• DocumentCode
    723326
  • Title

    Multi-parameter health state assessment

  • Author

    Kozlovszky, Miklos

  • Author_Institution
    Biotech Knowledge Center, Obuda Univ., Budapest, Hungary
  • fYear
    2015
  • fDate
    10-12 June 2015
  • Firstpage
    145
  • Lastpage
    150
  • Abstract
    Recent small, ubiquitous and mobile sensor devices are capable to measure a large set of vital parameters. Organism´s health status is correlated with the acquired information. We have established a dynamic health status model, which builds from the collected organism´s data. The data collection is realized with a multiplatform data acquisition framework (DAQit), which collects multimodal sensor information remotely, provides visualization/alarming services for experts and forwards information towards to the data archive and dispatcher centers for further processing. The dynamic health status model and a mobile DAQ (mDAQ) system enable experts to provide better and more effective remote health status monitoring, large scale population screening, more effective prevention, and support services.
  • Keywords
    biological techniques; biomedical telemetry; data acquisition; intelligent sensors; patient monitoring; remote sensing; DAQit; alarming services; collected organism data; data archive; data collection; dispatcher centers; dynamic health status model; large scale population screening; mDAQ; mobile DAQ system; mobile sensor devices; multimodal sensor information; multiparameter health state assessment; multiplatform data acquisition framework; organism health status; remote health status monitoring; small sensor devices; ubiquitous sensor devices; visualization services; vital parameters; Biomedical monitoring; Data acquisition; Data visualization; Diseases; Monitoring; Sociology; Statistics; dynamic health status model; remote monitoring;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinspired Intelligence (IWOBI), 2015 4th International Work Conference on
  • Conference_Location
    San Sebastian
  • Print_ISBN
    978-1-4673-7845-1
  • Type

    conf

  • DOI
    10.1109/IWOBI.2015.7160158
  • Filename
    7160158