Study of the electromyographic signal dynamic behavior in Amyotrophic Lateral Sclerosis (ALS)

Detalhes bibliográficos
Autor(a) principal: Santos, Maria Marta Oliveira Antunes dos
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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spelling 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
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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
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
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reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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