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dc.contributor.authorSchlittenlacher, Josef
dc.contributor.authorTurner, Richard
dc.contributor.authorMoore, Brian
dc.date.accessioned2018-10-10T10:44:43Z
dc.date.available2018-10-10T10:44:43Z
dc.date.issued2018-01
dc.identifier.issn2331-2165
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/283520
dc.description.abstractThis article describes a Bayesian active-learning procedure for estimating the edge frequency, fe, of a dead region, that is, a region in the cochlea with no or very few functioning inner hair cells or neurons. The method is based on the psychophysical tuning curve (PTC) but estimates the shape of the PTC from the parameters of a hearing model, namely fe, and degree of outer hair cell loss. It chooses the masker frequency and level for each trial to be highly informative about the model parameters in the context of previous data. The procedure was tested using 14 ears from eight subjects previously diagnosed with high-frequency dead regions. The estimates of fe agreed well with estimates obtained using "Fast PTCs" or more extensive measurements from an earlier study. On average, 33 trials were needed for the estimate of fe to fall and stay within 0.3 Cams of the final "true" value on the equivalent rectangular bandwidth-number scale. The time needed to obtain a reliable estimate was 5 to 8 min. This is comparable to the time required for Fast PTCs and short enough to be used when fitting a hearing aid. Compared with Fast PTCs, the new method has the advantage of using yes-no judgments rather than continuous Békésy tracking. This allows the slope of a subject's psychometric function and thus the reliability of his or her responses to be estimated, which in turn allows the test duration to be adjusted so as to achieve a given accuracy.
dc.format.mediumPrint
dc.languageeng
dc.publisherSAGE Publications
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectCochlea
dc.subjectHumans
dc.subjectHearing Tests
dc.subjectAudiometry
dc.subjectBayes Theorem
dc.subjectReproducibility of Results
dc.subjectAuditory Threshold
dc.subjectPerceptual Masking
dc.subjectHearing
dc.subjectTime Factors
dc.subjectAged
dc.subjectAged, 80 and over
dc.subjectMiddle Aged
dc.subjectFemale
dc.subjectMale
dc.subjectHair Cells, Auditory
dc.titleA Hearing-Model-Based Active-Learning Test for the Determination of Dead Regions.
dc.typeArticle
prism.publicationDate2018
prism.publicationNameTrends Hear
prism.startingPage2331216518788215
prism.volume22
dc.identifier.doi10.17863/CAM.30883
dcterms.dateAccepted2018-06-14
rioxxterms.versionofrecord10.1177/2331216518788215
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserved
rioxxterms.licenseref.startdate2018-01
dc.contributor.orcidMoore, Brian [0000-0001-7071-0671]
dc.identifier.eissn2331-2165
rioxxterms.typeJournal Article/Review
pubs.funder-project-idEngineering and Physical Sciences Research Council (EP/M026957/1)
cam.issuedOnline2018-07-19


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Attribution 4.0 International
Except where otherwise noted, this item's licence is described as Attribution 4.0 International