Wearable Affective Robot
With the development of the artificial intelligence (AI), the AI applications have influenced and changed people's daily life greatly. Here, a wearable affective robot that integrates the affective robot, social robot, brain wearable, and Wearable 2.0 is proposed for the first time. The propose...
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doaj-a9ce77f8efff45dd9834a608146af6e12021-03-29T21:28:55ZengIEEEIEEE Access2169-35362018-01-016647666477610.1109/ACCESS.2018.28779198506341Wearable Affective RobotMin Chen0https://orcid.org/0000-0002-0960-4447Jun Zhou1Guangming Tao2Jun Yang3Long Hu4Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, ChinaWuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, ChinaWuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, ChinaSchool of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, ChinaSchool of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, ChinaWith the development of the artificial intelligence (AI), the AI applications have influenced and changed people's daily life greatly. Here, a wearable affective robot that integrates the affective robot, social robot, brain wearable, and Wearable 2.0 is proposed for the first time. The proposed wearable affective robot is intended for a wide population, and we believe that it can improve the human health on the spirit level, meeting the fashion requirements at the same time. In this paper, the architecture and design of an innovative wearable affective robot, which is dubbed as Fitbot, are introduced in terms of hardware and algorithm's perspectives. In addition, the important functional component of the robot-brain wearable device is introduced from the aspect of the hardware design, EEG data acquisition and analysis, user behavior perception, and algorithm deployment. Then, the EEG-based cognition of user's behavior is realized. Through the continuous acquisition of the in-depth, in-breadth data, the Fitbot we present can gradually enrich user's life modeling and enable the wearable robot to recognize user's intention and further understand the behavioral motivation behind the user's emotion. The learning algorithm for the life modeling embedded in Fitbot can achieve better user's experience of affective social interaction. Finally, the application service scenarios and some challenging issues of a wearable affective robot are discussed.https://ieeexplore.ieee.org/document/8506341/Emotion cognitionsocial robotRNNEEGWearable 20 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Min Chen Jun Zhou Guangming Tao Jun Yang Long Hu |
spellingShingle |
Min Chen Jun Zhou Guangming Tao Jun Yang Long Hu Wearable Affective Robot IEEE Access Emotion cognition social robot RNN EEG Wearable 20 |
author_facet |
Min Chen Jun Zhou Guangming Tao Jun Yang Long Hu |
author_sort |
Min Chen |
title |
Wearable Affective Robot |
title_short |
Wearable Affective Robot |
title_full |
Wearable Affective Robot |
title_fullStr |
Wearable Affective Robot |
title_full_unstemmed |
Wearable Affective Robot |
title_sort |
wearable affective robot |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2018-01-01 |
description |
With the development of the artificial intelligence (AI), the AI applications have influenced and changed people's daily life greatly. Here, a wearable affective robot that integrates the affective robot, social robot, brain wearable, and Wearable 2.0 is proposed for the first time. The proposed wearable affective robot is intended for a wide population, and we believe that it can improve the human health on the spirit level, meeting the fashion requirements at the same time. In this paper, the architecture and design of an innovative wearable affective robot, which is dubbed as Fitbot, are introduced in terms of hardware and algorithm's perspectives. In addition, the important functional component of the robot-brain wearable device is introduced from the aspect of the hardware design, EEG data acquisition and analysis, user behavior perception, and algorithm deployment. Then, the EEG-based cognition of user's behavior is realized. Through the continuous acquisition of the in-depth, in-breadth data, the Fitbot we present can gradually enrich user's life modeling and enable the wearable robot to recognize user's intention and further understand the behavioral motivation behind the user's emotion. The learning algorithm for the life modeling embedded in Fitbot can achieve better user's experience of affective social interaction. Finally, the application service scenarios and some challenging issues of a wearable affective robot are discussed. |
topic |
Emotion cognition social robot RNN EEG Wearable 20 |
url |
https://ieeexplore.ieee.org/document/8506341/ |
work_keys_str_mv |
AT minchen wearableaffectiverobot AT junzhou wearableaffectiverobot AT guangmingtao wearableaffectiverobot AT junyang wearableaffectiverobot AT longhu wearableaffectiverobot |
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