ORCID
- Palomino, Marco: 0000-0001-7850-416X
Abstract
For the first time in the history of humanity, the number of people over 65 surpassed those under 5 in 2018. Undoubtedly, older people will play a significant role in the future of the economy and society in general, and technological innovation will be indispensable to support them. Thus, we were interested in learning how home automation could enable older people to live independently for longer. To better understand this, we held focus groups with UK senior citizens in 2021, and we analyzed the data derived from them from the perspective of affective computing. We have trained a machine learning classifier capable of distinguishing moods commonly associated with older adults. We have identified depression, sadness and anger as the most prominent mood states conveyed in our focus groups. Our practical insights can aid the design of strategic choices concerning the wellbeing of the ageing population.
DOI
10.15439/2022f50
Publication Date
2022-07-07
Publication Title
Communication Papers of the 17th Conference on Computer Science and Intelligence Systems
ISSN
2300-5963
Embargo Period
2022-11-10
Organisational Unit
School of Engineering, Computing and Mathematics
Recommended Citation
Palomino, M., Allen, R., Aider, F., Tirotto, F., Giorgi, I., Alexander, H., & Masala, G. (2022) 'The Mood of the Silver Economy: A Data Science Analysis of the Mood States of Older Adults and the Implications on their Wellbeing', Communication Papers of the 17th Conference on Computer Science and Intelligence Systems, . Available at: https://doi.org/10.15439/2022f50
