Fetusoid35: A robot research platform for neural development of both fetuses and preterm infants and for developmental care

Hiroki Mori, Daii Akutsu, Minoru Asada

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We have been developing a robot called Fetusoid35 that resembles a human fetus or preterm infant. We suppose that the robot could contribute to developmental science by shedding a new insight on the understanding the developmental process of fetuses and preterm infants. Based on the mechanism, we would expect to improve a developmental care of preterm infants. This extended abstract briefly introduces the design policy of Fetusoid35 with its specifications and the current status.

Original languageEnglish
Title of host publicationBiomimetic and Biohybrid Systems - Third International Conference, Living Machines 2014, Proceedings
PublisherSpringer Verlag
Pages411-413
Number of pages3
ISBN (Print)9783319094342
DOIs
Publication statusPublished - 2014 Jan 1
Event3rd International Conference on Biomimetic and Biohybrid Systems, Living Machines 2014 - Milan, Italy
Duration: 2014 Jul 302014 Aug 1

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8608 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other3rd International Conference on Biomimetic and Biohybrid Systems, Living Machines 2014
CountryItaly
CityMilan
Period14/7/3014/8/1

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Keywords

  • Developmental care
  • Fetus
  • Preterm infant
  • Robot platform

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Mori, H., Akutsu, D., & Asada, M. (2014). Fetusoid35: A robot research platform for neural development of both fetuses and preterm infants and for developmental care. In Biomimetic and Biohybrid Systems - Third International Conference, Living Machines 2014, Proceedings (pp. 411-413). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8608 LNAI). Springer Verlag. https://doi.org/10.1007/978-3-319-09435-9_46