Study of the electromyographic signal dynamic behavior in Amyotrophic Lateral Sclerosis (ALS)
Autor(a) principal: | |
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Data de Publicação: | 2014 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10362/14461 |
Resumo: | Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease characterized by motor neurons degeneration, which reduces muscular force, being very difficult to diagnose. Mathematical methods are used in order to analyze the surface electromiographic signal’s dynamic behavior (Fractal Dimension (FD) and Multiscale Entropy (MSE)), evaluate different muscle group’s synchronization (Coherence and Phase Locking Factor (PLF)) and to evaluate the signal’s complexity (Lempel-Ziv (LZ) techniques and Detrended Fluctuation Analysis (DFA)). Surface electromiographic signal acquisitions were performed in upper limb muscles, being the analysis executed for instants of contraction for ipsilateral acquisitions for patients and control groups. Results from LZ, DFA and MSE analysis present capability to distinguish between the patient group and the control group, whereas coherence, PLF and FD algorithms present results very similar for both groups. LZ, DFA and MSE algorithms appear then to be a good measure of corticospinal pathways integrity. A classification algorithm was applied to the results in combination with extracted features from the surface electromiographic signal, with an accuracy percentage higher than 70% for 118 combinations for at least one classifier. The classification results demonstrate capability to distinguish members between patients and control groups. These results can demonstrate a major importance in the disease diagnose, once surface electromyography (sEMG) may be used as an auxiliary diagnose method. |
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Study of the electromyographic signal dynamic behavior in Amyotrophic Lateral Sclerosis (ALS)Amyotrophic Lateral Sclerosis (ALS)CoherencePhase Locking Factor (PLF)Fractal Dimension (FD)Lempel-Ziv (LZ)Detrended Fluctuation Analysis (DFA)Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease characterized by motor neurons degeneration, which reduces muscular force, being very difficult to diagnose. Mathematical methods are used in order to analyze the surface electromiographic signal’s dynamic behavior (Fractal Dimension (FD) and Multiscale Entropy (MSE)), evaluate different muscle group’s synchronization (Coherence and Phase Locking Factor (PLF)) and to evaluate the signal’s complexity (Lempel-Ziv (LZ) techniques and Detrended Fluctuation Analysis (DFA)). Surface electromiographic signal acquisitions were performed in upper limb muscles, being the analysis executed for instants of contraction for ipsilateral acquisitions for patients and control groups. Results from LZ, DFA and MSE analysis present capability to distinguish between the patient group and the control group, whereas coherence, PLF and FD algorithms present results very similar for both groups. LZ, DFA and MSE algorithms appear then to be a good measure of corticospinal pathways integrity. A classification algorithm was applied to the results in combination with extracted features from the surface electromiographic signal, with an accuracy percentage higher than 70% for 118 combinations for at least one classifier. The classification results demonstrate capability to distinguish members between patients and control groups. These results can demonstrate a major importance in the disease diagnose, once surface electromyography (sEMG) may be used as an auxiliary diagnose method.Quintão, CarlaGamboa, HugoRUNSantos, Maria Marta Oliveira Antunes dos2015-03-09T16:55:16Z2014-102015-032014-10-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/14461enginfo: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:RCAAP2024-03-11T03:49:37Zoai:run.unl.pt:10362/14461Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:21:50.784783Repositório 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 |
Study of the electromyographic signal dynamic behavior in Amyotrophic Lateral Sclerosis (ALS) |
title |
Study of the electromyographic signal dynamic behavior in Amyotrophic Lateral Sclerosis (ALS) |
spellingShingle |
Study of the electromyographic signal dynamic behavior in Amyotrophic Lateral Sclerosis (ALS) Santos, Maria Marta Oliveira Antunes dos Amyotrophic Lateral Sclerosis (ALS) Coherence Phase Locking Factor (PLF) Fractal Dimension (FD) Lempel-Ziv (LZ) Detrended Fluctuation Analysis (DFA) |
title_short |
Study of the electromyographic signal dynamic behavior in Amyotrophic Lateral Sclerosis (ALS) |
title_full |
Study of the electromyographic signal dynamic behavior in Amyotrophic Lateral Sclerosis (ALS) |
title_fullStr |
Study of the electromyographic signal dynamic behavior in Amyotrophic Lateral Sclerosis (ALS) |
title_full_unstemmed |
Study of the electromyographic signal dynamic behavior in Amyotrophic Lateral Sclerosis (ALS) |
title_sort |
Study of the electromyographic signal dynamic behavior in Amyotrophic Lateral Sclerosis (ALS) |
author |
Santos, Maria Marta Oliveira Antunes dos |
author_facet |
Santos, Maria Marta Oliveira Antunes dos |
author_role |
author |
dc.contributor.none.fl_str_mv |
Quintão, Carla Gamboa, Hugo RUN |
dc.contributor.author.fl_str_mv |
Santos, Maria Marta Oliveira Antunes dos |
dc.subject.por.fl_str_mv |
Amyotrophic Lateral Sclerosis (ALS) Coherence Phase Locking Factor (PLF) Fractal Dimension (FD) Lempel-Ziv (LZ) Detrended Fluctuation Analysis (DFA) |
topic |
Amyotrophic Lateral Sclerosis (ALS) Coherence Phase Locking Factor (PLF) Fractal Dimension (FD) Lempel-Ziv (LZ) Detrended Fluctuation Analysis (DFA) |
description |
Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease characterized by motor neurons degeneration, which reduces muscular force, being very difficult to diagnose. Mathematical methods are used in order to analyze the surface electromiographic signal’s dynamic behavior (Fractal Dimension (FD) and Multiscale Entropy (MSE)), evaluate different muscle group’s synchronization (Coherence and Phase Locking Factor (PLF)) and to evaluate the signal’s complexity (Lempel-Ziv (LZ) techniques and Detrended Fluctuation Analysis (DFA)). Surface electromiographic signal acquisitions were performed in upper limb muscles, being the analysis executed for instants of contraction for ipsilateral acquisitions for patients and control groups. Results from LZ, DFA and MSE analysis present capability to distinguish between the patient group and the control group, whereas coherence, PLF and FD algorithms present results very similar for both groups. LZ, DFA and MSE algorithms appear then to be a good measure of corticospinal pathways integrity. A classification algorithm was applied to the results in combination with extracted features from the surface electromiographic signal, with an accuracy percentage higher than 70% for 118 combinations for at least one classifier. The classification results demonstrate capability to distinguish members between patients and control groups. These results can demonstrate a major importance in the disease diagnose, once surface electromyography (sEMG) may be used as an auxiliary diagnose method. |
publishDate |
2014 |
dc.date.none.fl_str_mv |
2014-10 2014-10-01T00:00:00Z 2015-03-09T16:55:16Z 2015-03 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10362/14461 |
url |
http://hdl.handle.net/10362/14461 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
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 |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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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 |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799137858726920192 |