Sensor Network for Bipolar sEMG Detection and Angular Measurement for the Characterization of Foot Drop Pathology

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dc.contributor.authorMurrugarra, Cecilia
dc.contributor.authorNoriega Alvarez, Santiago
dc.date.accessioned2021-03-03T19:34:24Z
dc.date.available2021-03-03T19:34:24Z
dc.date.issued2020
dc.description.abstractenglishAbstract. The aim of this research work was to develop an embedded electronic sensing system, portable, wireless and wearable prototype that allowed to perform bipolar surface electromyography (sEMG) detection for the Tibialis Anterior (TA) and Peroneus Longus (PL) muscles and measure the angular displacement of the ankle-foot joint for the characterization of Foot Drop (FD) pathology through the establishment of a sensor network. Two Sensor Units were developed around a CPU responsible for receiving the sensors measurements in order to assemble data packets for transmission. The bipolar sEMG detection is carried out through an analogous conditioning module. The sEMG architecture allows to obtain the raw, rectified, and the envelope of the muscular signals. The angular displacement measurement consists in an inertial measurement system. A statistical analysis to validate the precision of the measurements regard to commercial instruments, showing a MSE of 5, 27% for the sEMG and a mean error ≤ }1.5 ◦for angular displacement measurements. Likewise, an analysis was implemented both in the time and frequency domain for bipolar sEMG detection, to assess the energetic distribution of the TA and PL muscle contractions, showing that the spectral information in the 10–300 Hz range and PSD oscillates in the 0-7e-3 dB/Hz for a subject without FD pathology. The sensor network was implemented on the TA and PL in order to compare the transmitted and received information. The data collected and the experimental platform show the potential of the electronic prototype to measure physiological variables in real-time.eng
dc.format.mimetypeapplication/pdf
dc.identifier.doihttps://doi.org/10.1007/978-3-030-61834-6_27
dc.identifier.instnameinstname:Universidad El Bosquespa
dc.identifier.issn1865-0937
dc.identifier.reponamereponame:Repositorio Institucional Universidad El Bosquespa
dc.identifier.repourlrepourl:https://repositorio.unbosque.edu.co
dc.identifier.urihttps://hdl.handle.net/20.500.12495/5526
dc.language.isoeng
dc.publisherSpringer Nature Switzerland AG.spa
dc.publisher.journalCommunications in Computer and Information Sciencespa
dc.relation.ispartofseriesCommunications in Computer and Information Science, 1865-0937, p. 314-326spa
dc.relation.urihttps://link.springer.com/chapter/10.1007/978-3-030-61834-6_27
dc.rights.accessrightshttps://purl.org/coar/access_right/c_abf2
dc.rights.accessrightsinfo:eu-repo/semantics/openAccess
dc.rights.accessrightsAcceso abierto
dc.rights.creativecommons2020
dc.rights.localAcceso abiertospa
dc.subject.keywordsWearable sensorsspa
dc.subject.keywordsWireless transmissionspa
dc.subject.keywordssEMGspa
dc.subject.keywordsFoot dropspa
dc.subject.keywordsSensing systemspa
dc.titleSensor Network for Bipolar sEMG Detection and Angular Measurement for the Characterization of Foot Drop Pathologyspa
dc.title.translatedSensor Network for Bipolar sEMG Detection and Angular Measurement for the Characterization of Foot Drop Pathologyspa
dc.type.coarhttps://purl.org/coar/resource_type/c_6501
dc.type.driverinfo:eu-repo/semantics/article
dc.type.hasversioninfo:eu-repo/semantics/publishedVersion
dc.type.localArtículo de revista

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