Collage of published research papers

Citation

BibTex format

@article{Lima:2022:10.1109/tcds.2021.3115228,
author = {Lima, MR and Wairagkar, M and Gupta, M and Baena, FRY and Barnaghi, P and Sharp, DJ and Vaidyanathan, R},
doi = {10.1109/tcds.2021.3115228},
journal = {IEEE Transactions on Cognitive and Developmental Systems},
pages = {1378--1397},
title = {Conversational affective social robots for ageing and dementia support},
url = {http://dx.doi.org/10.1109/tcds.2021.3115228},
volume = {14},
year = {2022}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - 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 humanrobot engagement. In this paper, 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-centred approaches in the design of voice systems, including the capacity to handle communication breakdowns for effective use by target populations. We summarise 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.
AU - Lima,MR
AU - Wairagkar,M
AU - Gupta,M
AU - Baena,FRY
AU - Barnaghi,P
AU - Sharp,DJ
AU - Vaidyanathan,R
DO - 10.1109/tcds.2021.3115228
EP - 1397
PY - 2022///
SN - 2379-8920
SP - 1378
TI - Conversational affective social robots for ageing and dementia support
T2 - IEEE Transactions on Cognitive and Developmental Systems
UR - http://dx.doi.org/10.1109/tcds.2021.3115228
UR - https://ieeexplore.ieee.org/document/9548693
UR - http://hdl.handle.net/10044/1/91950
VL - 14
ER -

Awards

  • Finalist: Best Paper - IEEE Transactions on Mechatronics (awarded June 2021)

  • Finalist: IEEE Transactions on Mechatronics; 1 of 5 finalists for Best Paper in Journal

  • Winner: UK Institute of Mechanical Engineers (IMECHE) Healthcare Technologies Early Career Award (awarded June 2021): Awarded to Maria Lima (UKDRI CR&T PhD candidate)

  • Winner: Sony Start-up Acceleration Program (awarded May 2021): Spinout company Serg Tech awarded (1 of 4 companies in all of Europe) a place in Sony corporation start-up boot camp

  • “An Extended Complementary Filter for Full-Body MARG Orientation Estimation” (CR&T authors: S Wilson, R Vaidyanathan)

UK DRI


Established in 2017 by its principal funder the Medical Research Council, in partnership with Alzheimer's Society and Alzheimer’s Research UK, The UK Dementia Research Institute (UK DRI) is the UK’s leading biomedical research institute dedicated to neurodegenerative diseases.