Multiscale Entropy Quantifies the Differential Effect of the Medium Embodiment on Older Adults Prefrontal Cortex during the Story Comprehension: A Comparative Analysis
1
Hiroshi Ishiguro Laboratories (HIL), Advanced Telecommunications Research Institute International (ATR), 2-2 Hikaridai Seika-cho, Kyoto 619-02, Japan
2
School of Social Sciences, Waseda University, 1 Chome-104 Totsukamachi, Shinjuku, Tokyo 169-8050, Japan
3
Graduate School of Engineering Science, Osaka University, 2-1 Yamadaoka, Suita, Osaka 565-0871, Japan
*
Author to whom correspondence should be addressed.
†
Both authors contributed equally to this work.
Entropy 2019, 21(2), 199; https://doi.org/10.3390/e21020199
Received: 23 January 2019 / Revised: 15 February 2019 / Accepted: 16 February 2019 / Published: 19 February 2019
(This article belongs to the Special Issue Multiscale Entropy Approaches and Their Applications)
Todays’ communication media virtually impact and transform every aspect of our daily communication and yet the extent of their embodiment on our brain is unexplored. The study of this topic becomes more crucial, considering the rapid advances in such fields as socially assistive robotics that envision the use of intelligent and interactive media for providing assistance through social means. In this article, we utilize the multiscale entropy (MSE) to investigate the effect of the physical embodiment on the older people’s prefrontal cortex (PFC) activity while listening to stories. We provide evidence that physical embodiment induces a significant increase in MSE of the older people’s PFC activity and that such a shift in the dynamics of their PFC activation significantly reflects their perceived feeling of fatigue. Our results benefit researchers in age-related cognitive function and rehabilitation who seek for the adaptation of these media in robot-assistive cognitive training of the older people. In addition, they offer a complementary information to the field of human-robot interaction via providing evidence that the use of MSE can enable the interactive learning algorithms to utilize the brain’s activation patterns as feedbacks for improving their level of interactivity, thereby forming a stepping stone for rich and usable human mental model.
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MDPI and ACS Style
Keshmiri, S.; Sumioka, H.; Yamazaki, R.; Ishiguro, H. Multiscale Entropy Quantifies the Differential Effect of the Medium Embodiment on Older Adults Prefrontal Cortex during the Story Comprehension: A Comparative Analysis. Entropy 2019, 21, 199.
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