Coding Prony's method in MATLAB and applying it to biomedical signal filtering

Background:The response of many biomedical systems can be modelled using a linear combination of damped exponential functions. The approximation parameters, based on equally spaced samples, can be obtained using Prony's method and its variants (e.g. the matrix pencil method). This paper provide...

Descripción completa

Detalles Bibliográficos
Autores: Fernández Rodríguez, Alfredo José, Santiago Rodrigo, Luis de|||0000-0002-0018-5805, López Guillén, María Elena, Rodríguez Ascariz, José Manuel|||0000-0002-6926-7526, Miguel Jiménez, Juan Manuel|||0000-0002-4641-5848, Boquete Vázquez, Luciano|||0000-0001-8591-6103
Tipo de recurso: artículo
Fecha de publicación:2018
País:España
Institución:Universidad de Alcalá (UAH)
Repositorio:e_Buah Biblioteca Digital Universidad de Alcalá
Idioma:inglés
OAI Identifier:oai:ebuah.uah.es:10017/37431
Acceso en línea:http://hdl.handle.net/10017/37431
https://dx.doi.org/10.1186/s12859-018-2473-y
Access Level:acceso abierto
Palabra clave:Prony"s method
Matrix pencil
Least squares
Total least squares
Multifocal evoked visual potentials
Multiple sclerosis
Electrónica
Electronics
id ES_5fc6d00bb8cedb5b2f38d47ab222bae7
oai_identifier_str oai:ebuah.uah.es:10017/37431
network_acronym_str ES
network_name_str España
repository_id_str
spelling Coding Prony's method in MATLAB and applying it to biomedical signal filteringFernández Rodríguez, Alfredo JoséSantiago Rodrigo, Luis de|||0000-0002-0018-5805López Guillén, María ElenaRodríguez Ascariz, José Manuel|||0000-0002-6926-7526Miguel Jiménez, Juan Manuel|||0000-0002-4641-5848Boquete Vázquez, Luciano|||0000-0001-8591-6103Prony"s methodMatrix pencilLeast squaresTotal least squaresMultifocal evoked visual potentialsMultiple sclerosisElectrónicaElectronicsBackground:The response of many biomedical systems can be modelled using a linear combination of damped exponential functions. The approximation parameters, based on equally spaced samples, can be obtained using Prony's method and its variants (e.g. the matrix pencil method). This paper provides a tutorial on the main polynomial Prony and matrix pencil methods and their implementation in MATLAB and analyses how they perform with synthetic and multifocal visual-evoked potential (mfVEP) signals. This paper briefly describes the theoretical basis of four polynomial Prony approximation methods: classic, least squares (LS), total least squares (TLS) and matrix pencil method (MPM). In each of these cases, implementation uses general MATLAB functions. The features of the various options are tested by approximating a set of synthetic mathematical functions and evaluating filtering performance in the Prony domain when applied to mfVEP signals to improve diagnosis of patients with multiple sclerosis (MS). Results:The code implemented does not achieve 100%-correct signal approximation and, of the methods tested, LS and MPM perform best. When filtering mfVEP records in the Prony domain, the value of the area under the receiver-operating-characteristic (ROC) curve is 0.7055 compared with 0.6538 obtained with the usual filtering method used for this type of signal (discrete Fourier transform low-pass filter with a cut-off frequency of 35 Hz). Conclusions:This paper reviews Prony's method in relation to signal filtering and approximation, provides the MATLAB code needed to implement the classic, LS, TLS and MPM methods, and tests their performance in biomedical signal filtering and function approximation. It emphasizes the importance of improving the computational methods used to implement the various methods described above.Universidad de AlcaláAgencia Estatal de Investigación20182018-11-26journal articlehttp://purl.org/coar/resource_type/c_6501NAhttp://purl.org/coar/version/c_be7fb7dd8ff6fe43info:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10017/37431https://dx.doi.org/10.1186/s12859-018-2473-yreponame:e_Buah Biblioteca Digital Universidad de Alcaláinstname:Universidad de Alcalá (UAH)InglésengUAH Not available GC2016-004Agencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016 DPI2017-88438-R INVESTIGACION DE LA TECNICA DE POTENCIALES EVOCADOS VISUALES MULTIFOCALES. APLICACION EN ESTUDIOS DE EVOLUCION DE ESCLEROSIS MULTIPLE Y EVALUACION DE MEDICAMENTOSopen accesshttp://purl.org/coar/access_right/c_abf2Attribution-NonCommercial-ShareAlike 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-sa/4.0/info:eu-repo/semantics/openAccessoai:ebuah.uah.es:10017/374312026-06-18T11:13:07Z
dc.title.none.fl_str_mv Coding Prony's method in MATLAB and applying it to biomedical signal filtering
title Coding Prony's method in MATLAB and applying it to biomedical signal filtering
spellingShingle Coding Prony's method in MATLAB and applying it to biomedical signal filtering
Fernández Rodríguez, Alfredo José
Prony"s method
Matrix pencil
Least squares
Total least squares
Multifocal evoked visual potentials
Multiple sclerosis
Electrónica
Electronics
title_short Coding Prony's method in MATLAB and applying it to biomedical signal filtering
title_full Coding Prony's method in MATLAB and applying it to biomedical signal filtering
title_fullStr Coding Prony's method in MATLAB and applying it to biomedical signal filtering
title_full_unstemmed Coding Prony's method in MATLAB and applying it to biomedical signal filtering
title_sort Coding Prony's method in MATLAB and applying it to biomedical signal filtering
dc.creator.none.fl_str_mv Fernández Rodríguez, Alfredo José
Santiago Rodrigo, Luis de|||0000-0002-0018-5805
López Guillén, María Elena
Rodríguez Ascariz, José Manuel|||0000-0002-6926-7526
Miguel Jiménez, Juan Manuel|||0000-0002-4641-5848
Boquete Vázquez, Luciano|||0000-0001-8591-6103
author Fernández Rodríguez, Alfredo José
author_facet Fernández Rodríguez, Alfredo José
Santiago Rodrigo, Luis de|||0000-0002-0018-5805
López Guillén, María Elena
Rodríguez Ascariz, José Manuel|||0000-0002-6926-7526
Miguel Jiménez, Juan Manuel|||0000-0002-4641-5848
Boquete Vázquez, Luciano|||0000-0001-8591-6103
author_role author
author2 Santiago Rodrigo, Luis de|||0000-0002-0018-5805
López Guillén, María Elena
Rodríguez Ascariz, José Manuel|||0000-0002-6926-7526
Miguel Jiménez, Juan Manuel|||0000-0002-4641-5848
Boquete Vázquez, Luciano|||0000-0001-8591-6103
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Prony"s method
Matrix pencil
Least squares
Total least squares
Multifocal evoked visual potentials
Multiple sclerosis
Electrónica
Electronics
topic Prony"s method
Matrix pencil
Least squares
Total least squares
Multifocal evoked visual potentials
Multiple sclerosis
Electrónica
Electronics
description Background:The response of many biomedical systems can be modelled using a linear combination of damped exponential functions. The approximation parameters, based on equally spaced samples, can be obtained using Prony's method and its variants (e.g. the matrix pencil method). This paper provides a tutorial on the main polynomial Prony and matrix pencil methods and their implementation in MATLAB and analyses how they perform with synthetic and multifocal visual-evoked potential (mfVEP) signals. This paper briefly describes the theoretical basis of four polynomial Prony approximation methods: classic, least squares (LS), total least squares (TLS) and matrix pencil method (MPM). In each of these cases, implementation uses general MATLAB functions. The features of the various options are tested by approximating a set of synthetic mathematical functions and evaluating filtering performance in the Prony domain when applied to mfVEP signals to improve diagnosis of patients with multiple sclerosis (MS). Results:The code implemented does not achieve 100%-correct signal approximation and, of the methods tested, LS and MPM perform best. When filtering mfVEP records in the Prony domain, the value of the area under the receiver-operating-characteristic (ROC) curve is 0.7055 compared with 0.6538 obtained with the usual filtering method used for this type of signal (discrete Fourier transform low-pass filter with a cut-off frequency of 35 Hz). Conclusions:This paper reviews Prony's method in relation to signal filtering and approximation, provides the MATLAB code needed to implement the classic, LS, TLS and MPM methods, and tests their performance in biomedical signal filtering and function approximation. It emphasizes the importance of improving the computational methods used to implement the various methods described above.
publishDate 2018
dc.date.none.fl_str_mv 2018
2018-11-26
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
NA
http://purl.org/coar/version/c_be7fb7dd8ff6fe43
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/10017/37431
https://dx.doi.org/10.1186/s12859-018-2473-y
url http://hdl.handle.net/10017/37431
https://dx.doi.org/10.1186/s12859-018-2473-y
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv UAH Not available GC2016-004
Agencia Estatal de Investigación http://dx.doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016 DPI2017-88438-R INVESTIGACION DE LA TECNICA DE POTENCIALES EVOCADOS VISUALES MULTIFOCALES. APLICACION EN ESTUDIOS DE EVOLUCION DE ESCLEROSIS MULTIPLE Y EVALUACION DE MEDICAMENTOS
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-ShareAlike 4.0 International
http://creativecommons.org/licenses/by-nc-sa/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-ShareAlike 4.0 International
http://creativecommons.org/licenses/by-nc-sa/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:e_Buah Biblioteca Digital Universidad de Alcalá
instname:Universidad de Alcalá (UAH)
instname_str Universidad de Alcalá (UAH)
reponame_str e_Buah Biblioteca Digital Universidad de Alcalá
collection e_Buah Biblioteca Digital Universidad de Alcalá
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869409242436337664
score 15,301603

Similares en LA Referencia