Abstract
Nowadays, one of the clinical challenge is the realization of personalized treatments, which falls into the more general paradigm of the precision medicine. On the other hand, over the last years we have assisted the rising of technologies able to assist people at home during their daily activities. In this paper we present an intelligent system, which is able to self-adapt to user’s skills aiming at assisting her/him in the healthcare treatment. The system adopts the Reinforcement Learning paradigm to adapt the way to communicate with the patient. By this way, in case of patients with physical disabilities (e.g. auditory or visual impairments) or cognitive disabilities (e.g. mild cognitive impairments), the system automatically searches for the most effective way to communicate and remind the daily treatment plan to the patient.
The AMICO project has received funding from the National Programs (PON) of the Italian Ministry of Education, Universities and Research (MIUR): code ARS01_00900 (Decree n.1989, 26 July 2018).
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Coronato, A., Naeem, M. (2019). A Reinforcement Learning Based Intelligent System for the Healthcare Treatment Assistance of Patients with Disabilities. In: Esposito, C., Hong, J., Choo, KK. (eds) Pervasive Systems, Algorithms and Networks. I-SPAN 2019. Communications in Computer and Information Science, vol 1080. Springer, Cham. https://doi.org/10.1007/978-3-030-30143-9_2
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