Assessing Levodopa Effectiveness in Parkison's Disease during Gait Using Electroencephalogram and Machine Learning

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.creatorPires, Rafael Gonçalves-
Autor(es): dc.creatorPereira, Clayton Reginaldo-
Autor(es): dc.creatorPenedo, Tiago-
Autor(es): dc.creatorPapa, João Paulo-
Autor(es): dc.creatorRoder, Mateus-
Autor(es): dc.creatorBarbieri, Fabio Augusto-
Data de aceite: dc.date.accessioned2025-08-21T16:24:21Z-
Data de disponibilização: dc.date.available2025-08-21T16:24:21Z-
Data de envio: dc.date.issued2025-04-29-
Data de envio: dc.date.issued2023-12-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1109/IWSSIP62407.2024.10634032-
Fonte completa do material: dc.identifierhttps://hdl.handle.net/11449/307286-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/307286-
Descrição: dc.descriptionThis study aims to investigate the temporal effects of levodopa, a fundamental medication for treating Parkinson's disease, a neurodegenerative condition that causes diverse motor alterations as it progresses. Our goal is to identify, at some specific intervals after the first levodopa intake, whether a machine learning approach can determine the effectiveness of that drug during gait exercises using electroencephalogram signals. The analysis will focus on identifying specific temporal patterns associated with levodopa administration and its impact on brain electrical activities during gait. We observed the proposed approach can accurately identify drug administration 90 minutes after the first levodopa intake, showing machine learning techniques are promising to cope with such a task.-
Descrição: dc.descriptionSão Paulo State University Departament of Computing, SP-
Descrição: dc.descriptionSão Paulo State University Departament of Physical Education, SP-
Descrição: dc.descriptionSão Paulo State University Departament of Computing, SP-
Descrição: dc.descriptionSão Paulo State University Departament of Physical Education, SP-
Idioma: dc.languageen-
Relação: dc.relationInternational Conference on Systems, Signals, and Image Processing-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectDeep Learning-
Palavras-chave: dc.subjectElectroencephalogram-
Palavras-chave: dc.subjectParkinson's Disease-
Palavras-chave: dc.subjectSignal Analysis-
Título: dc.titleAssessing Levodopa Effectiveness in Parkison's Disease during Gait Using Electroencephalogram and Machine Learning-
Tipo de arquivo: dc.typeaula digital-
Aparece nas coleções:Repositório Institucional - Unesp

Não existem arquivos associados a este item.