Exercising with a humanoid companion is more effective than exercising alone

Schneider, Sebastian; Kummert, Franz

doi:10.1109/humanoids.2016.7803321

Cited by 16 publications

(18 citation statements)

References 19 publications

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“…Users' perceptions of their interaction with the robot thus improved, relative to their initial expectations. Schneider and Kümmert [66] also investigate the differences in motivation created by a robot that solely instructs users (instructor role) and one that exercises alongside the user (companion role); people appear more motivated by the robot companion role. Finally, in a robot coaching scenario [33], an elderly user study cites engagement and enjoyment while exercising but also reveals some difficulties, such as hearing instructions, focusing on the physical aspects of the robot while ignoring verbal instructions, and confusion associated with performing sequences of gestures.…”

Section: Robotic Coachesmentioning

confidence: 99%

Robotic Versus Human Coaches for Active Aging: An Automated Social Presence Perspective

Čaić

Avelino

Mahr

et al. 2019

Int J of Soc Robotics

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This empirical study compares elderly people's social perception of human versus robotic coaches in the context of an active and healthy aging program. In evaluating hedonic and utilitarian value perceptions of exergames (i.e., video games integrating physical activity), we consider elderly people's judgments of the warmth and competence (i.e., social cognition) of their assigned coach (human vs. robot). The field experiments involve 58 elderly participants in the real-life context. Leveraging a mixed-method approach that combines quantitative and qualitative data, we show that (1) socially assistive robots activate feelings of (automated) social presence (2) human coaches score higher on perceived warmth and competence relative to robotic coaches, and (3) social cognition affects elderly people's experience (i.e., emotional and cognitive reactions and behavioral intentions) with respect to exergames. These findings can inform future developments and design of social robots and systems for their smoother inclusion into elderly people's social networks. In particular, we recommend that socially assistive robots take complementary roles (e.g., motivational coach) and assist human caregivers in improving elderly people's physical and psychosocial well-being.

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Section: Robotic Coachesmentioning

confidence: 99%

Robotic Versus Human Coaches for Active Aging: An Automated Social Presence Perspective

Čaić

Avelino

Mahr

et al. 2019

Int J of Soc Robotics

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“…We therefore hypothesized that if participants believed that their partner were an humanoid robot such as the iCub, the perception of the partner's apparently effortful contribution could elicit a sense of commitment to the interaction. This hypothesis is also supported by research showing that participants were more motivated while performing an exercising task with an embodied robot partner than with a virtual partner (Fasola & Matarić, 2013), and by research indicating that participants were more motivated when exercising jointly with a robot partner than when exercising individually according to the instructions of a robot teacher (Schneider & Kümmert, 2016).…”

Section: Introductionmentioning

confidence: 78%

The perception of a robot partner’s effort elicits a sense of commitment to human-robot interaction

Székely

Powell

Vannucci

et al. 2019

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Previous research has shown that the perception that one’s partner is investing effort in a joint action can generate a sense of commitment, leading participants to persist longer despite increasing boredom. The current research extends this finding to human-robot interaction. We implemented a 2-player version of the classic snake game which became increasingly boring over the course of each round, and operationalized commitment in terms of how long participants persisted before pressing a ‘finish’ button to conclude each round. Participants were informed that they would be linked via internet with their partner, a humanoid robot. Our results reveal that participants persisted longer when they perceived what they believed to be cues of their robot partner’s effortful contribution to the joint action. This provides evidence that the perception of a robot partner’s effort can elicit a sense of commitment to human-robot interaction.

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“…While several studies showed the potential of virtual agents [10,11] and physical robots [12] to enhance engagement and learning in health, physical activity or social contexts, Fasola et al [13] showed better assessment by the elderly subjects of the physical robot coach compared to virtual systems. Robots for coaching physical exercises have been recently presented [14,15,16]. These approaches employed robots with few degrees of freedom that facilitates the imitation process.…”

Section: Related Workmentioning

confidence: 99%

Generating Shared Latent Variables for Robots to Imitate Human Movements and Understand Their Physical Limitations

Devanne

Nguyen

2019

Lecture Notes in Computer Science

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Assistive robotics and particularly robot coaches may be very helpful for rehabilitation healthcare. In this context, we propose a method based on Gaussian Process Latent Variable Model (GP-LVM) to transfer knowledge between a physiotherapist, a robot coach and a patient. Our model is able to map visual human body features to robot data in order to facilitate the robot learning and imitation. In addition, we propose to extend the model to adapt robots' understanding to patient's physical limitations during the assessment of rehabilitation exercises. Experimental evaluation demonstrates promising results for both robot imitation and model adaptation according to the patients' limitations.

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Exercising with a humanoid companion is more effective than exercising alone

Cited by 16 publications

References 19 publications

Robotic Versus Human Coaches for Active Aging: An Automated Social Presence Perspective

Robotic Versus Human Coaches for Active Aging: An Automated Social Presence Perspective

The perception of a robot partner’s effort elicits a sense of commitment to human-robot interaction

Generating Shared Latent Variables for Robots to Imitate Human Movements and Understand Their Physical Limitations

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