A framework for AI-driven neurorehabilitation training: the profiling challenge

Bibliographic Details
Main Author: Rodrigues, Pedro Alexandre Gomes
Publication Date: 2022
Format: Master thesis
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10400.13/4890
Summary: Cognitive decline is a common sign that a person is ageing. However, abnormal cases can lead to dementia, affecting daily living activities and independent functioning. It is a leading cause of disability and death. Its prevention is a global health priority. One way to address cognitive decline is to undergo cognitive rehabilitation. Cognitive rehabilitation aims to restore or mitigate the symptoms of a cognitive disability, increasing the quality of life for the patient. However, cognitive rehabilitation is stuck to clinical environments and logistics, leading to a suboptimal set of expansive tools that is hard to accommodate every patient’s needs. The BRaNT project aims to create a tool that mitigates this problem. The NeuroAIreh@b is a rehabilitation tool developed within a framework that combines neuropsychological assessments, neurorehabilitation procedures, artificial intelligence and game design, composing a tool that is easy to set up in a clinical environment and accessible to adapt to every patient’s needs. Among all the challenges within NeuroAlreh@b, one focuses on representing a cognitive profile through the aggregation of multiple neuropsychological assessments. To test this possibility, we will need data from patients currently unavailable. In the first part of this master’s project, study the possibility of aggregating neuropsychological assessments for the case of Alzheimer’s disease using the Alzheimer’s Disease Neuroimaging Initiative database. This database contains a vast collection of images and neuropsychological assessments that will serve as a baseline for the NeuroAlreh@b when the time comes. In the second part of this project, we set up a computational system to run all the artificial intelligence models and simulations required for the BRaNT project. The system allocates a database and a webserver to serve all the required pages for the project.
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spelling A framework for AI-driven neurorehabilitation training: the profiling challengeDriven neurorehabilitation trainingNeurorehabilitation trainingCognitive declineCognitive rehabilitationDeclínio cognitivoReabilitação cognitivaInformatics Engineering.Faculdade de Ciências Exatas e da EngenhariaCognitive decline is a common sign that a person is ageing. However, abnormal cases can lead to dementia, affecting daily living activities and independent functioning. It is a leading cause of disability and death. Its prevention is a global health priority. One way to address cognitive decline is to undergo cognitive rehabilitation. Cognitive rehabilitation aims to restore or mitigate the symptoms of a cognitive disability, increasing the quality of life for the patient. However, cognitive rehabilitation is stuck to clinical environments and logistics, leading to a suboptimal set of expansive tools that is hard to accommodate every patient’s needs. The BRaNT project aims to create a tool that mitigates this problem. The NeuroAIreh@b is a rehabilitation tool developed within a framework that combines neuropsychological assessments, neurorehabilitation procedures, artificial intelligence and game design, composing a tool that is easy to set up in a clinical environment and accessible to adapt to every patient’s needs. Among all the challenges within NeuroAlreh@b, one focuses on representing a cognitive profile through the aggregation of multiple neuropsychological assessments. To test this possibility, we will need data from patients currently unavailable. In the first part of this master’s project, study the possibility of aggregating neuropsychological assessments for the case of Alzheimer’s disease using the Alzheimer’s Disease Neuroimaging Initiative database. This database contains a vast collection of images and neuropsychological assessments that will serve as a baseline for the NeuroAlreh@b when the time comes. In the second part of this project, we set up a computational system to run all the artificial intelligence models and simulations required for the BRaNT project. The system allocates a database and a webserver to serve all the required pages for the project.Fermé, Eduardo LeopoldoBermúdez I Badia, SergiDigitUMaRodrigues, Pedro Alexandre Gomes2023-01-09T12:27:14Z2022-11-182022-11-18T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10400.13/4890urn:tid:203145690enginfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-02-24T16:54:54Zoai:digituma.uma.pt:10400.13/4890Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T20:42:48.910763Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv A framework for AI-driven neurorehabilitation training: the profiling challenge
title A framework for AI-driven neurorehabilitation training: the profiling challenge
spellingShingle A framework for AI-driven neurorehabilitation training: the profiling challenge
Rodrigues, Pedro Alexandre Gomes
Driven neurorehabilitation training
Neurorehabilitation training
Cognitive decline
Cognitive rehabilitation
Declínio cognitivo
Reabilitação cognitiva
Informatics Engineering
.
Faculdade de Ciências Exatas e da Engenharia
title_short A framework for AI-driven neurorehabilitation training: the profiling challenge
title_full A framework for AI-driven neurorehabilitation training: the profiling challenge
title_fullStr A framework for AI-driven neurorehabilitation training: the profiling challenge
title_full_unstemmed A framework for AI-driven neurorehabilitation training: the profiling challenge
title_sort A framework for AI-driven neurorehabilitation training: the profiling challenge
author Rodrigues, Pedro Alexandre Gomes
author_facet Rodrigues, Pedro Alexandre Gomes
author_role author
dc.contributor.none.fl_str_mv Fermé, Eduardo Leopoldo
Bermúdez I Badia, Sergi
DigitUMa
dc.contributor.author.fl_str_mv Rodrigues, Pedro Alexandre Gomes
dc.subject.por.fl_str_mv Driven neurorehabilitation training
Neurorehabilitation training
Cognitive decline
Cognitive rehabilitation
Declínio cognitivo
Reabilitação cognitiva
Informatics Engineering
.
Faculdade de Ciências Exatas e da Engenharia
topic Driven neurorehabilitation training
Neurorehabilitation training
Cognitive decline
Cognitive rehabilitation
Declínio cognitivo
Reabilitação cognitiva
Informatics Engineering
.
Faculdade de Ciências Exatas e da Engenharia
description Cognitive decline is a common sign that a person is ageing. However, abnormal cases can lead to dementia, affecting daily living activities and independent functioning. It is a leading cause of disability and death. Its prevention is a global health priority. One way to address cognitive decline is to undergo cognitive rehabilitation. Cognitive rehabilitation aims to restore or mitigate the symptoms of a cognitive disability, increasing the quality of life for the patient. However, cognitive rehabilitation is stuck to clinical environments and logistics, leading to a suboptimal set of expansive tools that is hard to accommodate every patient’s needs. The BRaNT project aims to create a tool that mitigates this problem. The NeuroAIreh@b is a rehabilitation tool developed within a framework that combines neuropsychological assessments, neurorehabilitation procedures, artificial intelligence and game design, composing a tool that is easy to set up in a clinical environment and accessible to adapt to every patient’s needs. Among all the challenges within NeuroAlreh@b, one focuses on representing a cognitive profile through the aggregation of multiple neuropsychological assessments. To test this possibility, we will need data from patients currently unavailable. In the first part of this master’s project, study the possibility of aggregating neuropsychological assessments for the case of Alzheimer’s disease using the Alzheimer’s Disease Neuroimaging Initiative database. This database contains a vast collection of images and neuropsychological assessments that will serve as a baseline for the NeuroAlreh@b when the time comes. In the second part of this project, we set up a computational system to run all the artificial intelligence models and simulations required for the BRaNT project. The system allocates a database and a webserver to serve all the required pages for the project.
publishDate 2022
dc.date.none.fl_str_mv 2022-11-18
2022-11-18T00:00:00Z
2023-01-09T12:27:14Z
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