Englander Institute for Precision Medicine

The Bridge2AI-voice application: initial feasibility study of voice data acquisition through mobile health.

TitleThe Bridge2AI-voice application: initial feasibility study of voice data acquisition through mobile health.
Publication TypeJournal Article
Year of Publication2025
AuthorsMoothedan E, Boyer M, Watts S, Abdel-Aty Y, Ghosh S, Rameau A, Sigaras A, Elemento O, Bensoussan Y
Corporate AuthorsBridge2AI-Voice Consortium
JournalFront Digit Health
Volume7
Pagination1514971
Date Published2025
ISSN2673-253X
Abstract

INTRODUCTION: Bridge2AI-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 & METHODS: Participants 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.

RESULTS: Forty-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.

CONCLUSION: Findings 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.

DOI10.3389/fdgth.2025.1514971
Alternate JournalFront Digit Health
PubMed ID40302934
PubMed Central IDPMC12037532

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