• DocumentCode
    643508
  • Title

    Wireless network acquisition of joint EEG-ECG-ergospirometric signals for epilepsy detection

  • Author

    Lay-Ekuakille, Aime ; Vergallo, P. ; Griffo, G. ; Kanoun, Olfa ; Angelillo, F. ; Trabacca, A.

  • Author_Institution
    Dept. of Innovation Eng., Univ. of Salento, Lecce, Italy
  • fYear
    2013
  • fDate
    7-8 Oct. 2013
  • Firstpage
    41
  • Lastpage
    45
  • Abstract
    Wireless network architecture allows the implementation of fatigue measurement that was once performed in a limited and constrained way due to the use of wired connections. This paper presents measurement acquisitions by means of wireless network that allows joint acquisition of electroencephalograms, electrocardiograms and ergospirometry signals. This opportunity permits to a person walking to a dedicated path (about 30 meters) to develop fatigue that is recorded in function of EEG and ECG. Only wireless configuration allows the patient under test to walk. Some issues have been developed to detect interesting features on transmitted signals for epilepsy detection.
  • Keywords
    biomedical equipment; bone; electrocardiography; electroencephalography; gait analysis; medical signal detection; medical signal processing; wireless sensor networks; electrocardiograms; electroencephalograms; epilepsy detection; fatigue measurement; joint EEG-ECG-ergospirometric signals; joint acquisition; person walking; transmitted signals; wireless configuration; wireless network acquisition; wireless network architecture; Electrocardiography; Electroencephalography; Monitoring; Robot sensing systems; Wireless communication; Wireless sensor networks; Biomedical networking and communication; ECG; EEG; Epilepsy; Ergospirometry; Telemetry; WSN; throughput;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Measurements and Networking Proceedings (M&N), 2013 IEEE International Workshop on
  • Conference_Location
    Naples
  • Print_ISBN
    978-1-4673-2873-9
  • Type

    conf

  • DOI
    10.1109/IWMN.2013.6663774
  • Filename
    6663774