Real-Time Management of Multimodal Streaming Data for Monitoring of Epileptic Patients.

New generation of healthcare is represented by wearable health monitoring systems, which provide real-time monitoring of patient's physiological parameters. It is expected that continuous ambulatory monitoring of vital signals will improve treatment of patients and enable proactive personal health m...

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Publicado en:Journal of Medical Systems Vol. 40; no. 3; pp. 1 - 12
Autores principales: Triantafyllopoulos, Dimitrios, Korvesis, Panagiotis, Mporas, Iosif, Megalooikonomou, Vasileios
Formato: pictorial research tables/charts Journal Article
Publicado: Springer Nature Mar2016
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Mar2016
      vid: 40
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      pub: Springer Nature
      place: New York, New York
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        atl: Real-Time Management of Multimodal Streaming Data for Monitoring of Epileptic Patients.
      aug:
        au:
          Triantafyllopoulos, Dimitrios
          Korvesis, Panagiotis
          Mporas, Iosif
          Megalooikonomou, Vasileios
        affil: Multidimensional Data Analysis and Knowledge Management Laboratory, Department of Computer Engineering and Informatics, University of Patras, 26500 Rion-Patras Greece
      sug:
        subj:
          Epilepsy
          Monitoring, Physiologic Methods
          Wearable Sensors Evaluation
          Wireless Communications
          Seizures Diagnosis
          Human
          Data Analysis, Computer Assisted Methods
          Algorithms
          Funding Source
      ab: New generation of healthcare is represented by wearable health monitoring systems, which provide real-time monitoring of patient's physiological parameters. It is expected that continuous ambulatory monitoring of vital signals will improve treatment of patients and enable proactive personal health management. In this paper, we present the implementation of a multimodal real-time system for epilepsy management. The proposed methodology is based on a data streaming architecture and efficient management of a big flow of physiological parameters. The performance of this architecture is examined for varying spatial resolution of the recorded data.
      pubtype: Academic Journal
      doctype:
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        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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