A robot as fitness companion: Towards an interactive action-based motivation model

2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids)

2016

Self Cite

Abstract-Engineers developing socially assistive robots for promoting a healthy and active lifestyle are facing several mechanical and interactive design challenges. In this paper we are answering the question whether a humanoid robot exercising partner capable of working out together with its user makes significant improvement in the user's engagement. We conducted a study with 56 participants doing five isometric exercises in three conditions comparing the differences between working out alone (IC), with an humanoid robot instructor (RI), or with a humanoid robot companion (RC). Our results show that the RC brings a motivational gain to exercise longer compared to all other conditions.

Section: B Sar For Physical Activitymentioning

confidence: 99%

Exercising with a humanoid companion is more effective than exercising alone

2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids)

2016

Self Cite

“…In previous work we have developed a motivational interaction model which we have evaluated in an extended long-term study [25]. While the previous im-…”

Section: Introductionmentioning

confidence: 99%

“…In this work we describe a general formalized framework for SAR and introduce three scenarios that made use of it. Furthermore, we want to show that the modularization of the motivational interaction patterns allows to systematically test different aspects of 25 interactional motivation.…”

mentioning

confidence: 99%

A framework for designing socially assistive robot interactions

Goerlich

Cognitive Systems Research

2017

Self Cite

Robots are increasingly tested in different socially assistive scenarios. Future applications range from dieting, coaching, tutoring to autism therapy. In such applications the success of the system is commonly evaluated by the ability to encourage the user to keep up with a task. Hence, one important requirement for supportive systems is to have an interactional motivational model that formalizes the way how users can be assisted. In this paper we describe our framework for coordinating motivational interaction scenarios with socially assistive robots (SAR) in the context of sport assistance. We exemplify three different sport scenarios where we have used the same motivational interaction model. Furthermore, we show how this model can be used to systematically test the different aspects of motivation in the context of SAR in sport domains. Therefore, we have conducted an experiment to evaluate the importance of acknowledgement from SAR for human interaction partners. The results show that users exercise longer if acknowledgment is included into the motivational model.

“…While other types of feedback (i.e. positive, negative, comparative or corrective feedback) have been studied in Human-Robot Interaction (HRI) [8][9][10], the quantitative effects of acknowledgement while working out with a robot have not been compared to a baseline measurement. Because most of the published studies comparing different types of feedback are lacking comparative results to baseline studies with no robot or no feedback, it is difficult to distinguish the true motivational effects of SAR.…”

Section: Introductionmentioning

confidence: 99%

Motivational Effects of Acknowledging Feedback from a Socially Assistive Robot

2016

Social Robotics

Self Cite

Abstract. Preventing diseases of affluence is one of the major challenges for our future society. Recently, robots have been introduced as support for people on dieting or rehabilitation tasks. In our current work, we are investigating how the companionship and acknowledgement of a socially assistive robot (SAR) can influence the user to persist longer on a planking task. We conducted a 2 (acknowledgement vs. no-acknowledgment) x 2 (instructing vs. exercising together) x 1 (baseline) study with 96 subjects. We observed a motivational gain if the robot is exercising together with the user or if the robot is giving acknowledging feedback. However, we could not find an increase in motivation if the robot is showing both behaviors. We attribute the later finding to ceiling effects and discuss why we could not find an additional performance gain. Moreover, we highlight implications for SAR researchers developing robots to motivate people to extend exercising duration.