Conversational Affective Social Robots for Ageing and Dementia Support

被引:26
作者
Lima, Maria R. [1 ,2 ]
Wairagkar, Maitreyee [1 ,2 ]
Gupta, Manish [3 ]
Baena, Ferdinando [4 ,5 ]
Barnaghi, Payam [2 ,6 ]
Sharp, David J. [2 ,6 ]
Vaidyanathan, Ravi [1 ,2 ]
机构
[1] Imperial Coll London, Dept Mech Engn, London SW7 2BX, England
[2] UK Dementia Res Inst, Care Res & Technol Ctr, London W12 0BZ, England
[3] Google Res India, Bengaluru, India
[4] Imperial Coll London, Dept Mech Engn, London SW7 2BX, England
[5] Imperial Coll London, Hamlyn Ctr Robot Surg, London SW7 2BX, England
[6] Imperial Coll London, Dept Brain Sci, London SW7 2BX, England
关键词
Ageing; cognitive robotics; conversational AI; dementia; human-robot interaction (HRI); socially assistive robots (SAR); voice technology; COMMUNICATION ROBOT; ASSISTIVE ROBOTICS; ELDERLY-PEOPLE; NURSING-HOMES; CARE; CATEGORIZATION; CHALLENGES; INTERFACE; SERVICES; EMOTION;
D O I
10.1109/TCDS.2021.3115228
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Socially assistive robots (SAR) hold significant potential to assist older adults and people with dementia in human engagement and clinical contexts by supporting mental health and independence at home. While SAR research has recently experienced prolific growth, long-term trust, clinical translation, and patient benefit remain immature. Affective human-robot interactions are unresolved and the deployment of robots with conversational abilities is fundamental for robustness and human-robot engagement. In this article, we review the state of the art within the past two decades, design trends, and current applications of conversational affective SAR for ageing and dementia support. A horizon scanning of AI voice technology for healthcare, including ubiquitous smart speakers, is further introduced to address current gaps inhibiting home use. We discuss the role of user-centered approaches in the design of voice systems, including the capacity to handle communication breakdowns for effective use by target populations. We summarize the state of development in interactions using speech and natural language processing, which forms a baseline for longitudinal health monitoring and cognitive assessment. Drawing from this foundation, we identify open challenges and propose future directions to advance conversational affective social robots for: 1) user engagement; 2) deployment in real-world settings; and 3) clinical translation.
引用
收藏
页码:1378 / 1397
页数:20
相关论文
共 131 条
[1]  
A. A. Skills, MY CAR AL SKILL
[2]  
A. S. Society, LOCKDOWNS SIDE EFFEC
[3]   Scoping review on the use of socially assistive robot technology in elderly care [J].
Abdi, Jordan ;
Al-Hindawi, Ahmed ;
Ng, Tiffany ;
Vizcaychipi, Marcela P. .
BMJ OPEN, 2018, 8 (02)
[4]  
Abdollahi H, 2017, 2017 IEEE-RAS 17TH INTERNATIONAL CONFERENCE ON HUMANOID ROBOTICS (HUMANOIDS), P541, DOI 10.1109/HUMANOIDS.2017.8246925
[5]  
Addlesee A, 2019, Arxiv, DOI arXiv:1909.06644
[6]  
Alzheimer's Research U.K. U.K, DEM STAT
[7]  
Amazon, AL CAR HUB
[8]   Cognitive System Framework for Brain-Training Exercise Based on Human-Robot Interaction [J].
Andriella, Antonio ;
Torras, Carme ;
Alenya, Guillem .
COGNITIVE COMPUTATION, 2020, 12 (04) :793-810
[9]  
[Anonymous], 2008, P 3 ACM IEEE INT C H
[10]  
Asgari Meysam, 2017, Alzheimers Dement (N Y), V3, P219, DOI 10.1016/j.trci.2017.01.006