Objective detection of the central auditory processing disorder: A new machine learning approach

IEEE Transactions on Biomedical Engineering

Volumn 51, Issue 7, 2004, Pages 1147-1155

  Strauss, Daniel J ^a   Delb, Wolfgang ^b   Plinkert, Peter K ^b  

^a Key Numerics   (Germany)

^b SAARLAND UNIVERSITY   (Germany)

Author keywords

Auditory brainstem responses; Binaural interaction; Central auditory processing disorder (CAPD); Frames; Machine learning; Support vector machines; Wavelets

Indexed keywords

BRAIN; COMPUTATIONAL METHODS; DIAGNOSIS; NEUROLOGY;

AUDITORY BRAINSTEM RESPONSES; BINAURAL INTERACTION; SUPPORT VECTOR MACHINES;

BIOMEDICAL ENGINEERING;

ARTICLE; AUDITORY NERVOUS SYSTEM; AUTOMATION; BETA RHYTHM; BINAURAL HEARING; BRAIN STEM; CHILD; DIAGNOSTIC TEST; DIAGNOSTIC VALUE; EVOKED BRAIN STEM AUDITORY RESPONSE; HIGH RISK PATIENT; HUMAN; HUMAN EXPERIMENT; MACHINE; MORPHOLOGY; PERCEPTION DEAFNESS; RELIABILITY;

ARTIFICIAL INTELLIGENCE; DIAGNOSIS, COMPUTER-ASSISTED; ELECTROENCEPHALOGRAPHY; EVOKED POTENTIALS, AUDITORY, BRAIN STEM; HUMANS; LANGUAGE DEVELOPMENT DISORDERS; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SOUND LOCALIZATION;

EID: 2942729638     PISSN: 00189294     EISSN: None     Source Type: Journal    
DOI: 10.1109/TBME.2004.827948     Document Type: Article

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