Author
Listed:
- Àngela Nebot
(Soft Computing Research Group at Intelligent Data Science and Artificial Intelligence Research Center, Universitat Politènica de Catalunya, 08034 Barcelona, Spain)
- Sara Domènech
(Fundació Salut i Envelliment, Universitat Autònoma de Barcelona, 08041 Barcelona, Spain)
- Natália Albino-Pires
(Escola Superior de Educação, Instituto Politécnico de Coimbra, 3030-329 Coimbra, Portugal)
- Francisco Mugica
(Soft Computing Research Group at Intelligent Data Science and Artificial Intelligence Research Center, Universitat Politènica de Catalunya, 08034 Barcelona, Spain)
- Anass Benali
(Soft Computing Research Group at Intelligent Data Science and Artificial Intelligence Research Center, Universitat Politènica de Catalunya, 08034 Barcelona, Spain)
- Xènia Porta
(Fundació Salut i Envelliment, Universitat Autònoma de Barcelona, 08041 Barcelona, Spain)
- Oriol Nebot
(UX/UI Dessign Department, Universitat Oberta de Catalunya Barcelona, 08035 Barcelona, Spain)
- Pedro M. Santos
(CINTESIS—Center for Health Technology and Services Research, Universidad de Lusófona Humanidades e Tecnologias, 1749-024 Lisboa, Portugal)
Abstract
Reminiscence therapy (RT) consists of thinking about one’s own experiences through the presentation of memory-facilitating stimuli, and it has as its fundamental axis the activation of emotions. An innovative way of offering RT involves the use of technology-assisted applications, which must also satisfy the needs of the user. This study aimed to develop an AI-based computer application that recreates RT in a personalized way, meeting the characteristics of RT guided by a therapist or a caregiver. The material guiding RT focuses on intangible cultural heritage. The application incorporates facial expression analysis and reinforcement learning techniques, with the aim of identifying the user’s emotions and, with them, guiding the computer system that emulates RT dynamically and in real time. A pilot study was carried out at five senior centers in Barcelona and Portugal. The results obtained are very positive, showing high user satisfaction. Moreover, the results indicate that the high frequency of positive emotions increased in the participants at the end of the intervention, while the low frequencies of negative emotions were maintained at the end of the intervention.
Suggested Citation
Àngela Nebot & Sara Domènech & Natália Albino-Pires & Francisco Mugica & Anass Benali & Xènia Porta & Oriol Nebot & Pedro M. Santos, 2022.
"LONG-REMI: An AI-Based Technological Application to Promote Healthy Mental Longevity Grounded in Reminiscence Therapy,"
IJERPH, MDPI, vol. 19(10), pages 1-15, May.
Handle:
RePEc:gam:jijerp:v:19:y:2022:i:10:p:5997-:d:815951
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:19:y:2022:i:10:p:5997-:d:815951. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.