Abstract
Alzheimer’s disease is one of the most well-known diseases among the elderly. It is a neuro-degenerative and irreversible brain disease that gradually erodes memory, thinking skills, and, eventually, the capacity to do even basic daily activities. Therefore, patients should be aided at all times in carrying out their daily tasks. In this study, we propose a new assistance system for Alzheimer’s patients to help them performing daily life activities independently. The proposed assistance system is composed of a human activity recognition module, based on 3D skeletons data and transformer encoder, in order to monitor the patient behavior and an assistance module, based on reinforcement learning (RL), to detect anomalies in the patient behavior and provide alerts accordingly. Experiments carried out on the DemCare dataset proved the effectiveness of our RL-based assistance system compared to state-of-the-art methods.
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The authors would like to acknowledge the financial support of this work by grants from General Direction of Scientific Research (DGRST), Tunisia, under the ARUB program.
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Snoun, A., Bouchrika, T., Jemai, O. (2022). A Reinforcement Learning and Transformers Based Intelligent System for the Support of Alzheimer’s Patients in Daily Life Activities. In: Nguyen, N.T., Manolopoulos, Y., Chbeir, R., Kozierkiewicz, A., Trawiński, B. (eds) Computational Collective Intelligence. ICCCI 2022. Lecture Notes in Computer Science(), vol 13501. Springer, Cham. https://doi.org/10.1007/978-3-031-16014-1_42
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