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Cian Donovan

dblp:168/3185 · also Cian Donavan · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2019
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1Human-computer interaction and ubiquitous computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Health and well-being technologies · 56% Human-robot interaction · 44%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Health and well-being technologies
long-term care
0.412019
Meeting Stevie: Perceptions of a Socially Assistive Robot by Residents and Staff in a Long-Term Care Facility · HRI 2019
Human-robot interaction › assistive robotics
socially assistive robotics
0.412019
Meeting Stevie: Perceptions of a Socially Assistive Robot by Residents and Staff in a Long-Term Care Facility · HRI 2019
Health and well-being technologies
elderly care
0.112019
Meeting Stevie: Perceptions of a Socially Assistive Robot by Residents and Staff in a Long-Term Care Facility · HRI 2019

Methods — techniques the papers use, named apart from their topics

mixed-method study · 0.4focus groups · 0.4
YearPublicationVenuePosition
2019 Meeting Stevie: Perceptions of a Socially Assistive Robot by Residents and Staff in a Long-Term Care Facility
abstract
Socially assistive robots (SARs) have the potential to improve working conditions of care workers, empower vulnerable people to retain independence, and even provide social companionship. Through a series of focus groups, this study explores how older adults and professional care workers in a Continued Care Retirement Community (CCRC) perceived a bespoke SAR platform known as Stevie. Using a mixed-method approach, it emerged that both care staff and residents developed a strong fondness for the robot, perceived it to be useful, and could envision a range of useful applications.
Conor McGinn, Eamonn Bourke, Andrew Murtagh, Cian Donovan, Michael Cullinan
HRI4