Morphological Computation of Skin Focusing on Fingerprint Structure

Akane Musha, Manabu Daihara, Hiroki Shigemune, Hideyuki Sawada

研究成果: Conference contribution

抄録

When humans get tactile sensation, we touch an object with the skin and the stimuli are transmitted to the brain. The effect of the skin in tactile perception however has not been clarified yet, and sensors considering the skin functions are not introduced. In this research, we investigate the information processing performed by the skin against physical stimuli in touching an object from the viewpoint of morphological computation. We create a dynamical model that expresses the skin structure based on the spring and mass model, and show that the model contributes to the learning of temporal response against physical stimuli. In addition, we conduct an experiment to compare the learning performance of a finger model having fingerprints with a model without fingerprints. Frequency response against physical stimuli with different frequencies is examined, and the result shows that the performance of a model with fingerprints is better in the higher frequency range. The model with fingerprints also reflects the hardness of the human skin remarkably. These results are expected to help clarify the information processing ability of the human skin focusing on the fingerprint structure in response to external physical stimuli.

本文言語English
ホスト出版物のタイトルArtificial Neural Networks and Machine Learning – ICANN 2020 - 29th International Conference on Artificial Neural Networks, Proceedings
編集者Igor Farkaš, Paolo Masulli, Stefan Wermter
出版社Springer Science and Business Media Deutschland GmbH
ページ470-481
ページ数12
ISBN(印刷版)9783030616151
DOI
出版ステータスPublished - 2020
イベント29th International Conference on Artificial Neural Networks, ICANN 2020 - Bratislava, Slovakia
継続期間: 2020 9 152020 9 18

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
12397 LNCS
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Conference

Conference29th International Conference on Artificial Neural Networks, ICANN 2020
CountrySlovakia
CityBratislava
Period20/9/1520/9/18

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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