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dc.contributor.authorMehta, Daryush D.
dc.contributor.authorVan Stan, Jarrad H.
dc.contributor.authorGhassemi, Marzyeh
dc.contributor.authorGuttag, John V.
dc.contributor.authorCheyne, Harold A.
dc.contributor.authorHillman, Robert E.
dc.contributor.authorZanartu, Matias
dc.contributor.authorEspinoza, Victor M.
dc.contributor.authorCortes, Juan P.
dc.date.accessioned2016-01-04T14:14:23Z
dc.date.available2016-01-04T14:14:23Z
dc.date.issued2015-10
dc.date.submitted2015-06
dc.identifier.issn2296-4185
dc.identifier.urihttp://hdl.handle.net/1721.1/100569
dc.description.abstractMany common voice disorders are chronic or recurring conditions that are likely to result from inefficient and/or abusive patterns of vocal behavior, referred to as vocal hyperfunction. The clinical management of hyperfunctional voice disorders would be greatly enhanced by the ability to monitor and quantify detrimental vocal behaviors during an individual’s activities of daily life. This paper provides an update on ongoing work that uses a miniature accelerometer on the neck surface below the larynx to collect a large set of ambulatory data on patients with hyperfunctional voice disorders (before and after treatment) and matched-control subjects. Three types of analysis approaches are being employed in an effort to identify the best set of measures for differentiating among hyperfunctional and normal patterns of vocal behavior: (1) ambulatory measures of voice use that include vocal dose and voice quality correlates, (2) aerodynamic measures based on glottal airflow estimates extracted from the accelerometer signal using subject-specific vocal system models, and (3) classification based on machine learning and pattern recognition approaches that have been used successfully in analyzing long-term recordings of other physiological signals. Preliminary results demonstrate the potential for ambulatory voice monitoring to improve the diagnosis and treatment of common hyperfunctional voice disorders.en_US
dc.description.sponsorshipVoice Health Institute (National Institute on Deafness and Other Communication Disorders (U.S.) Grant R33 DC011588)en_US
dc.description.sponsorshipVoice Health Institute (National Institute on Deafness and Other Communication Disorders (U.S.) Grant F31 DC014412)en_US
dc.description.sponsorshipMIT International Science and Technology Initiativesen_US
dc.description.sponsorshipComision Nacional de Investigacion Ciencia y Tecnologia (Chile) (Grant FONDECYT 1151077)en_US
dc.description.sponsorshipComision Nacional de Investigacion Ciencia y Tecnologia (Chile) (Grant Basal FB0008)en_US
dc.description.sponsorshipUniversidad Federico Santa Mariaen_US
dc.description.sponsorshipUniversidad de Chileen_US
dc.description.sponsorshipIntel Science & Technology Center for Big Dataen_US
dc.description.sponsorshipNational Library of Medicine (U.S.) (Biomedical Informatics Research Training Grant NIH/NLM 2T15 LM007092-22)en_US
dc.language.isoen_US
dc.publisherFrontiers Research Foundationen_US
dc.relation.isversionofhttp://dx.doi.org/10.3389/fbioe.2015.00155en_US
dc.rightsCreative Commons Attributionen_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_US
dc.sourceFrontiers Research Foundationen_US
dc.titleUsing Ambulatory Voice Monitoring to Investigate Common Voice Disorders: Research Updateen_US
dc.typeArticleen_US
dc.identifier.citationMehta, Daryush D., Jarrad H. Van Stan, Matias Zanartu, Marzyeh Ghassemi, John V. Guttag, Víctor M. Espinoza, Juan P. Cortes, Harold A. Cheyne, and Robert E. Hillman. “Using Ambulatory Voice Monitoring to Investigate Common Voice Disorders: Research Update.” Frontiers in Bioengineering and Biotechnology 3 (October 16, 2015).en_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.mitauthorGhassemi, Marzyehen_US
dc.contributor.mitauthorGuttag, John V.en_US
dc.relation.journalFrontiers in Bioengineering and Biotechnologyen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsMehta, Daryush D.; Van Stan, Jarrad H.; Zanartu, Matias; Ghassemi, Marzyeh; Guttag, John V.; Espinoza, Víctor M.; Cortes, Juan P.; Cheyne, Harold A.; Hillman, Robert E.en_US
dc.identifier.orcidhttps://orcid.org/0000-0001-6349-7251
dc.identifier.orcidhttps://orcid.org/0000-0003-0992-0906
mit.licenseOPEN_ACCESS_POLICYen_US


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