Skip navigation
  •  Inicio
  • UDC 
    • Cómo depositar
    • Políticas del RUC
    • FAQ
    • Derechos de autor
    • Más información en INFOguías UDC
  • Listar 
    • Comunidades
    • Buscar por:
    • Fecha de publicación
    • Autor
    • Título
    • Materia
  • Ayuda
    • español
    • Gallegan
    • English
  • Acceder
  •  Español 
    • Español
    • Galego
    • English
  
Ver ítem 
  •   RUC
  • Facultade de Ciencias da Saúde
  • Investigación (FCS)
  • Ver ítem
  •   RUC
  • Facultade de Ciencias da Saúde
  • Investigación (FCS)
  • Ver ítem
JavaScript is disabled for your browser. Some features of this site may not work without it.

Validation of Self-Quantification Xiaomi Band in a Clinical Sleep Unit

Thumbnail
Ver/Abrir
MirandaDuro_2020_Validation_Self_Quantification_Xiaomi_Band.pdf (239.2Kb)
Use este enlace para citar
http://hdl.handle.net/2183/26457
Atribución 4.0 España
Excepto si se señala otra cosa, la licencia del ítem se describe como Atribución 4.0 España
Colecciones
  • Investigación (FCS) [1293]
Metadatos
Mostrar el registro completo del ítem
Título
Validation of Self-Quantification Xiaomi Band in a Clinical Sleep Unit
Autor(es)
Martínez-Martínez, Francisco José
Concheiro-Moscoso, Patricia
Miranda-Duro, María del Carmen
Docampo Boedo, Francisco
Mejuto Muiño, Francisco Javier
Groba, Betania
Fecha
2020-08-21
Cita bibliográfica
Martínez-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):29
Resumen
[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.
Palabras clave
Sleep
Polysomnography
Participatory health
Xiaomi Mi Smart Band 5
Internet of things
 
Versión del editor
https://doi.org/10.3390/proceedings2020054029
Derechos
Atribución 4.0 España
ISSN
2504-3900

Listar

Todo RUCComunidades & ColeccionesPor fecha de publicaciónAutoresTítulosMateriasGrupo de InvestigaciónTitulaciónEsta colecciónPor fecha de publicaciónAutoresTítulosMateriasGrupo de InvestigaciónTitulación

Mi cuenta

AccederRegistro

Estadísticas

Ver Estadísticas de uso
Sherpa
OpenArchives
OAIster
Scholar Google
UNIVERSIDADE DA CORUÑA. Servizo de Biblioteca.    DSpace Software Copyright © 2002-2013 Duraspace - Sugerencias