Mostrar o rexistro simple do ítem

dc.contributor.authorMartínez-Martínez, Francisco José
dc.contributor.authorConcheiro-Moscoso, Patricia
dc.contributor.authorMiranda-Duro, María del Carmen
dc.contributor.authorDocampo Boedo, Francisco
dc.contributor.authorMejuto Muiño, Francisco Javier
dc.contributor.authorGroba, Betania
dc.date.accessioned2020-10-19T08:24:45Z
dc.date.available2020-10-19T08:24:45Z
dc.date.issued2020-08-21
dc.identifier.citationMartínez-Martínez FJ, Concheiro-Moscoso P, Miranda-Duro MC, Docampo Boedo F, Mejuto Muiño FJ, Groba B. Validation of Self-Quantification Xiaomi Band in a Clinical Sleep Unit. Proceedings. 2020; 54(1):29es_ES
dc.identifier.issn2504-3900
dc.identifier.urihttp://hdl.handle.net/2183/26457
dc.description.abstract[Abstract] Polysomnography (PSG) is currently the accepted gold standard for sleep studies, as it measures multiple variables that lead to a clear diagnosis of any sleep disorder. However, it has some clear drawbacks, since it can only be performed by qualified technicians, has a high cost and complexity and is very invasive. In the last years, actigraphy has been used along PSG for sleep studies. In this study, we intend to assess the capability of the new Xiaomi Mi Smart Band 5 to be used as an actigraphy tool. Sleep measures from PSG and Xiaomi Mi Smart Band 5 recorded in the same night will be obtained and further analysed to assess their concordance. For this analysis, we perform a paired sample t-test to compare the different measures, Bland–Altman plots to evaluate the level of agreement between the Mi Band and PSG and Epoch by Epoch analysis to study the ability of the Mi Band to correctly identify PSG-defined sleep stages. This study belongs to the research field known as participatory health, which aims to offer an innovative healthcare model driven by the patients themselves, leading to civic empowerment and self-management of health.es_ES
dc.language.isoenges_ES
dc.publisherMDPI AGes_ES
dc.relation.urihttps://doi.org/10.3390/proceedings2020054029es_ES
dc.rightsAtribución 4.0 Españaes_ES
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/es/*
dc.subjectSleepes_ES
dc.subjectPolysomnographyes_ES
dc.subjectParticipatory healthes_ES
dc.subjectXiaomi Mi Smart Band 5es_ES
dc.subjectInternet of Thingses_ES
dc.titleValidation of Self-Quantification Xiaomi Band in a Clinical Sleep Unites_ES
dc.typeinfo:eu-repo/semantics/conferenceObjectes_ES
dc.rights.accessinfo:eu-repo/semantics/openAccesses_ES
UDC.journalTitleProceedingses_ES
UDC.volume54es_ES
UDC.issue1es_ES
UDC.startPage29es_ES
UDC.conferenceTitle3rd XoveTIC Conference; A Coruña, Spain; 8–9 October 2020es_ES


Ficheiros no ítem

Thumbnail
Thumbnail

Este ítem aparece na(s) seguinte(s) colección(s)

Mostrar o rexistro simple do ítem