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dc.contributor.authorCortés, Juan P.
dc.contributor.authorEspinoza, Víctor M.
dc.contributor.authorGhassemi, Marzyeh
dc.contributor.authorMehta, Daryush D.
dc.contributor.authorVan Stan, Jarrad H.
dc.contributor.authorHillman, Robert E.
dc.contributor.authorGuttag, John V
dc.contributor.authorZañartu, Matías
dc.contributor.authorGhassemi, Marzyeh
dc.date.accessioned2020-12-22T19:41:48Z
dc.date.available2020-12-22T19:41:48Z
dc.date.issued2018-12
dc.date.submitted2018-06
dc.identifier.issn1932-6203
dc.identifier.urihttps://hdl.handle.net/1721.1/128897
dc.description.abstractThis is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Phonotraumatic vocal hyperfunction (PVH) is associated with chronic misuse and/or abuse of voice that can result in lesions such as vocal fold nodules. The clinical aerodynamic assessment of vocal function has been recently shown to differentiate between patients with PVH and healthy controls to provide meaningful insight into pathophysiological mechanisms associated with these disorders. However, all current clinical assessment of PVH is incomplete because of its inability to objectively identify the type and extent of detrimental phonatory function that is associated with PVH during daily voice use. The current study sought to address this issue by incorporating, for the first time in a comprehensive ambulatory assessment, glottal airflow parameters estimated from a neck-mounted accelerometer and recorded to a smartphone-based voice monitor. We tested this approach on 48 patients with vocal fold nodules and 48 matched healthy-control subjects who each wore the voice monitor for a week. Seven glottal airflow features were estimated every 50 ms using an impedance-based inverse filtering scheme, and seven high-order summary statistics of each feature were computed every 5 minutes over voiced segments. Based on a univariate hypothesis testing, eight glottal airflow summary statistics were found to be statistically different between patient and healthy-control groups. L 1 -regularized logistic regression for a supervised classification task yielded a mean (standard deviation) area under the ROC curve of 0.82 (0.25) and an accuracy of 0.83 (0.14). These results outperform the state-of-the-art classification for the same classification task and provide a new avenue to improve the assessment and treatment of hyperfunctional voice disorders.en_US
dc.description.sponsorshipNational Institute on Deafness and Other Communication Disorders (Awards R33DC011588 and P50DC015446)en_US
dc.language.isoen
dc.publisherPublic Library of Science (PLoS)en_US
dc.relation.isversionofhttp://dx.doi.org/10.1371/journal.pone.0209017en_US
dc.rightsCreative Commons Attribution 4.0 International licenseen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourcePLoSen_US
dc.titleAmbulatory assessment of phonotraumatic vocal hyperfunction using glottal airflow measures estimated from neck-surface accelerationen_US
dc.typeArticleen_US
dc.identifier.citationCortés, Juan P. et al. "Ambulatory assessment of phonotraumatic vocal hyperfunction using glottal airflow measures estimated from neck-surface acceleration." PLoS ONE 13, 12 (December 2018): e0209017 © 2018 Cortés et al.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.relation.journalPLoS ONEen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2019-05-30T14:32:50Z
dspace.date.submission2019-05-30T14:32:51Z
mit.journal.volume13en_US
mit.journal.issue12en_US


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