Detection and Alert of muscle fatigue considering a Surface Electromyography Chaotic Model

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dc.contributor.authorVictoria Herrera
dc.contributor.authorJesus Franklin Andrade Romero
dc.contributor.authorMauricio Améstegui
dc.coverage.spatialBolivia
dc.date.accessioned2026-03-22T16:09:47Z
dc.date.available2026-03-22T16:09:47Z
dc.date.issued2011
dc.descriptionCitaciones: 1
dc.description.abstractThis work propose a detection and alert algorithm for muscle fatigue in paraplegic patients undergoing electro-therapy sessions. The procedure is based on a mathematical chaotic model emulating physiological signals and Continuous Wavelet Transform (CWT). The chaotic model developed is based on a logistic map that provides suitable data accomplishing some physiological signal class patterns. The CWT was applied to signals generated by the model and the resulting vector was obtained through Total Wavelet Entropy (TWE). In this sense, the presented work propose a viable and practical alert and detection algorithm for muscle fatigue.
dc.identifier.doi10.1088/1742-6596/285/1/012046
dc.identifier.urihttps://doi.org/10.1088/1742-6596/285/1/012046
dc.identifier.urihttps://andeanlibrary.org/handle/123456789/56608
dc.language.isoen
dc.publisherIOP Publishing
dc.relation.ispartofJournal of Physics Conference Series
dc.sourceUniversidade Federal do ABC
dc.subjectElectromyography
dc.subjectChaotic
dc.subjectWavelet
dc.subjectComputer science
dc.subjectWavelet transform
dc.subjectContinuous wavelet transform
dc.subjectPattern recognition (psychology)
dc.subjectArtificial intelligence
dc.subjectSIGNAL (programming language)
dc.subjectApproximate entropy
dc.titleDetection and Alert of muscle fatigue considering a Surface Electromyography Chaotic Model
dc.typearticle

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