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ORIGINAL RESEARCH article

Front. Robot. AI
Sec. Human-Robot Interaction
Volume 11 - 2024 | doi: 10.3389/frobt.2024.1419584

Siamese and triplet network-based pain expression in robotic avatars for care and nursing training

Provisionally accepted
Miran Lee Miran Lee *Minjeong Lee Minjeong Lee Suyeong Kim Suyeong Kim
  • Daegu University, Gyeongsan, North Gyeongsang, Republic of Korea

The final, formatted version of the article will be published soon.

    Care and nursing training (CNT) refers to developing the ability to effectively respond to patient needs by investigating their requests and improving trainees' care skills in a caring environment. Although conventional CNT programs have been conducted based on videos, books, and role-playing, the best approach is to practice on a real human. However, it is challenging to recruit patients for continuous training, and the patients may experience fatigue or boredom with iterative testing.As an alternative approach, a patient robot that reproduces various human diseases and provides feedback to trainees has been introduced. This study presents a patient robot that can express feelings of pain, similarly to a real human, in joint care education. The two primary objectives of the proposed patient robot-based care training system are (a) to infer the pain felt by the patient robot and intuitively provide the trainee with the patient's pain state, and (b) to provide facial expression-based visual feedback of the patient robot for care training.

    Keywords: human-robot interaction, care and nursing education, pain expression, robotic facial expression, SIAMESE network

    Received: 18 Apr 2024; Accepted: 30 Aug 2024.

    Copyright: © 2024 Lee, Lee and Kim. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Miran Lee, Daegu University, Gyeongsan, 712-714, North Gyeongsang, Republic of Korea

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.