A new method for sleep apnea classification using wavelets and feedforward neural networks

Artificial Intelligence in Medicine

Volumn 34, Issue 1, 2005, Pages 65-76

  Fontenla Romero, Oscar ^a   Guijarro Berdiñas, Bertha ^a   Alonso Betanzos, Amparo ^a   Moret Bonillo, Vicente ^a  

^a UNIVERSITY OF A CORUÑA   (Spain)

Author keywords

Detection and classification of apneas; Discrete wavelet transformation; Sleep apnea syndrome; Supervised neural networks

Indexed keywords

CLASSIFICATION (OF INFORMATION); ERROR ANALYSIS; FEEDFORWARD NEURAL NETWORKS; FUNCTION EVALUATION; LEARNING SYSTEMS; SUPERVISORY AND EXECUTIVE PROGRAMS; WAVELET TRANSFORMS;

ERROR FUNCTIONS; SUPERVIZED LEARNING; WAVELET TRANSFORMATIONS;

SLEEP RESEARCH;

ACCURACY; ARTIFICIAL NEURAL NETWORK; BAYES THEOREM; BIOTRANSFORMATION; COMPUTER SIMULATION; CONFERENCE PAPER; DISEASE CLASSIFICATION; ENTROPY; HUMAN; LEARNING; POSITIVE FEEDBACK; PRIORITY JOURNAL; SLEEP APNEA SYNDROME; VALIDATION PROCESS;

ALGORITHMS; BAYES THEOREM; HUMANS; NEURAL NETWORKS (COMPUTER); POLYSOMNOGRAPHY; SLEEP APNEA SYNDROMES;

EID: 18844426990     PISSN: 09333657     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.artmed.2004.07.014     Document Type: Conference Paper

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