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

Detalhes bibliográficos
Autor(a) principal: Rodrigues, Pedro Alexandre Gomes
Data de Publicação: 2022
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.13/4890
Resumo: 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 EngenhariaDomínio/Área Científica::Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e InformáticaDomínio/Área Científica::Ciências Médicas::Outras Ciências MédicasCognitive 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.O declínio cognitivo é um sinal comum de que uma pessoa está a envelhecer. No entanto, casos anormais podem levar à demência, afetando as atividades diárias e funcionamento independente. Demência é uma das principais causas de incapacidade e morte. Fazendo da sua prevenção uma prioridade para a saúde global. Uma forma de lidar com o declínio cognitivo é submeter-se à reabilitação cognitiva. A reabilitação cognitiva visa restaurar ou mitigar os sintomas de uma deficiência cognitiva, aumentando a qualidade de vida do paciente. No entanto, a reabilitação cognitiva está presa a ambientes clínicos e logística, levando a um conjunto sub-ideal de ferramentas com custos elevados e complicadas de acomodar as necessidades de cada paciente. O projeto BRaNT visa criar uma ferramenta que atenue este problema. O NeuroAIreh@b é uma ferramenta de reabilitação desenvolvida num quadro que combina avaliações neuropsicológicas, reabilitação, inteligência artificial e design de jogos, compondo uma ferramenta fácil de adaptar a um ambiente clínico e acessível para se adaptar às necessidades de cada paciente. Entre todos os desafios dentro de NeuroAlreh@b, foca-se em representar um perfil cognitivo através da agregação de múltiplas avaliações neuropsicológicas. Para testar esta possibilidade, precisaremos de dados de pacientes, que atualmente não temos. Na primeira parte do projeto deste mestrado, vamos testar a possibilidade de agregar avaliações neuropsicológicas para o caso da doença de Alzheimer utilizando a base de dados da Iniciativa de Neuroimagem da Doença de Alzheimer. Esta base de dados contém uma vasta coleção de imagens e avaliações neuropsicológicas que servirão de base para o NeuroAlreh@b quando chegar a hora. Na segunda parte deste projeto, vamos criar um sistema informático para executar todos os modelos e simulações de inteligência artificial necessários para o projeto BRaNT. O sistema também irá alocar uma base de dados e um webserver para servir todas as páginas necessárias para o projeto.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/10400.13/4890TID:203145690enginfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-01-15T03:30:42Zoai:digituma.uma.pt:10400.13/4890Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T16:31:41.984726Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
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
Domínio/Área Científica::Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
Domínio/Área Científica::Ciências Médicas::Outras Ciências Médicas
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
Domínio/Área Científica::Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
Domínio/Área Científica::Ciências Médicas::Outras Ciências Médicas
topic Driven neurorehabilitation training
Neurorehabilitation training
Cognitive decline
Cognitive rehabilitation
Declínio cognitivo
Reabilitação cognitiva
Informatics Engineering
.
Faculdade de Ciências Exatas e da Engenharia
Domínio/Área Científica::Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
Domínio/Área Científica::Ciências Médicas::Outras Ciências Médicas
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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TID:203145690
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