dd798800aff13498be466942419517b0 pmc_9141720.pdf 4a910cf6c2e095dd51f0189bfe2ed73011c30758 pmc_9141720.pdf 5fe6479754df99ba6411b7672d7fc2c2e38188418b670eeafa8113d193048b80 pmc_9141720.pdf Title: LONG-REMI: An AI-Based Technological Applicationto Promote Healthy Mental Longevity Groundedin Reminiscence Therapy Subject: 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. Keywords: reminiscence therapy; cognitive impairment; intangible cultural heritage; emotions recognition; face tracking; reinforcement learning Author: Àngela Nebot, Sara Domènech, Natália Albino-Pires, Francisco Mugica, Anass Benali, Xènia Porta, Oriol Nebot and Pedro M. 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Santos Subject: 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. 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