Effectiveness of Intrinsically Motivated Adaptive Agent for Sustainable Human-Agent Interaction

Nozawa, Takayuki; Kondo, Toshiyuki

doi:10.1007/978-3-642-10684-2_20

Cited by 2 publications

(1 citation statement)

References 9 publications

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“…Nozawa and Kondo ( 2009 ) have monitored the activity of the PFC using fNIRS during controlled mouse-based interaction with a virtual agent and found a surge of activity predominantly in the DL-PFC, which they interpreted in attentional terms only. Benbasat et al ( 2010 ) reported a neuroimaging study of how virtual agents induce social presence as a function of their appearance (gender, ethnicity) using fMRI, with the anterior paracingulate cortex as a region of interest.…”

Section: Previous and Related Workmentioning

confidence: 99%

Affective Interaction with a Virtual Character Through an fNIRS Brain-Computer Interface

Aranyi

Pecune

Charles

et al. 2016

Front. Comput. Neurosci.

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Affective brain-computer interfaces (BCI) harness Neuroscience knowledge to develop affective interaction from first principles. In this article, we explore affective engagement with a virtual agent through Neurofeedback (NF). We report an experiment where subjects engage with a virtual agent by expressing positive attitudes towards her under a NF paradigm. We use for affective input the asymmetric activity in the dorsolateral prefrontal cortex (DL-PFC), which has been previously found to be related to the high-level affective-motivational dimension of approach/avoidance. The magnitude of left-asymmetric DL-PFC activity, measured using functional near infrared spectroscopy (fNIRS) and treated as a proxy for approach, is mapped onto a control mechanism for the virtual agent’s facial expressions, in which action units (AUs) are activated through a neural network. We carried out an experiment with 18 subjects, which demonstrated that subjects are able to successfully engage with the virtual agent by controlling their mental disposition through NF, and that they perceived the agent’s responses as realistic and consistent with their projected mental disposition. This interaction paradigm is particularly relevant in the case of affective BCI as it facilitates the volitional activation of specific areas normally not under conscious control. Overall, our contribution reconciles a model of affect derived from brain metabolic data with an ecologically valid, yet computationally controllable, virtual affective communication environment.

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Section: Previous and Related Workmentioning

confidence: 99%

Affective Interaction with a Virtual Character Through an fNIRS Brain-Computer Interface

Aranyi

Pecune

Charles

et al. 2016

Front. Comput. Neurosci.

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Functional Near-Infrared Spectroscopy in Human-Robot Interaction

Canning

Scheutz

2013

Journal of Human-Robot Interaction

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Functional near-infrared spectroscopy (fNIRS) is a promising new tool for research in human-robot interaction (HRI). The technology has already been used for brain-robot interfaces to affect robots' behaviors and as an evaluation tool for assessing brain activity during interactions. In this survey, we provide a comprehensive literature review of published research on fNIRS from various communities to assess its utility in HRI. We discuss four exemplary applications in more detail and also list several challenges that need to be overcome for fNIRS to be an effective tool in realistic HRI settings. Keywords: human-robot interaction (HRI), functional near-infrared spectroscopy (fNIRS), nearinfrared spectroscopy (NIRS), brain imaging, neuroimaging, brain-robot interface (BRI), humanmachine interaction (HMI), brain-computer interface (BCI), brain-machine interface (BMI) Authors retain copyright and grant the Journal of Human-Robot Interaction right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.

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Effectiveness of Intrinsically Motivated Adaptive Agent for Sustainable Human-Agent Interaction

Cited by 2 publications

References 9 publications

Affective Interaction with a Virtual Character Through an fNIRS Brain-Computer Interface

Affective Interaction with a Virtual Character Through an fNIRS Brain-Computer Interface

Functional Near-Infrared Spectroscopy in Human-Robot Interaction

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