Publication
Integrated electromyography visualization with multi temporal resolution
| dc.contributor.author | Cardoso, Pedro | |
| dc.contributor.author | Datia, Nuno | |
| dc.contributor.author | Pós-de-Mina Pato, Matilde | |
| dc.date.accessioned | 2017-05-24T08:42:01Z | |
| dc.date.available | 2017-05-24T08:42:01Z | |
| dc.date.issued | 2017-04 | |
| dc.description.abstract | For the analysis and comparison of electromyography (EMG) signals from different patients, standardization techniques are used to calculate the integrated EMG signal (iEMG), useful to evaluate the level of activity of different muscles. The iEMG corresponds to the area under the rectified curve (AUC). Currently, monitoring and follow-up of these patients is done in regular health exams where the evolution of patients is assessed. The monitoring includes performing multiple clinical trials. The goal of this paper is to help medical staff assessing the evolution of amyotrophic lateral sclerosis (ALS) disease by analyzing the collected data. The signal, described by the electromyogram, can be measured applying conductive elements or electrodes to the skin surface. The electrical activity of skeletal muscles is continuously measured for at least 24 hours. In this work we used an appropriate data model to store data generated by EMGs, optimized for analytical processing. We implemented aWeb API in order to provide access to the model data in an agnostic way, both to database management systems and data consumers. We implemented a web application to visualize data through the use of several interactive charts. Usability testing helped to validate the solution, confirming the ease of use of the web application and the fulfillment of all the proposed goals. The telemonitoring ALS patients doesn't change mortality but reduces the need for hospitalization and costs for patient. | pt_PT |
| dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
| dc.identifier.citation | CARDOSO, Pedro; DATIA, Nuno; PATO, M. P. M – Integrated electromyography visualization with multi temporal resolution. In 2017 11th International Symposium on Medical Information and Communication Technology (ISMICT). Lisbon, Portugal. IEEE, 2017. ISBN: 978-1-5090-5464-0. Pp. 91-95 | pt_PT |
| dc.identifier.doi | 10.1109/ISMICT.2017.7891775 | pt_PT |
| dc.identifier.isbn | 978-1-5090-5464-0 | |
| dc.identifier.isbn | 978-1-5090-5465-7 | |
| dc.identifier.issn | 2326-8301 | |
| dc.identifier.uri | http://hdl.handle.net/10400.21/7053 | |
| dc.language.iso | eng | pt_PT |
| dc.peerreviewed | yes | pt_PT |
| dc.publisher | Institute of Electrical and Electronics Engineers | pt_PT |
| dc.relation.publisherversion | http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7891775 | pt_PT |
| dc.subject | Dimensional Modeling | pt_PT |
| dc.subject | Usability | pt_PT |
| dc.subject | OData | pt_PT |
| dc.subject | Data visualization | pt_PT |
| dc.title | Integrated electromyography visualization with multi temporal resolution | pt_PT |
| dc.type | conference object | |
| dspace.entity.type | Publication | |
| oaire.citation.endPage | 95 | pt_PT |
| oaire.citation.startPage | 91 | pt_PT |
| oaire.citation.title | IEEE International Symposium on Medical Information and Communication Technology | pt_PT |
| person.familyName | Datia | |
| person.familyName | Pós-de-Mina Pato | |
| person.givenName | Nuno | |
| person.givenName | Matilde | |
| person.identifier | 2587159 | |
| person.identifier | 2482285 | |
| person.identifier.ciencia-id | 071F-5CBD-5D83 | |
| person.identifier.ciencia-id | FA11-8E2D-DC05 | |
| person.identifier.orcid | 0000-0003-1600-0227 | |
| person.identifier.orcid | 0000-0001-8976-7651 | |
| person.identifier.rid | R-7957-2016 | |
| person.identifier.rid | AAM-8381-2020 | |
| person.identifier.scopus-author-id | 56026178000 | |
| person.identifier.scopus-author-id | 16550896700 | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | conferenceObject | pt_PT |
| relation.isAuthorOfPublication | 368f1534-fbb8-4e99-994c-1c7104a42bc6 | |
| relation.isAuthorOfPublication | a357377e-e428-4f62-a47a-f2a20e4cbdd5 | |
| relation.isAuthorOfPublication.latestForDiscovery | 368f1534-fbb8-4e99-994c-1c7104a42bc6 |