TCCDW WORKSHOP (PervasiveHealth) 2009

Research Article

Pervasive embedded real time monitoring of EEG & SpO2

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  • @INPROCEEDINGS{10.4108/ICST.PERVASIVEHEALTH2009.6044,
        author={Ajay M. Cheriyan and Zbigniew Kalbarczyk and Ravishankar K. Iyer and Albert O. Jarvi and Tanya M. Gallagher and Kenneth L. Watkin},
        title={Pervasive embedded real time monitoring of EEG \& SpO2},
        proceedings={TCCDW WORKSHOP (PervasiveHealth) 2009},
        proceedings_a={TCCDW},
        year={2009},
        month={8},
        keywords={cognitive decline, embedded monitoring, EEG and Sp02},
        doi={10.4108/ICST.PERVASIVEHEALTH2009.6044}
    }
    
  • Ajay M. Cheriyan
    Zbigniew Kalbarczyk
    Ravishankar K. Iyer
    Albert O. Jarvi
    Tanya M. Gallagher
    Kenneth L. Watkin
    Year: 2009
    Pervasive embedded real time monitoring of EEG & SpO2
    TCCDW
    IEEE
    DOI: 10.4108/ICST.PERVASIVEHEALTH2009.6044
Ajay M. Cheriyan1,*, Zbigniew Kalbarczyk1,*, Ravishankar K. Iyer1,*, Albert O. Jarvi2,*, Tanya M. Gallagher2,*, Kenneth L. Watkin2,*
  • 1: Center for Reliable and High Performance Computing, University of Illinois, Urbana-Champaign, Urbana, IL - 61801
  • 2: Center for Health, Aging and Disability, University of Illinois, Urbana-Champaign, Urbana, IL - 61801
*Contact email: cheriyal@illinois.edu, kalbarcz@illinois.edu, rkiyer@illinois.edu, ajarvi2@illinois.edu, tmgallag@illinois.edu, watkin@illinois.edu

Abstract

Recent research has underscored the potential role of analysis of EEG signals as indicators of cognitive decline. In addition, we have also seen the emergence of embedded systems that are capable of analyzing biological signals in real time to track a number of physiological variables and make accurate conclusions about the individual's physiological status and health. This paper presents the design of an embedded system which is capable of tracking relevant bio-signals from the person in real time and facilitating a dependable decision making process that provides alerts for potential brain activity changes. The design focuses around the use of sensors and a processing element. It incorporates the use of electroencephalography (EEG) and oxygen saturation (SpO2) signals. As an early proof-of-concept, our system collects data from the sensors, performs initial processing and provides the framework to compute significant physiological variables.