Abstract
Edge computing has recently emerged as a transformative concept, facilitating the development of future technologies such as AI, robotics, IoT, and high-speed wireless sensor networks like 5G. It achieves this by bridging the gap between cloud computing resources and end-users. In the context of medical and healthcare applications, edge computing plays a crucial role in enabling remote patient monitoring and handling large volumes of multimedia data. One specific area where edge computing has made significant strides is in the field of robotics, particularly in the domain of robot-assisted therapy (RAT). RAT is an active-assistive robotic technology within the realm of rehabilitation robotics, garnering considerable attention from researchers. Its primary objective is to benefit individuals with disabilities, such as children with autism spectrum disorder (ASD). However, RAT faces a substantial challenge, namely the development of models capable of accurately detecting the emotional states of individuals with ASD and retaining knowledge of their unique preferences. Furthermore, incorporating expert diagnosis and recommendations to guide robots in adapting therapy approaches to varying conditions and scenarios is essential to the ASD therapy process. This paper proposes a novel architecture known as edge cognitive computing, which seamlessly integrates human experts and assisted robots within the same framework to provide long-term support for ASD patients. By combining real-time computing and analysis through an innovative cognitive robotic model designed for ASD therapy, this proposed architecture achieves several critical functionalities. These include uninterrupted remote diagnosis, continuous symptom monitoring, rapid response to emergencies, dynamic therapy adjustments, and advanced assistance, all aimed at enhancing the well-being of individuals with ASD.
Original language | English |
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Title of host publication | Human-Computer Interaction |
Subtitle of host publication | Thematic Area, HCI 2024, Held as Part of the 26th HCI International Conference, HCII 2024, Proceedings |
Editors | Masaaki Kurosu, Ayako Hashizume |
Publisher | Springer, Cham |
Pages | 3-18 |
Number of pages | 16 |
Volume | 14685 |
ISBN (Electronic) | 9783031604126 |
ISBN (Print) | 9783031604119 |
DOIs | |
Publication status | Published - 2 Jun 2024 |
Event | 26th Human-Computer Interaction International Conference - Washington, United States Duration: 29 Jun 2024 → 4 Jul 2024 Conference number: 26 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Publisher | Springer |
Volume | 14685 LNCS |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | 26th Human-Computer Interaction International Conference |
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Abbreviated title | HCI 2024 |
Country/Territory | United States |
City | Washington |
Period | 29/06/24 → 4/07/24 |