TY - JOUR
KW - article
KW - Artificial intelligence
KW - Humans
KW - Intangible cultural heritage
KW - Likert scale
KW - Longevity
KW - Pilot Projects
KW - Psychotherapy
KW - Technology
KW - aged
KW - Artificial intelligence
KW - axon guidance
KW - caregiver
KW - clinical article
KW - clinical feature
KW - cognition
KW - cognitive defect
KW - cognitive impairment
KW - computer simulation
KW - computer system usability questionnaire
KW - cultural heritage
KW - dancing
KW - Education
KW - emotion
KW - emotions recognition
KW - face tracking
KW - Facial expression
KW - facial recognition
KW - Female
KW - health care system
KW - human
KW - human activities
KW - Inheritance
KW - Innovation
KW - Intangible cultural heritage
KW - longevity
KW - male
KW - medical procedures
KW - mental health
KW - mental longevity
KW - mild cognitive impairment
KW - multicenter study
KW - nerve cell network
KW - neuropsychological test
KW - observational study
KW - outcome assessment
KW - path finding algorithm
KW - pilot study
KW - Proverb
KW - psychotherapy
KW - questionnaire
KW - reinforcement (psychology)
KW - reinforcement learning
KW - reinforcement learning (machine learning)
KW - reminiscence therapy
KW - Satisfaction
KW - Technology
KW - tongue twister
KW - tracking
KW - visual analog scale
KW - wellbeing
AU - Angela Nebot
AU - Sara Domenech
AU - Natalia Albino-Pires
AU - Francisco Mugica
AU - Anass Benali
AU - Xenia Porta
AU - Oriol Nebot
AU - Pedro Santos
AB - 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.
DO - 10.3390/ijerph19105997
M1 - 10
N1 - Publisher: MDPI
N2 - 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.
TI - LONG-REMI: An AI-Based Technological Application to Promote Healthy Mental Longevity Grounded in Reminiscence Therapy
UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129957505&doi=10.3390%2fijerph19105997&partnerID=40&md5=9e68f33d447de47bfe7c05076e126fb9
VL - 19
SN - 16617827 (ISSN)
ER -