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Index for estimation of muscle force from mechanomyogrpahy based on the Lempel-Ziv algorithm
dc.contributor.author | Sarlabous Uranga, Leonardo |
dc.contributor.author | Torres Cebrián, Abel |
dc.contributor.author | Fiz Fernández, José Antonio |
dc.contributor.author | Morera, Josep |
dc.contributor.author | Jané Campos, Raimon |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial |
dc.contributor.other | Institut de Bioenginyeria de Catalunya |
dc.date.accessioned | 2014-01-07T09:24:08Z |
dc.date.created | 2013-02-19 |
dc.date.issued | 2013-02-19 |
dc.identifier.citation | Sarlabous, L. [et al.]. Index for estimation of muscle force from mechanomyogrpahy based on the Lempel-Ziv algorithm. "Journal of electromyography and kinesiology", 19 Febrer 2013, vol. 23, núm. 3, p. 548-557. |
dc.identifier.issn | 1050-6411 |
dc.identifier.uri | http://hdl.handle.net/2117/21147 |
dc.description.abstract | The study of the amplitude of respiratory muscle mechanomyographic (MMG) signals could be useful in clinical practice as an alternative non-invasive technique to assess respiratory muscle strength. The MMG signal is stochastic in nature, and its amplitude is usually estimated by means of the average rectified value (ARV) or the root mean square (RMS) of the signal. Both parameters can be used to estimate MMG activity, as they correlate well with muscle force. These estimations are, however, greatly affected by the presence of structured impulsive noise that overlaps in frequency with the MMG signal. In this paper, we present a method for assessing muscle activity based on the Lempel–Ziv algorithm: the Multistate Lempel–Ziv (MLZ) index. The behaviour of the MLZ index was tested with synthesised signals, with various amplitude distributions and degrees of complexity, and with recorded diaphragm MMG signals. We found that this index, like the ARV and RMS parameters, is positively correlated with changes in amplitude of the diaphragm MMG components, but is less affected by components that have non-random behaviour (like structured impulsive noise). Therefore, the MLZ index could provide more information to assess the MMG–force relationship. |
dc.format.extent | 10 p. |
dc.language.iso | eng |
dc.subject | Àrees temàtiques de la UPC::Enginyeria biomèdica::Electrònica biomèdica |
dc.subject | Àrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::Bioinformàtica |
dc.subject.lcsh | Electromyography--Data processing |
dc.subject.lcsh | Respiratory organs--Diseases--Research |
dc.subject.lcsh | Muscle strength--Research |
dc.subject.lcsh | Respiratory muscles |
dc.subject.other | Mechanomyography |
dc.subject.other | Electromyography |
dc.subject.other | Muscle force |
dc.subject.other | Lempel-Ziv |
dc.subject.other | Diaphragm |
dc.subject.other | Respiratory muscles |
dc.title | Index for estimation of muscle force from mechanomyogrpahy based on the Lempel-Ziv algorithm |
dc.type | Article |
dc.subject.lemac | Respiració -- Mesurament |
dc.subject.lemac | Processament digital -- Biomedicina |
dc.subject.lemac | Pulmons -- Malalties -- Mètodes estadístics |
dc.subject.lemac | Tractament del senyal |
dc.contributor.group | Universitat Politècnica de Catalunya. SISBIO - Senyals i Sistemes Biomèdics |
dc.identifier.doi | 10.1016/j.jelekin.2012.12.007 |
dc.description.peerreviewed | Peer Reviewed |
dc.relation.publisherversion | http://www.jelectromyographykinesiology.com/article/S1050-6411%2813%2900019-9/fulltext |
dc.rights.access | Restricted access - publisher's policy |
local.identifier.drac | 12953475 |
dc.description.version | Postprint (published version) |
dc.date.lift | 10000-01-01 |
local.citation.author | Sarlabous, L.; Torres, A.; Fiz, J.; Morera, J.; Jane, R. |
local.citation.publicationName | Journal of electromyography and kinesiology |
local.citation.volume | 23 |
local.citation.number | 3 |
local.citation.startingPage | 548 |
local.citation.endingPage | 557 |
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