Real-time sleep apnea detection by classifier combination

IEEE Transactions on Information Technology in Biomedicine

Volumn 16, Issue 3, 2012, Pages 469-477

  Xie, Baile ^a   Minn, Hlaing ^a  

^a The University of Texas at Dallas   (United States)

Author keywords

Classifier combination; electrocardiograph (ECG); feature selection; hypopnea; machine learning; saturation of peripheral oxygen (SpO 2); sleep apnea

Indexed keywords

CLASSIFICATION PERFORMANCE; CLASSIFIER COMBINATION; DECISION STUMPS; DIAGNOSTIC ABILITY; ELECTROCARDIOGRAPH (ECG); HYPOPNEA; INDIVIDUAL CLASSIFIERS; POLYSOMNOGRAPHY; SLEEP APNEA; SLEEP APNEA DETECTION;

ADAPTIVE BOOSTING; DECISION TABLES; FEATURE EXTRACTION; LEARNING SYSTEMS; OXYGEN;

ELECTROCARDIOGRAPHY;

ADULT; AGED; ARTICLE; ARTIFICIAL INTELLIGENCE; COMPUTER SYSTEM; ELECTROCARDIOGRAPHY; FEMALE; HUMAN; MALE; METHODOLOGY; MIDDLE AGED; MONITORING; OXIMETRY; PATHOPHYSIOLOGY; SIGNAL PROCESSING; SLEEP APNEA SYNDROME;

ADULT; AGED; ARTIFICIAL INTELLIGENCE; COMPUTER SYSTEMS; ELECTROCARDIOGRAPHY; FEMALE; HUMANS; MALE; MIDDLE AGED; MONITORING, PHYSIOLOGIC; OXIMETRY; SIGNAL PROCESSING, COMPUTER-ASSISTED; SLEEP APNEA SYNDROMES;

EID: 84860666399     PISSN: 10897771     EISSN: None     Source Type: Journal    
DOI: 10.1109/TITB.2012.2188299     Document Type: Article

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