On applying approximate entropy to ECG signals for knowledge discovery on the example of big sensor data

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 7669 LNCS, Issue , 2012, Pages 646-657

  Holzinger, Andreas ^a   Stocker, Christof ^a   Bruschi, Manuel ^a   Auinger, Andreas ^b   Silva, Hugo ^c   Gamboa, Hugo ^d   Fred, Ana ^c  

^a MEDICAL UNIVERSITY OF GRAZ   (Austria)

^b UNIVERSITY OF APPLIED SCIENCES UPPER AUSTRIA   (Austria)

^c INSTITUTO DE TELECOMUNICAÇÕES   (Portugal)

^d UNIVERSIDADE NOVA DE LISBOA   (Portugal)

Author keywords

ApEn; big data; ECG complexity; Information entropy; knowledge discovery

Indexed keywords

APEN; APPROXIMATE ENTROPY; BIG DATUM; COMPLEX DATA; COMPUTATIONAL SCIENCE; ECG DATA; ECG SIGNALS; INFORMATION ENTROPY; LOCAL PROPERTY; SENSOR DATA; STATISTICAL CONCEPTS; STATISTICAL VALIDITY; SUBJECT CLASSIFICATION; WINDOW SIZE;

ARTIFICIAL INTELLIGENCE; DATA MINING;

ELECTROCARDIOGRAPHY;

EID: 84870367323     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-35236-2_64     Document Type: Conference Paper

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