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Authors: Yuri Almeida 1 ; 2 ; Manisha Sirsat 1 ; Sergi Bermúdez i Badia 3 ; 2 and Eduardo Fermé 1 ; 2

Affiliations: 1 NOVA-LINCS, Portugal ; 2 Universidade da Madeira, Portugal ; 3 Madeira Interactive Technologies Institute, Portugal

Keyword(s): Long Term Care in Cognitive Neurorehabilitation, Profiling Challenges, Machine Learning, Belief Revision.

Abstract: One of the health clinic challenges is rehabilitation therapy cognitive impairment that can happen after brain injury, dementia and in normal cognitive decline due to aging. Current cognitive rehabilitation therapy has been shown to be the most effective way to address this problem. However, a) it is not adaptive for every patient, b) it has a high cost, and c) it is usually implemented in clinical environments. The Task Generator (TG) is a free tool for the generation of cognitive training tasks. However, TG is not designed to adapt and monitor the cognitive progress of the patient. Hence, we propose in the BRaNT project an enhancement of TG with belief revision and machine learning techniques, gamification and remote monitoring capabilities to enable health professionals to provide a long-term personalized cognitive rehabilitation therapy at home. The BRaNT is an interdisciplinary effort that addresses scientific limitations of current practices as well as provides solutions toward s the sustainability of health systems and contributes towards the improvement of quality of life of patients. This paper proposes the AI-Rehab framework for the BRaNT, explains profiling challenge in the situation of insufficient data and presents an alternate AI solutions which might be applicable once enough data is available. (More)

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Paper citation in several formats:
Almeida, Y.; Sirsat, M.; Bermúdez i Badia, S. and Fermé, E. (2020). AI-Rehab: A Framework for AI Driven Neurorehabilitation Training - The Profiling Challenge. In Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies - Cognitive Health IT, ISBN 978-989-758-398-8; ISSN 2184-4305, pages 845-853. DOI: 10.5220/0009369108450853

@conference{cognitive health it20,
author={Yuri Almeida. and Manisha Sirsat. and Sergi {Bermúdez i Badia}. and Eduardo Fermé.},
title={AI-Rehab: A Framework for AI Driven Neurorehabilitation Training - The Profiling Challenge},
booktitle={Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies - Cognitive Health IT,},
year={2020},
pages={845-853},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009369108450853},
isbn={978-989-758-398-8},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies - Cognitive Health IT,
TI - AI-Rehab: A Framework for AI Driven Neurorehabilitation Training - The Profiling Challenge
SN - 978-989-758-398-8
IS - 2184-4305
AU - Almeida, Y.
AU - Sirsat, M.
AU - Bermúdez i Badia, S.
AU - Fermé, E.
PY - 2020
SP - 845
EP - 853
DO - 10.5220/0009369108450853