A wireless, modular and wearable system for the recognition and assessment of foot drop pathology

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dc.contributor.authorNoriega Alvarez, Santiago
dc.contributor.authorRojas, Maria C.
dc.contributor.authorMurrugarra Quiroz, Cecilia
dc.contributor.orcidMurrugarra Quiroz, Cecilia [0000-0001-9439-5418]
dc.date.accessioned2020-11-11T18:57:30Z
dc.date.available2020-11-11T18:57:30Z
dc.date.issued2020
dc.description.abstractenglishIn this paper, a portable, low cost and non-invasive real-time signals processing prototype was designed and developed for the diagnosis and continuous monitoring of the physiopathological condition of foot drop. The behavior of the electrical activity of the Tibialis Anterior (TA) and Peroneus Longus (PL) muscles through bipolar surface electromyography (sEMG), together with the angular measurement of the joint complex of the ankle-foot in the sagittal and frontal planes using an Inertial Measurement Unit (IMU) sensor system, are monitored from a mobile interface. This prototype consists of five modules capable of performing functions of sensing, signal processing, data storage, and transmission. The Central Processing Unit (CPU) process the sEMG signals from the two-channel amplifier with 10 bits of resolution at a sampling frequency of 1ksps; the IMU Sensor System operates at a sample rate of 1ksps with 16 bits of resolution. Both sEMG and angular displacement data registers are transmitted wirelessly via Bluetooth communication protocol to a mobile interface designed for smartphones/tablets and PC. Data verification was made using a commercial electromyograph and a goniometer. The observations regarding the health status of the patient on a statistical, mathematical analysis of the collected data, exhibiting a mean-square-error of 5,27% for the sEMG as well as an average error of ≤±2∘ in the angular displacement measurements. The prototype designed and developed establishes a new perspective in the recognition and elaboration of profiles of physiopathological disabilities in humans, development of clinical applications, and databases for future studies of the disease.eng
dc.format.mimetypeapplication/pdf
dc.identifier.doihttps://doi.org/10.1007/978-3-030-31019-6_33
dc.identifier.instnameinstname:Universidad El Bosquespa
dc.identifier.reponamereponame:Repositorio Institucional Universidad El Bosquespa
dc.identifier.repourlrepourl:https://repositorio.unbosque.edu.co
dc.identifier.urihttps://hdl.handle.net/20.500.12495/4673
dc.language.isoeng
dc.publisherSpringer Linkspa
dc.publisher.journalCommunications in Computer and Information Sciencespa
dc.relation.ispartofseriesCommunications in Computer and Information Science, Vol. 1052, 2019, p. 379-393spa
dc.relation.urihttps://link.springer.com/chapter/10.1007/978-3-030-31019-6_33
dc.rights.accessrightshttps://purl.org/coar/access_right/c_abf2
dc.rights.accessrightsinfo:eu-repo/semantics/openAccess
dc.rights.accessrightsAcceso abierto
dc.rights.creativecommons2019-10-09
dc.rights.localAcceso abiertospa
dc.subject.keywordsFoot dropspa
dc.subject.keywordsRehabilitationspa
dc.subject.keywordsEMGspa
dc.subject.keywordsSensorsspa
dc.subject.keywordsReal time, signal acquisitionspa
dc.titleA wireless, modular and wearable system for the recognition and assessment of foot drop pathologyspa
dc.title.translatedA wireless, modular and wearable system for the recognition and assessment 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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