Detection of cough signals in continuous audio recordings using hidden Markov models

IEEE Transactions on Biomedical Engineering

Volumn 53, Issue 6, 2006, Pages 1078-1083

  Matos, Sergio ^a,b   Birring, Surinder S ^a,c,d   Pavord, Ian D ^a,b,c   Evans, David H ^a,b,e,f,g,h  

^a UNIVERSITY HOSPITALS OF LEICESTER NHS TRUST   (United Kingdom)

^b UNIVERSITY OF LEICESTER   (United Kingdom)

^c GLENFIELD HOSPITAL   (United Kingdom)

^d BRITISH THORACIC SOCIETY   (United Kingdom)

^e Institute of Physics   (United Kingdom)

^f Institute of Physics and Engineering in Medicine   (United Kingdom)

^g Institute of Physics ^*  (United Kingdom)

^h European Federation of Societies for Ultrasound in Medicine and Biology   (United Kingdom)

Author keywords

Automatic detection; Cough counts; Cough monitor; Hidden Markov models

Indexed keywords

AUTOMATIC DETECTION; COUGH COUNTS; COUGH MONITOR; HIDDEN MARKOV MODELS;

DATA RECORDING; MARKOV PROCESSES; MATHEMATICAL MODELS; PATIENT MONITORING; PATIENT TREATMENT; SOUND RECORDING;

DISEASE CONTROL;

AMBULATORY MONITORING; ARTICLE; AUDIO RECORDING; CLINICAL ARTICLE; CONTROLLED STUDY; COUGHING; DATA ANALYSIS; HUMAN; MATHEMATICAL ANALYSIS; MATHEMATICAL MODEL; MICROPHONE; PROBABILITY; RECORDER; SIGNAL PROCESSING; SOUND DETECTION;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; AUSCULTATION; COUGH; DIAGNOSIS, COMPUTER-ASSISTED; HUMANS; MARKOV CHAINS; MONITORING, AMBULATORY; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SOUND SPECTROGRAPHY;

EID: 33744988731     PISSN: 00189294     EISSN: None     Source Type: Journal    
DOI: 10.1109/TBME.2006.873548     Document Type: Article

References (9)

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