Juliana Codino
Michigan State University
17 Papers
10 Citations
Juliana Codino is an academic researcher from Michigan State University. The author has contributed to research in topics: Medicine & Voice therapy. The author has an hindex of 3, co-authored 12 publications. Previous affiliations of Juliana Codino include National University of Entre Ríos & University of Buenos Aires.
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Papers
Voice Therapy in the Context of the COVID-19 Pandemic: Guidelines for Clinical Practice.
Adrián Castillo-Allendes,Francisco Contreras-Ruston,Lady Catherine Cantor-Cutiva,Juliana Codino,Marco Guzman,Celina Malebran,Carlos Manzano,Axel Pavez,Thays Vaiano,Fabiana Wilder,Mara Behlau +10 more
TL;DR: A group of 11 experts in voice and swallowing disorders from 5 different countries conducted a consensus recommendation following the American Academy of Otolaryngology-Head and Neck Surgery rules building a clinical guide for SLPs during this pandemic context.
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Reproducibility of Voice Parameters: The Effect of Room Acoustics and Microphones
Pasquale Bottalico,Juliana Codino,Lady Catherine Cantor-Cutiva,Katherine L. Marks,Charles Nudelman,Jean Skeffington,Rahul Shrivastav,Maria Cristina Jackson-Menaldi,Eric Hunter,Adam D. Rubin +9 more
TL;DR: The effect of room acoustics and background noise on voice parameters appears to be stronger than the type of microphone used for the recording, and an appropriate acoustical clinical space may be more important than the quality of the microphone.
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The Art of Caring for the Professional Singer
TL;DR: The otolaryngologist is introduced to the specifics of caring for professional singers, which requires a deeper understanding of the demands, vocabulary, psyche, and economics of the professional singer.
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Voice Biofeedback via Bone Conduction Headphones: Effects on Acoustic Voice Parameters and Self-Reported Vocal Effort in Individuals With Voice Disorders.
TL;DR: In this article , the effects of bone conduction feedback on acoustic voice parameters and vocal effort ratings were examined, and the results showed that the high feedback condition resulted in a statistically significant decrease in the within-participant centered SPL values and mean pitch strength across all participants.
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Automated Electroglottographic Inflection Events Detection. A Pilot Study
TL;DR: A computational algorithm was developed based on the mathematical properties of the EGG signal, which detects and reports events throughout the contact phase, which could allow professionals in the clinical setting to obtain an automatic quantitative and qualitative report of such events present in a voice sample, without having to manually analyze the whole E GG signal.
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