICES; SIGNAL QUALITY; TRAINING SETS;

NEURAL NETWORKS;

EID: 84866323283     PISSN: 09673334     EISSN: 13616579     Source Type: Journal    
DOI: 10.1088/0967-3334/33/9/1419     Document Type: Article

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