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dc.contributor.authorSarlabous Uranga, Leonardo
dc.contributor.authorTorres Cebrián, Abel
dc.contributor.authorFiz Fernández, José Antonio
dc.contributor.authorMorera, Josep
dc.contributor.authorJané Campos, Raimon
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial
dc.contributor.otherInstitut de Bioenginyeria de Catalunya
dc.identifier.citationSarlabous, 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.description.abstractThe 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.extent10 p.
dc.subjectÀrees temàtiques de la UPC::Enginyeria biomèdica::Electrònica biomèdica
dc.subjectÀrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::Bioinformàtica
dc.subject.lcshElectromyography--Data processing
dc.subject.lcshRespiratory organs--Diseases--Research
dc.subject.lcshMuscle strength--Research
dc.subject.lcshRespiratory muscles
dc.subject.otherMuscle force
dc.subject.otherRespiratory muscles
dc.titleIndex for estimation of muscle force from mechanomyogrpahy based on the Lempel-Ziv algorithm
dc.subject.lemacRespiració -- Mesurament
dc.subject.lemacProcessament digital -- Biomedicina
dc.subject.lemacPulmons -- Malalties -- Mètodes estadístics
dc.subject.lemacTractament del senyal
dc.contributor.groupUniversitat Politècnica de Catalunya. SISBIO - Senyals i Sistemes Biomèdics
dc.description.peerreviewedPeer Reviewed
dc.rights.accessRestricted access - publisher's policy
dc.description.versionPostprint (published version)
local.citation.authorSarlabous, L.; Torres, A.; Fiz, J.; Morera, J.; Jane, R.
local.citation.publicationNameJournal of electromyography and kinesiology

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