More Like this

1. Using Socially Assistive Robot Feedback to Reinforce Infant Leg Movement Acceleration

   Deng, W; Sargent, B; Bradley, NS; Klein, L; Rosales, M; Pulido, JC; Matarić, MJ; Smith, BA. (August 2021, 30th IEEE International Conference on Robot & Human Interactive Communication (RO-MAN))

   null (Ed.)
2. Socially Assistive Infant-Robot Interaction: Using Robots to Encourage Infant Leg-Motion Training

   https://doi.org/10.1109/MRA.2019.2905644  

   Fitter, Naomi; Funke, Rebecca; Pulido Pascual, Jose Carlos; Eisenman, Lauren E.; Deng, Weiyang; Rosales, Marcelo R.; Bradley, Nina; Sargent, Barbara; Smith, Beth; Mataric, Maja (January 2019, IEEE Robotics & Automation Magazine)
3. Surprise! Predicting Infant Visual Attention in a Socially Assistive Robot Contingent Learning Paradigm

   https://doi.org/10.1109/RO-MAN46459.2019.8956385  

   Klein, Lauren; Itti, Laurent; Smith, Beth A.; Rosales, Marcelo; Nikolaidis, Stefanos; Matarić; Maja J. (October 2019, Ro-Man 2019- International Conference on Robot and Human Interactive Communication)

   Early intervention to address developmental disability in infants has the potential to promote improved outcomes in neurodevelopmental structure and function [1]. Researchers are starting to explore Socially Assistive Robotics (SAR) as a tool for delivering early interventions that are synergistic with and enhance human-administered therapy. For SAR to be effective, the robot must be able to consistently attract the attention of the infant in order to engage the infant in a desired activity. This work presents the analysis of eye gaze tracking data from five 6-8 month old infants interacting with a Nao robot that kicked its leg as a contingent reward for infant leg movement. We evaluate a Bayesian model of lowlevel surprise on video data from the infants’ head-mounted camera and on the timing of robot behaviors as a predictor of infant visual attention. The results demonstrate that over 67% of infant gaze locations were in areas the model evaluated to be more surprising than average. We also present an initial exploration using surprise to predict the extent to which the robot attracts infant visual attention during specific intervals in the study. This work is the first to validate the surprise model on infants; our results indicate the potential for using surprise to inform robot behaviors that attract infant attention during SAR interactions. 

   more » « less
4. Roll for Robot: A Tabletop Role-Playing Game for Designing Socially Assistive Robots for Depression Management

   https://doi.org/10.1007/978-981-96-3522-1_23  

   Collins, Sawyer; Henkel, Kenna Baugus; Henkel, Zachary; Śabanović, Selma (January 2025, Springer Nature Singapore)
5. The Ins and Outs of Socially Assistive Robots: Sensors and Behaviors of a Therapeutic Robot for Depression Management

   Collins, S; Henkel, Z; Baugus_Henkel, K; Bennett, CC; Stanojević, Č; Piatt, JA; Bethel, CL; Šabanović, S (October 2024, Springer Verlag)

   Using socially assistive robots (SARs) as specialized companions for those living with depression to manage symptoms provides a unique opportunity for exploration of robotic systems as comfort objects. Moreover, the robotic components allow for specialized behavioral responses to particular stimuli, as preferred by the user. We have conducted semi-structured interviews with 10 participants about the zoomorphic robot’s TherabotTM desired behaviors and focus groups with five additional participants regarding the preferred sensors within the TherabotTM system. In this paper, using the data from interviews and focus groups, we explore SAR input and output for depression management. While participants overall expected the robot to respond in much similar ways as a well-trained service animal, they expressed interest in the robot understanding unique information about the environment and the user, such as when the user might need interaction. 

   more » « less