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A Low-Cost Cognitive Assistant

Abstract

[EN] In this paper, we present in depth the hardware components of a low-cost cognitive assistant. The aim is to detect the performance and the emotional state that elderly people present when performing exercises. Physical and cognitive exercises are a proven way of keeping elderly people active, healthy, and happy. Our goal is to bring to people that are at their homes (or in unsupervised places) an assistant that motivates them to perform exercises and, concurrently, monitor them, observing their physical and emotional responses. We focus on the hardware parts and the deep learning models so that they can be reproduced by others. The platform is being tested at an elderly people care facility, and validation is in process.This work was partly supported by the FCT (Fundacao para a Ciencia e Tecnologia) through the Post-Doc scholarship SFRH/BPD/102696/2014 (A. Costa), by the Generalitat Valenciana (PROMETEO/2018/002), and by the Spanish Government (RTI2018-095390-B-C31).Araujo, A.; Rincón Arango, JA.; Julian Inglada, VJ.; Novais, P.; Carrascosa Casamayor, C. (2020). A Low-Cost Cognitive Assistant. Electronics. 9(2):1-19. https://doi.org/10.3390/electronics902031011992Licher, S., Darweesh, S. K. L., Wolters, F. J., Fani, L., Heshmatollah, A., Mutlu, U., … Ikram, M. A. (2018). Lifetime risk of common neurological diseases in the elderly population. Journal of Neurology, Neurosurgery & Psychiatry, 90(2), 148-156. doi:10.1136/jnnp-2018-318650Jaul, E., & Barron, J. (2017). Age-Related Diseases and Clinical and Public Health Implications for the 85 Years Old and Over Population. Frontiers in Public Health, 5. doi:10.3389/fpubh.2017.00335Brasure, M., Desai, P., Davila, H., Nelson, V. A., Calvert, C., Jutkowitz, E., … Kane, R. L. (2017). Physical Activity Interventions in Preventing Cognitive Decline and Alzheimer-Type Dementia. Annals of Internal Medicine, 168(1), 30. doi:10.7326/m17-1528Iuliano, E., di Cagno, A., Cristofano, A., Angiolillo, A., D’Aversa, R., … Di Costanzo, A. (2019). Physical exercise for prevention of dementia (EPD) study: background, design and methods. BMC Public Health, 19(1). doi:10.1186/s12889-019-7027-3Müllers, P., Taubert, M., & Müller, N. G. (2019). Physical Exercise as Personalized Medicine for Dementia Prevention? Frontiers in Physiology, 10. doi:10.3389/fphys.2019.00672Pérez-Fuentes, M. del C., Gázquez Linares, J. J., Ruiz Fernández, M. D., & Molero Jurado, M. del M. (2017). Inventory of Overburden in Alzheimer’s Patient Family Caregivers with no Specialized Training. International Journal of Clinical and Health Psychology, 17(1), 56-64. doi:10.1016/j.ijchp.2016.09.004Berglund, E., Lytsy, P., & Westerling, R. (2015). Health and wellbeing in informal caregivers and non-caregivers: a comparative cross-sectional study of the Swedish general population. Health and Quality of Life Outcomes, 13(1). doi:10.1186/s12955-015-0309-2Peña-Longobardo, L. M., & Oliva-Moreno, J. (2014). Caregiver Burden in Alzheimer’s Disease Patients in Spain. Journal of Alzheimer’s Disease, 43(4), 1293-1302. doi:10.3233/jad-141374Hoefman, R. J., Meulenkamp, T. M., & De Jong, J. D. (2017). Who is responsible for providing care? Investigating the role of care tasks and past experiences in a cross-sectional survey in the Netherlands. BMC Health Services Research, 17(1). doi:10.1186/s12913-017-2435-5Pearson, C. F., Quinn, C. C., Loganathan, S., Datta, A. R., Mace, B. B., & Grabowski, D. C. (2019). The Forgotten Middle: Many Middle-Income Seniors Will Have Insufficient Resources For Housing And Health Care. Health Affairs, 38(5), 10.1377/hlthaff. doi:10.1377/hlthaff.2018.05233Costa, A., Novais, P., Julian, V., & Nalepa, G. J. (2018). Cognitive assistants. 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A Caregiver Support Platform within the Scope of an Ambient Assisted Living Ecosystem. Sensors, 14(3), 5654-5676. doi:10.3390/s140305654Costa, Â., Heras, S., Palanca, J., Jordán, J., Novais, P., & Julian, V. (2017). Using Argumentation Schemes for a Persuasive Cognitive Assistant System. Lecture Notes in Computer Science, 538-546. doi:10.1007/978-3-319-59294-7_43Wang, J., Chen, Y., Hao, S., Peng, X., & Hu, L. (2019). Deep learning for sensor-based activity recognition: A survey. Pattern Recognition Letters, 119, 3-11. doi:10.1016/j.patrec.2018.02.010Nweke, H. F., Teh, Y. W., Al-garadi Mohammed Ali, & Alo, U. R. (2018). Deep learning algorithms for human activity recognition using mobile and wearable sensor networks: State of the art and research challenges. Expert Systems with Applications, 105, 233-261. doi:10.1016/j.eswa.2018.03.056Martinez-Martin, E., & Cazorla, M. (2019). A Socially Assistive Robot for Elderly Exercise Promotion. 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