Towards an automatic recommendation system to well-being for elderly based on augmented reality

Accordingly to the National Population Council (CONAPO) in Mexico, people over 60 years old are equivalent to 10% of the population [1]. This age is considered the beginning of the older adult stage, and by 2050 there will be an inevitable generational transition where older adults will represent 21.5% of the Mexican population. One of the most common diseases of this sector is cognitive impairment or dementia, being Alzheimer’s Disease (AD) the most common with 60% of cases. AD causes depression and negative emotional states that impact the physical, mental and social health of adults and their families. Advances in artificial intelligence have proven to approach and understand human behavior and their emotional state under different circumstances. In this paper, we propose an Augmented Reality based strategy for measuring different emotional states of older adults. By interacting with multimedia content (audios, photos, and videos) we are laying the foundations for the creation of an intelligent platform that detects the negative emotional state and issues multimedia recommendations based on tastes customized to move the patient to a positive emotional state.

[1]  John Tudor,et al.  Fuzzy logic based emotion classification , 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[2]  Rafael A. Calvo,et al.  Affect Detection: An Interdisciplinary Review of Models, Methods, and Their Applications , 2010, IEEE Transactions on Affective Computing.

[3]  Nhan Le Thanh,et al.  Detecting depression using multimodal approach of emotion recognition , 2012, 2012 IEEE International Conference on Complex Systems (ICCS).

[4]  Erik Cambria,et al.  Affective Computing and Sentiment Analysis , 2016, IEEE Intelligent Systems.

[5]  Tom Crick,et al.  Incorporating Emotion and Personality-Based Analysis in User-Centered Modelling , 2016, SGAI Conf..

[6]  Ivor W. Tsang,et al.  ‘Who Likes What and, Why?’ Insights into Modeling Users’ Personality Based on Image ‘Likes’ , 2018, IEEE Transactions on Affective Computing.

[7]  P. Ekman Emotions revealed , 2004, BMJ.

[8]  A. Tellegen,et al.  PERSONALITY PROCESSES AND INDIVIDUAL DIFFERENCES An Alternative "Description of Personality": The Big-Five Factor Structure , 2022 .

[9]  Rosario Baltazar,et al.  Towards Game Based Monitoring and Cognitive Therapy for Elderly using a Neural-Fuzzy approach Conference , 2018 .

[10]  Manolis Tsiknakis,et al.  Dementia Care Frameworks and Assistive Technologies for Their Implementation: A Review , 2019, IEEE Reviews in Biomedical Engineering.

[11]  Víctor Zamudio,et al.  Identification and Analysis of Emotions in a Game Based Therapy for Patients with Cognitive Impairment , 2018, Intelligent Environments.

[12]  Marko Horvat,et al.  Multimedia stimuli databases usage patterns: a survey report , 2013, 2013 36th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO).