Comparing the Effects of Social Robots and Virtual Agents on Exercising Motivation

Schneider S, Kummert F. Comparing the Effects of Social Robots and Virtual Agents on Exercising Motivation. In: Social Robotics. Lecture Notes in Computer Science. Vol 11357. Cham: Springer International Publishing; 2018: 451-461

Socially Assistive Robots for Exercising Scenarios. Studies on group effects, feedback, embodiment and adaption

Schneider S. Socially Assistive Robots for Exercising Scenarios. Studies on group effects, feedback, embodiment and adaption. Bielefeld: Universität Bielefeld; 2019.Even though positive effects of being physically active are commonly known, only a few parts of the world population are sufficiently ac- tive. The World Health Organization (WHO) states that this problem affects 31% of the adult’s world population and 80% of the adolescent population. Appropriate levels of physical activity (PA) are essential to prevent obesity in childhood and to keep a Quality of Life (QOL) in old age but are also essential to prevent other Noncommunicable Diseases (NCDs). Thus, physical inactivity is growing into a severe problem globally, and there is a growing need to motivate people to become more physically active during their lifetime. One primary cause that raises PA levels is having a peer or help from professionals. However, having assistance is not possible in every situation. It might be challenging to find and schedule with a partner or to commute to other places. Roboticist introduced Socially Assistive Robot (SAR) as an assistive tool for exercising, cognitive or rehabilitation tasks. This thesis explores SAR in the context of exercising along four features that have been partly targeted but not yet thoroughly investigated. These features are a) the social role of the robot, b) encouragement c) embodiment and d) adaptation. First, this thesis looks at the mo- tivational effects of exercising with SAR concerning features a) - c). Second, this thesis questions how a system can adapt to the user, and whether adaptivity or adaptability is enough to close the gap between user needs and system behavior. I conducted studies that test the dif- ferent features by assessing subjective ratings of the robot as well as measurable motivational variables (e.g., time spent exercising with the robot) in a bodyweight workout scenario. The results show that features a) - c) have a positive influence on user’s exercising time. Additionally, users perceive a robot compan- ion as more likable than a robot instructor or a human partner. Fur- thermore, an adaptive robot increases the associated competence and quality of relationship compared to an adaptable robot. However, the results also show that the robot does not always have to exercise along with the user. In situations where it is not possible, the robot could also only give encouraging feedback. This thesis backs up earlier find- ings of using SAR by replicating motivational group exercising ef- fects found in Human-Human Interaction (HHI). Thus, the evidence that SARs are a suitable tool for rehabilitative interventions increases which may convince health experts to consider SAR as a useful thera- peutic tool. Nevertheless, this thesis evaluated the effects only during short-term interactions. Thus, proving that the found effects are long- lasting is essential for future studies

Exercising with a Humanoid Companion is More Effective than Exercising Alone

Schneider S, Kummert F. Exercising with a Humanoid Companion is More Effective than Exercising Alone. In: Humanoids 2016 : IEEE-RAS International Conference on Humanoid Robots. Piscataway, NJ: IEEE; 2016: 495-501

Motivational Effects of Acknowledging Feedback from a Socially Assistive Robot

Schneider S, Kummert F. Motivational Effects of Acknowledging Feedback from a Socially Assistive Robot. In: Agah A, Cabibihan J-J, Howard AM, Salichs MA, He H, eds. Social Robotics. ICSR 2016. Proceedings of the Eighth International Conference on Social Robotics. Lecture Notes in Computer Science. Vol 9979. Cham: Springer; 2016: 870-879

Exploring Embodiment and Dueling Bandits for Preference Adaptation in Human-Robot Interaction

Schneider S, Kummert F. Exploring Embodiment and Dueling Bandits for Preference Adaptation in Human-Robot Interaction. In: Human-robot collaboration and human assistance for an improved quality of life : IEEE RO-MAN 2017 : 26th IEEE International Symposium on Robot and Human Ineractive Communicationon. Piscataway, NJ: IEEE; 2017: 1325-1331

Between Fear and Trust: Factors Influencing Older Adults' Evaluation of Socially Assistive Robots

Socially Assistive Robots (SARs) are expected to support autonomy, aging in place, and wellbeing in later life. For successful assimilation, it is necessary to understand factors affecting older adults Quality Evaluations (QEs) of SARs, including the pragmatic and hedonic evaluations and overall attractiveness. Previous studies showed that trust in robots significantly enhances QE, while technophobia considerably decreases it. The current study aimed to examine the relative impact of these two factors on older persons QE of SARs. The study was based on an online survey of 384 individuals aged 65 and above. Respondents were presented with a video of a robotic system for physical and cognitive training and filled out a questionnaire relating to that system. The results indicated a positive association between trust and QE and a negative association between technophobia and QE. A simultaneous exploration demonstrated that the relative impact of technophobia is significantly more substantial than that of trust. In addition, the pragmatic qualities of the robot were found to be more crucial to its QE than the social aspects of use. The findings suggest that implementing robotics technology in later life strongly depends on reducing older adults technophobia regarding the convenience of using SARs and highlight the importance of simultaneous explorations of facilitators and inhibitors

Towards long-term social child-robot interaction: using multi-activity switching to engage young users

Social robots have the potential to provide support in a number of practical domains, such as learning and behaviour change. This potential is particularly relevant for children, who have proven receptive to interactions with social robots. To reach learning and therapeutic goals, a number of issues need to be investigated, notably the design of an effective child-robot interaction (cHRI) to ensure the child remains engaged in the relationship and that educational goals are met. Typically, current cHRI research experiments focus on a single type of interaction activity (e.g. a game). However, these can suffer from a lack of adaptation to the child, or from an increasingly repetitive nature of the activity and interaction. In this paper, we motivate and propose a practicable solution to this issue: an adaptive robot able to switch between multiple activities within single interactions. We describe a system that embodies this idea, and present a case study in which diabetic children collaboratively learn with the robot about various aspects of managing their condition. We demonstrate the ability of our system to induce a varied interaction and show the potential of this approach both as an educational tool and as a research method for long-term cHRI

Virtual Reality Games for Motor Rehabilitation

This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion