Frontiers in Digital Health (Apr 2025)
The Bridge2AI-voice application: initial feasibility study of voice data acquisition through mobile health
- Elijah Moothedan,
- Micah Boyer,
- Stephanie Watts,
- Yassmeen Abdel-Aty,
- Satrajit Ghosh,
- Anaïs Rameau,
- Alexandros Sigaras,
- Olivier Elemento,
- Bridge2AI-Voice Consortium,
- Yael Bensoussan,
- Yael Bensoussan,
- Olivier Elemento,
- Anais Rameau,
- Alexandros Sigaras,
- Satrajit Ghosh,
- Maria Powell,
- Vardit Ravitsky,
- Jean Christophe Belisle-Pipon,
- David Dorr,
- Phillip Payne,
- Alistair Johnson,
- Ruth Bahr,
- Donald Bolser,
- Frank Rudzicz,
- Jordan Lerner-Ellis,
- Kathy Jenkins,
- Shaheen Awan,
- Micah Boyer,
- William Hersh,
- Andrea Krussel,
- Steven Bedrick,
- Toufeeq Ahmed Syed,
- Jamie Toghranegar,
- James Anibal,
- Duncan Sutherland,
- Enrique Diaz-Ocampo,
- Elizabeth Silberhoz,
- John Costello,
- Alexander Gelbard,
- Kimberly Vinson,
- Tempestt Neal,
- Lochana Jayachandran,
- Evan Ng,
- Selina Casalino,
- Yassmeen Abdel-Aty,
- Karim Hanna,
- Theresa Zesiewicz,
- Elijah Moothedan,
- Emily Evangelista,
- Samantha Salvi Cruz,
- Robin Zhao,
- Mohamed Ebraheem,
- Karlee Newberry,
- Iris De Santiago,
- Ellie Eiseman,
- JM Rahman,
- Stacy Jo,
- Anna Goldenberg
Affiliations
- Elijah Moothedan
- Charles E. Schmidt College of Medicine, Florida Atlantic University, Boca Raton, FL, United States
- Micah Boyer
- USF Health Voice Center, Department of Otolaryngology-Head & Neck Surgery, University of South Florida, Tampa, FL, United States
- Stephanie Watts
- USF Health Voice Center, Department of Otolaryngology-Head & Neck Surgery, University of South Florida, Tampa, FL, United States
- Yassmeen Abdel-Aty
- USF Health Voice Center, Department of Otolaryngology-Head & Neck Surgery, University of South Florida, Tampa, FL, United States
- Satrajit Ghosh
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, United States
- Anaïs Rameau
- Sean Parker Institute for the Voice, Department of Otolaryngology-Head & Neck Surgery, Weill Cornell Medical College, New York, NY, United States
- Alexandros Sigaras
- Englander Institute for Precision Medicine, Weil Cornell Medical College, New York, NY, United States
- Olivier Elemento
- Englander Institute for Precision Medicine, Weil Cornell Medical College, New York, NY, United States
- Bridge2AI-Voice Consortium
- Yael Bensoussan
- USF Health Voice Center, Department of Otolaryngology-Head & Neck Surgery, University of South Florida, Tampa, FL, United States
- Yael Bensoussan
- Olivier Elemento
- Anais Rameau
- Alexandros Sigaras
- Satrajit Ghosh
- Maria Powell
- Vardit Ravitsky
- Jean Christophe Belisle-Pipon
- David Dorr
- Phillip Payne
- Alistair Johnson
- Ruth Bahr
- Donald Bolser
- Frank Rudzicz
- Jordan Lerner-Ellis
- Kathy Jenkins
- Shaheen Awan
- Micah Boyer
- William Hersh
- Andrea Krussel
- Steven Bedrick
- Toufeeq Ahmed Syed
- Jamie Toghranegar
- James Anibal
- Duncan Sutherland
- Enrique Diaz-Ocampo
- Elizabeth Silberhoz
- John Costello
- Alexander Gelbard
- Kimberly Vinson
- Tempestt Neal
- Lochana Jayachandran
- Evan Ng
- Selina Casalino
- Yassmeen Abdel-Aty
- Karim Hanna
- Theresa Zesiewicz
- Elijah Moothedan
- Emily Evangelista
- Samantha Salvi Cruz
- Robin Zhao
- Mohamed Ebraheem
- Karlee Newberry
- Iris De Santiago
- Ellie Eiseman
- JM Rahman
- Stacy Jo
- Anna Goldenberg
- DOI
- https://doi.org/10.3389/fdgth.2025.1514971
- Journal volume & issue
-
Vol. 7
Abstract
IntroductionBridge2AI-Voice, a collaborative multi-institutional consortium, aims to generate a large-scale, ethically sourced voice, speech, and cough database linked to health metadata in order to support AI-driven research. A novel smartphone application, the Bridge2AI-Voice app, was created to collect standardized recordings of acoustic tasks, validated patient questionnaires, and validated patient reported outcomes. Before broad data collection, a feasibility study was undertaken to assess the viability of the app in a clinical setting through task performance metrics and participant feedback.Materials & methodsParticipants were recruited from a tertiary academic voice center. Participants were instructed to complete a series of tasks through the application on an iPad. The Plan-Do-Study-Act model for quality improvement was implemented. Data collected included demographics and task metrics including time of completion, successful task/recording completion, and need for assistance. Participant feedback was measured by a qualitative interview adapted from the Mobile App Rating Scale.ResultsForty-seven participants were enrolled (61% female, 92% reported primary language of English, mean age of 58.3 years). All owned smart devices, with 49% using mobile health apps. Overall task completion rate was 68%, with acoustic tasks successfully recorded in 41% of cases. Participants requested assistance in 41% of successfully completed tasks, with challenges mainly related to design and instruction understandability. Interview responses reflected favorable perception of voice-screening apps and their features.ConclusionFindings suggest that the Bridge2AI-Voice application is a promising tool for voice data acquisition in a clinical setting. However, development of improved User Interface/User Experience and broader, diverse feasibility studies are needed for a usable tool.Level of evidence: 3.
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