2015
DOI: 10.1001/jamaoto.2015.1249
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Preliminary Study of the Open Quotient in an Ex Vivo Perfused Human Larynx

Abstract: Importance Scientific understanding human voice production to date is a product of indirect investigations including animal models, cadaveric tissue study, or computational modeling. Due to its invasive nature, direct experimentation of human voice production has previously not been possible. The feasibility of an ex-vivo perfused human phonatory model has recently allowed systematic investigation in virtually living human larynges with parametric laryngeal muscle stimulation. Objective In this study, the re… Show more

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Cited by 8 publications
(5 citation statements)
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“…Open Quotient (OQ) [a.u.] 0.37-1.00 (Holmberg et al, 1988;Baken and Orlikoff, 2000) 0.42-1.00 (Mendelsohn et al, 2015) 0.93 0.93…”
Section: Parametermentioning
confidence: 99%
“…Open Quotient (OQ) [a.u.] 0.37-1.00 (Holmberg et al, 1988;Baken and Orlikoff, 2000) 0.42-1.00 (Mendelsohn et al, 2015) 0.93 0.93…”
Section: Parametermentioning
confidence: 99%
“…The differences in the point fields can in part be explained by the fact that the DEGG method is more dependent on a highly stable and simple EGG signal. This is caused by the because there are many factors including interglottal mucus and irregular vibration of vocal cords which affect the relationship between the DEGG and glottal closure [12][13][14][15][16][17]. In comparison, the neural network is better able to identify and predict the position of the opening and closing of the glottis because it is better able to filter the irregularities in the EGG signal from the HSV training.…”
Section: Construction Of the Neural Network Modelmentioning
confidence: 99%
“…The differences in the point fields can in part be explained by the fact that the DEGG method is more dependent on a highly stable and simple EGG signal. This is caused by the because there are many factors including interglottal mucus and irregular vibration of vocal cords which affect the relationship between the DEGG and glottal closure [12][13][14][15][16][17]. In comparison, the neural network is better able to identify and predict the position of the opening and closing of the glottis because it is better able to filter the irregularities in the EGG signal from the HSV training.…”
Section: Construction Of the Neural Network Modelmentioning
confidence: 99%