ORIGINAL RESEARCH article
Front. Robot. AI
Sec. Biomedical Robotics
Volume 12 - 2025 | doi: 10.3389/frobt.2025.1646880
This article is part of the Research TopicInteractive Robots for Healthcare and ParticipationView all 6 articles
Designing Socially Assistive Robots for Clinical Practice: Insights from an Asynchronous Remote Community of Speech-Language Pathologists
Provisionally accepted
- 1University of Nevada, Reno, Reno, United States
- 2University of Nevada Reno College of Education & Human Development, Reno, United States
- 3University at Buffalo, Buffalo, United States
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Socially Assistive Robots (SARs) present promising opportunities to augment speech-language therapy, specifically when considering high caseloads and enhancing engagement for children with communication disorders. However, the majority of existing SAR implementations often lack alignment with clinician practices and can overlook expressive strategies that are central to speech-language pathology interventions. This study investigates the perspectives of practicing speech-language pathologists (SLPs) on the role, design, and integration of SARs through a four-week Asynchronous Remote Community (ARC) study. Thirteen licensed SLPs participated in weekly activities and discussions, contributing reflective insights on emotional expression, domain-specific needs, and potential roles for SARs in therapy. By using an ARC format, this study supported a distributed and flexible model of engagement where participants contributed iteratively and asynchronously, creating a space for deeper reflection and discussion across varying work settings. This structure enabled a co-design framework that facilitated longitudinal insights, peer dialogue, and participant driven design requirements. Through a thematic analysis we identified five design considerations: (1) the need for expressive and multi-modal communication,(2) customization of behavior to accommodate sensory and developmental profiles, (3) role adaptability across therapy contexts, (4) ethical concerns regarding overuse and replacement fears, (5) opportunities for data tracking and personalization. Our findings contribute a set of clinician-informed design implications for SAR development and demonstrates the viability of ARC as a co-design framework in mental health related human-robot interaction. This bridges the gap between robotic capabilities and clinical expectations, fostering the development of socially intelligent, adaptable, and ethically grounded SARs for speech-language interventions.
Keywords: socially assistive robots, Speech-Language Pathology, co-design, Expression, Asynchronous Remote Community
Received: 14 Jun 2025; Accepted: 15 Aug 2025.
Copyright: © 2025 Oliva, Olszewski, Sadeghi, Dantu and Feil-Seifer. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Denielle Oliva, denielleo@unr.edu
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