TY - GEN
T1 - Development of dementia care training system based on augmented reality and whole body wearable tactile sensor
AU - Hiramatsu, Tomoki
AU - Kamei, Masaya
AU - Inoue, Daiji
AU - Kawamura, Akihiro
AU - An, Qi
AU - Kurazume, Ryo
N1 - Publisher Copyright:
© 2020 IEEE.
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2020/10/24
Y1 - 2020/10/24
N2 - This study develops a training system for a multimodal comprehensive care methodology for dementia patients called Humanitude. Humanitude has attracted much attention as a gentle and effective care technique. It consists of four main techniques, namely, eye contact, verbal communication, touch, and standing up, and more than 150 care elements. Learning Humanitude thus requires much time. To provide an effective training system for Humanitude, we develop a training system that realizes sensing and interaction simultaneously by combining a real entity and augmented reality technology. To imitate the interaction between a patient and a caregiver, we superimpose a three-dimensional CG model of a patient's face onto the head of a soft doll using augmented reality technology. Touch information such as position and force is sensed using the whole body wearable tactile sensor developed to quantify touch skills. This training system enables the evaluation of eye contact and touch skills simultaneously. We build a prototype of the proposed training system and evaluate the usefulness of the system in public lectures.
AB - This study develops a training system for a multimodal comprehensive care methodology for dementia patients called Humanitude. Humanitude has attracted much attention as a gentle and effective care technique. It consists of four main techniques, namely, eye contact, verbal communication, touch, and standing up, and more than 150 care elements. Learning Humanitude thus requires much time. To provide an effective training system for Humanitude, we develop a training system that realizes sensing and interaction simultaneously by combining a real entity and augmented reality technology. To imitate the interaction between a patient and a caregiver, we superimpose a three-dimensional CG model of a patient's face onto the head of a soft doll using augmented reality technology. Touch information such as position and force is sensed using the whole body wearable tactile sensor developed to quantify touch skills. This training system enables the evaluation of eye contact and touch skills simultaneously. We build a prototype of the proposed training system and evaluate the usefulness of the system in public lectures.
UR - http://www.scopus.com/inward/record.url?scp=85102409305&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85102409305&partnerID=8YFLogxK
U2 - 10.1109/IROS45743.2020.9341039
DO - 10.1109/IROS45743.2020.9341039
M3 - Conference contribution
AN - SCOPUS:85102409305
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 4148
EP - 4154
BT - 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2020
Y2 - 24 October 2020 through 24 January 2021
ER -