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Amy O'Connell

Publications and source records attributed to Amy O'Connell.

4 recordsLinked to original sources

A Deployable Architecture for Robot-Mediated Tasks (DART): Evaluation in Socially Assistive Robot-Guided Cognitive Behavioral Therapy Exercises

Socially assistive robots (SARs) can support structured health and well-being interventions, but hardware and cost constraints limit interaction complexity and longitudinal real-world deployments. We present DART: Deployable Architecture for Robot-Mediated Tasks, an architecture that extends SARs through a web application and cloud infrastructure, enabling visual content, user input, remote computation, and persistent data storage synergistically with the robot's physical embodiment, speech, and movement. We evaluated DART by instantiating it in an interatively-developed full-stack HRI system for helping university students with elevated generalized anxiety to complete cognitive behavioral therapy (CBT) homework exercises. The resulting system, which used the low-cost open-source Blossom robot platform, was refined and evaluated through a participatory design process and multiple user studies, and finally evaluated in an in-lab study with 103 participants, and then a six-week in-home deployment with four participants. In the in-lab evaluation, participants showed significant within-session reductions in stress, state anxiety, and negative affect, and gave the platform a mean System Usability Scale score of 78.89. In the home deployment, the mean System Usability Scale score was 87.5, with positive qualitative feedback on usability. Participants across both groups identified speech input, visual presentation, and web-robot synchronization as priorities for improvement. These findings validate DART as an effective architecture for extending the capabilities of a low-cost SAR in both in-lab single-session and in real-world longitudinal deployments.

cs.RO

Can I Pet Your Robot? Incorporating Capacitive Touch Sensing into a Soft Socially Assistive Robot Platform

This work presents a method of incorporating low-cost capacitive tactile sensors on a soft socially assistive robot platform. By embedding conductive thread into the robot's crocheted exterior, we formed a set of low-cost, flexible capacitive tactile sensors that do not disrupt the robot's soft, zoomorphic embodiment. We evaluated the sensors' performance through a user study (N=20) and found that the sensors reliably detected user touch events and localized touch inputs to one of three regions on the robot's exterior.

cs.RO

An Interactive Augmented Reality Interface for Personalized Proxemics Modeling

Understanding and respecting personal space preferences is essential for socially assistive robots designed for older adult users. This work introduces and evaluates a novel personalized context-aware method for modeling users' proxemics preferences during human-robot interactions. Using an interactive augmented reality interface, we collected a set of user-preferred distances from the robot and employed an active transfer learning approach to fine-tune a specialized deep learning model. We evaluated this approach through two user studies: 1) a convenience population study (N = 24) to validate the efficacy of the active transfer learning approach; and 2) a user study involving older adults (N = 15) to assess the system's usability. We compared the data collected with the augmented reality interface and with the physical robot to examine the relationship between proxemics preferences for a virtual robot versus a physically embodied robot. We found that fine-tuning significantly improved model performance: on average, the error in testing decreased by 26.97% after fine-tuning. The system was well-received by older adult participants, who provided valuable feedback and suggestions for future work.

cs.RO

Design and Evaluation of a Socially Assistive Robot Schoolwork Companion for College Students with ADHD

College students with ADHD respond positively to simple socially assistive robots (SARs) that monitor attention and provide non-verbal feedback, but studies have been done only in brief in-lab sessions. We present an initial design and evaluation of an in-dorm SAR study companion for college students with ADHD. This work represents the introductory stages of an ongoing user-centered, participatory design process. In a three-week within-subjects user study, university students (N=11) with self-reported symptoms of adult ADHD had a SAR study companion in their dorm room for two weeks and a computer-based system for one week. Toward developing SARs for long-term, in-dorm use, we focus on 1) evaluating the usability and desire for SAR study companions by college students with ADHD and 2) collecting participant feedback about the SAR design and functionality. Participants responded positively to the robot; after one week of regular use, 91% (10 of 11) chose to continue using the robot voluntarily in the second week.

cs.RO