An Artificial Neuronal Network Approach to Diagnosis of Attention Deficit Hyperactivity Disorder

Detalhes bibliográficos
Autor(a) principal: Pereira, Sónia
Data de Publicação: 2014
Outros Autores: Gomes, Sabino, Vicente, Henrique, Ribeiro, Jorge, Abelha, António, Novais, Paulo, Machado, José, Neves, José
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10174/12113
Resumo: On the one hand about 3% to 12% of school-aged children present Attention Deficit Hyperactivity Disorder (ADHD), a situation that is characterized by attention deficit, impulsiveness and restlessness, coming from a change in the neurotransmitters of the central nervous system, caused by psychological messes, environment effects or genetic characteristics. One the other hand, when one´s aim is the prediction of ADHD in children and teenagers, we need to be able to handle incomplete or default data, like the one in ActiGraph´s images that may exhibit potential disordered sleep patterns. Indeed, using a new approach to knowledge representation and reasoning based on Logic Programming, complemented with a computational framework based on Artificial Neural Networks, ActiGraph’s pioneering actigraphy monitoring systems may deliver, on the fly, real world information about sleep/wake behavior, circadian rhythms, daytime physical activity, and environmental light intensity for the study and clinical assessment of sleep disorders and the relationship between sleep and chronic disease.
id RCAP_03a2022a5c4f2ea29a55cee5091c1b29
oai_identifier_str oai:dspace.uevora.pt:10174/12113
network_acronym_str RCAP
network_name_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository_id_str
spelling An Artificial Neuronal Network Approach to Diagnosis of Attention Deficit Hyperactivity DisorderActiGraph´s ImagesAttention Deficit Hyperactivity DisorderLogic ProgrammingKnowledge Representation and ReasoningArtificial Neuronal NetworksOn the one hand about 3% to 12% of school-aged children present Attention Deficit Hyperactivity Disorder (ADHD), a situation that is characterized by attention deficit, impulsiveness and restlessness, coming from a change in the neurotransmitters of the central nervous system, caused by psychological messes, environment effects or genetic characteristics. One the other hand, when one´s aim is the prediction of ADHD in children and teenagers, we need to be able to handle incomplete or default data, like the one in ActiGraph´s images that may exhibit potential disordered sleep patterns. Indeed, using a new approach to knowledge representation and reasoning based on Logic Programming, complemented with a computational framework based on Artificial Neural Networks, ActiGraph’s pioneering actigraphy monitoring systems may deliver, on the fly, real world information about sleep/wake behavior, circadian rhythms, daytime physical activity, and environmental light intensity for the study and clinical assessment of sleep disorders and the relationship between sleep and chronic disease.Institute of Electrical and Electronics Engineers, Inc.2014-12-29T17:44:48Z2014-12-292014-10-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10174/12113http://hdl.handle.net/10174/12113engPereira, S., Gomes, S., Vicente, H., Ribeiro, J., Abelha, A., Novais, P., Machado, J., & Neves, J., An Artificial Neuronal Network Approach to Diagnosis of Attention Deficit Hyperactivity Disorder. In Proceedings of 2014 IEEE International Conference on Imaging Systems and Techniques (IST 2014), pp. 410–415, Institute of Electrical and Electronics Engineers, Inc., New Jersey, USA, 2014.ISBN: 978-1-4799-6748-3Departamento de Químicandndhvicente@uevora.ptjribeiro@estg.ipvc.ptabelha@di.uminho.ptpjon@di.uminho.ptjmac@di.uminho.ptjneves@di.uminho.ptProceedings of 2014 IEEE International Conference on Imaging Systems and Techniques (IST 2014)559Pereira, SóniaGomes, SabinoVicente, HenriqueRibeiro, JorgeAbelha, AntónioNovais, PauloMachado, JoséNeves, Joséinfo: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:RCAAP2023-08-08T04:06:29ZPortal AgregadorONG
dc.title.none.fl_str_mv An Artificial Neuronal Network Approach to Diagnosis of Attention Deficit Hyperactivity Disorder
title An Artificial Neuronal Network Approach to Diagnosis of Attention Deficit Hyperactivity Disorder
spellingShingle An Artificial Neuronal Network Approach to Diagnosis of Attention Deficit Hyperactivity Disorder
Pereira, Sónia
ActiGraph´s Images
Attention Deficit Hyperactivity Disorder
Logic Programming
Knowledge Representation and Reasoning
Artificial Neuronal Networks
title_short An Artificial Neuronal Network Approach to Diagnosis of Attention Deficit Hyperactivity Disorder
title_full An Artificial Neuronal Network Approach to Diagnosis of Attention Deficit Hyperactivity Disorder
title_fullStr An Artificial Neuronal Network Approach to Diagnosis of Attention Deficit Hyperactivity Disorder
title_full_unstemmed An Artificial Neuronal Network Approach to Diagnosis of Attention Deficit Hyperactivity Disorder
title_sort An Artificial Neuronal Network Approach to Diagnosis of Attention Deficit Hyperactivity Disorder
author Pereira, Sónia
author_facet Pereira, Sónia
Gomes, Sabino
Vicente, Henrique
Ribeiro, Jorge
Abelha, António
Novais, Paulo
Machado, José
Neves, José
author_role author
author2 Gomes, Sabino
Vicente, Henrique
Ribeiro, Jorge
Abelha, António
Novais, Paulo
Machado, José
Neves, José
author2_role author
author
author
author
author
author
author
dc.contributor.author.fl_str_mv Pereira, Sónia
Gomes, Sabino
Vicente, Henrique
Ribeiro, Jorge
Abelha, António
Novais, Paulo
Machado, José
Neves, José
dc.subject.por.fl_str_mv ActiGraph´s Images
Attention Deficit Hyperactivity Disorder
Logic Programming
Knowledge Representation and Reasoning
Artificial Neuronal Networks
topic ActiGraph´s Images
Attention Deficit Hyperactivity Disorder
Logic Programming
Knowledge Representation and Reasoning
Artificial Neuronal Networks
description On the one hand about 3% to 12% of school-aged children present Attention Deficit Hyperactivity Disorder (ADHD), a situation that is characterized by attention deficit, impulsiveness and restlessness, coming from a change in the neurotransmitters of the central nervous system, caused by psychological messes, environment effects or genetic characteristics. One the other hand, when one´s aim is the prediction of ADHD in children and teenagers, we need to be able to handle incomplete or default data, like the one in ActiGraph´s images that may exhibit potential disordered sleep patterns. Indeed, using a new approach to knowledge representation and reasoning based on Logic Programming, complemented with a computational framework based on Artificial Neural Networks, ActiGraph’s pioneering actigraphy monitoring systems may deliver, on the fly, real world information about sleep/wake behavior, circadian rhythms, daytime physical activity, and environmental light intensity for the study and clinical assessment of sleep disorders and the relationship between sleep and chronic disease.
publishDate 2014
dc.date.none.fl_str_mv 2014-12-29T17:44:48Z
2014-12-29
2014-10-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10174/12113
http://hdl.handle.net/10174/12113
url http://hdl.handle.net/10174/12113
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Pereira, S., Gomes, S., Vicente, H., Ribeiro, J., Abelha, A., Novais, P., Machado, J., & Neves, J., An Artificial Neuronal Network Approach to Diagnosis of Attention Deficit Hyperactivity Disorder. In Proceedings of 2014 IEEE International Conference on Imaging Systems and Techniques (IST 2014), pp. 410–415, Institute of Electrical and Electronics Engineers, Inc., New Jersey, USA, 2014.
ISBN: 978-1-4799-6748-3
Departamento de Química
nd
nd
hvicente@uevora.pt
jribeiro@estg.ipvc.pt
abelha@di.uminho.pt
pjon@di.uminho.pt
jmac@di.uminho.pt
jneves@di.uminho.pt
Proceedings of 2014 IEEE International Conference on Imaging Systems and Techniques (IST 2014)
559
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers, Inc.
publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers, Inc.
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1777304597522546688

Registros relacionados