Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/71872
Registo completo
Campo DC | Valor | Idioma |
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dc.contributor.author | Pinho, Francisco | por |
dc.contributor.author | Cerqueira, João José | por |
dc.contributor.author | Correia, J. H. | por |
dc.contributor.author | Sousa, Nuno | por |
dc.contributor.author | Dias, Nuno | por |
dc.date.accessioned | 2021-04-15T15:37:29Z | - |
dc.date.issued | 2017 | - |
dc.identifier.issn | 0309-1902 | - |
dc.identifier.uri | https://hdl.handle.net/1822/71872 | - |
dc.description.abstract | The World Health Organisation has pointed that a successful health care delivery, requires effective medical devices as tools for prevention, diagnosis, treatment and rehabilitation. Several studies have concluded that longer monitoring periods and outpatient settings might increase diagnosis accuracy and success rate of treatment selection. The long-term monitoring of epileptic patients through electroencephalography (EEG) has been considered a powerful tool to improve the diagnosis, disease classification, and treatment of patients with such condition. This work presents the development of a wireless and wearable EEG acquisition platform suitable for both long-term and short-term monitoring in inpatient and outpatient settings. The developed platform features 32 passive dry electrodes, analogue-to-digital signal conversion with 24-bit resolution and a variable sampling frequency from 250 Hz to 1000 Hz per channel, embedded in a stand-alone module. A computer-on-module embedded system runs a Linux® operating system that rules the interface between two software frameworks, which interact to satisfy the real-time constraints of signal acquisition as well as parallel recording, processing and wireless data transmission. A textile structure was developed to accommodate all components. Platform performance was evaluated in terms of hardware, software and signal quality. The electrodes were characterised through electrochemical impedance spectroscopy and the operating system performance running an epileptic discrimination algorithm was evaluated. Signal quality was thoroughly assessed in two different approaches: playback of EEG reference signals and benchmarking with a clinical-grade EEG system in alpha-wave replacement and steady-state visual evoked potential paradigms. The proposed platform seems to efficiently monitor epileptic patients in both inpatient and outpatient settings and paves the way to new ambulatory clinical regimens as well as non-clini | por |
dc.description.sponsorship | POFC - Programa Operacional Temático Factores de Competitividade(FCOMP-01-0124-FEDER-022674)This work is supported by Fundac¸~ao para a Ci^ encia e Tecnologia with the reference project FCOMP 01 0124- FEDER-010909 [FCT/PTDC/SAU-BEB/100392/2008], FCOMP 01 0124 FEDER 021145 [FCT/PTDC/SAU-ENB/118383/2010] and by FEDER funds through the Programa Operacional Fatores de Competitividade – COMPETE and National Funds through Fundac¸~ao para a Ciencia e Tecnologia with the reference ^ Project: FCOMP-01-0124-FEDER-022674. This work is also sup ported by ADI Project “DoIT – Desenvolvimento e Operacionalizac¸~ao da Investigac¸~ao de Translac¸~ao” (project no. 13853, PPS4-MyHealth), funded by Fundo Europeu de Desenvolvimento Regional (FEDER) through the Programa Operacional Factores de Competitividade (POFC). | por |
dc.language.iso | eng | por |
dc.publisher | Taylor and Francis | por |
dc.rights | restrictedAccess | por |
dc.subject | EEG | por |
dc.subject | Epilepsy | por |
dc.subject | Dry-electrodes Embedded systems | por |
dc.subject | Embedded systems | por |
dc.subject | dry-electrodes | por |
dc.subject | wireless | por |
dc.title | myBrain: a novel EEG embedded system for epilepsy monitoring | por |
dc.type | letterToEditor | por |
dc.peerreviewed | yes | por |
dc.relation.publisherversion | https://www.tandfonline.com/doi/full/10.1080/03091902.2017.1382585 | por |
oaire.citationStartPage | 564 | por |
oaire.citationEndPage | 585 | por |
oaire.citationIssue | 7 | por |
oaire.citationVolume | 41 | por |
dc.date.updated | 2021-04-15T13:52:43Z | - |
dc.identifier.eissn | 1464-522X | - |
dc.identifier.doi | 10.1080/03091902.2017.1382585 | por |
dc.date.embargo | 10000-01-01 | - |
dc.identifier.pmid | 28994627 | por |
sdum.export.identifier | 10630 | - |
sdum.journal | Journal of Medical Engineering and Technology | por |
dc.identifier.pmc | 28994627 | - |
Aparece nas coleções: | CMEMS - Artigos em revistas internacionais/Papers in international journals |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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myBrain_2017_journal.pdf Acesso restrito! | 1,45 MB | Adobe PDF | Ver/Abrir |