Abstract
The increase in the elderly population today is a fact. This group of people needs day-to-day care due to their age and, in addition, they often have health problems. Technology can be used to mitigate these problem. However, it must be beared in mind that most of this population is currently unable to get the most out of electronic devices. To help elders benefit from these devices systems adapted to their needs and preferences are needed. In particular, systems that use the elders contextual information to integrate several aspects of eldercare and adapt them to each elder would provide significant benefits. In this paper, we propose to use smartphones as the device who centralizes contextual information of the elders, focusing on emotion recognition. These emotions will be used to recognize to what extent an elderly person needs care at certain times of the day and to adapt surrounding IoT systems to their needs and moods.
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Agarwal, S., Santra, B., Mukherjee, D.P.: Anubhav: recognizing emotions through facial expression. Vis. Comput. 34(2), 177–191 (2018)
Berrocal, J., Garcia-Alonso, J., Murillo, J.M., Canal, C.: Rich contextual information for monitoring the elderly in an early stage of cognitive impairment. Pervasive Mob. Comput. 34, 106–125 (2017)
Dantcheva, A., Bilinski, P., Broutart, J.C., Robert, P., Bremond, F.: Emotion facial recognition by the means of automatic video analysis. Gerontechnol. J. (2016)
Flores-Martin, D., Pérez-Vereda, A., Berrocal, J., Canal, C., Murillo, J.M.: Coordinación de Dispositivos IoT mediante Web Semántica y Ontologías en Situational-Context. JISBD (2018)
Garcia-Alonso, J., Berrocal, J., Murillo, J.M., Mendes, D., Fonseca, C., Lopes, M.: Situational-context for virtually modeling the elderly. In: Novais, P., et al. (eds.) ISAmI 2018. AISC, vol. 806, pp. 298–305. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-01746-0_35
Goyal, S.J., Upadhyay, A.K., Jadon, R.S., Goyal, R.: Real-life facial expression recognition systems: a review. In: Satapathy, S.C., Bhateja, V., Das, S. (eds.) Smart Computing and Informatics. SIST, vol. 77, pp. 311–331. Springer, Singapore (2018). https://doi.org/10.1007/978-981-10-5544-7_31
Hossain, M.S., Muhammad, G.: Cloud-assisted speech and face recognition framework for health monitoring. Mob. Netw. Appl. 20(3), 391–399 (2015)
Kulkarni, A., Shendge, A., Varma, V., Kimmatkar, N.V.: Intelligent emotion detection system using facial images (2018)
Li, H., Buenaposada, J.M., Baumela, L.: Real-time facial expression recognition with illumination-corrected image sequences. In: 8th IEEE International Conference on Automatic Face & Gesture Recognition, FG 2008, pp. 1–6. IEEE (2008)
Lozano-Monasor, E., López, M.T., Vigo-Bustos, F., Fernández-Caballero, A.: Facial expression recognition in ageing adults: from lab to ambient assisted living. J. Ambient Intell. Humanized Comput. 8(4), 567–578 (2017)
Moguel, E., et al.: Enriched elderly virtual profiles by means of a multidimensionalidad integrated assessment platform (2018)
Núñez, C.A.V., Mendoza, P.S., Hernández, K.A., Molinares, D.J.: Internet de las cosas y la salud centrada en el hogar. Salud Uninorte 32(2) (2016)
Rodrigues, R., Huber, M., Lamura, G., et al.: Facts and figures on healthy ageing and long-term care. European Centre for Social Welfare Policy and Research, Vienna (2012)
Sánchez López, M.A., Fernández Alemán, J.L., Toval, A., Carrillo de Gea, J.M.: Teléfonos inteligentes para la tercera edad: una revisión de aplicaciones móviles de salud (2015)
Stergiou, C., Psannis, K.E., Kim, B.G., Gupta, B.: Secure integration of IoT and cloud computing. Future Gener. Comput. Syst. 78, 964–975 (2018)
Suk, M., Prabhakaran, B.: Real-time mobile facial expression recognition system-a case study. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 132–137 (2014)
Acknowledgements
This work was supported by 4IE project (0045-4IE-4-P) funded by the Interreg V-A España-Portugal (POCTEP) 2014–2020 program, by the Spanish Ministry of Economy, Industry and Competitiveness (TIN2014-53986-REDT and TIN2015-69957-R (MINECO/FEDER)), by the Department of Economy and Infrastructure of the Government of Extremadura (GR15098), and by the European Regional Development Fund.
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Bonilla, S., Moguel, E., Garcia-Alonso, J. (2019). Facial Recognition of Emotions with Smartphones to Improve the Elder Quality of Life. In: García-Alonso, J., Fonseca, C. (eds) Gerontechnology. IWoG 2018. Communications in Computer and Information Science, vol 1016. Springer, Cham. https://doi.org/10.1007/978-3-030-16028-9_2
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DOI: https://doi.org/10.1007/978-3-030-16028-9_2
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