• DocumentCode
    180875
  • Title

    Real-Time ECG and EMG Analysis for Biking Using Android-Based Mobile Devices

  • Author

    Richer, Robert ; Blank, Peter ; Schuldhaus, Dominik ; Eskofier, Bjorn M.

  • Author_Institution
    Dept. of Comput. Sci., Friedrich-Alexander-Univ. Erlangen-Nuremberg, Erlangen, Germany
  • fYear
    2014
  • fDate
    16-19 June 2014
  • Firstpage
    104
  • Lastpage
    108
  • Abstract
    We developed an application for Android-based mobile devices that enables a real-time calculation of heart rate and cadence for biking. Therefore, both ECG and EMG data are acquired in real time by Shimmer sensors and transmitted via Bluetooth, as well as processed and evaluated on the mobile device. The ECG algorithm is based on the Pan-Tompkins algorithm for QRS-Detection and offers a heart beat detection rate of more than 94%. The EMG algorithm offers a treadle detection rate of more than 91%. The application´s range of features is complemented by GPS data for the calculation of speed and location information. It is available for download and can for example be used for controlling the user´s training status, for live training supervision and for the subsequent analysis of the various training runs.
  • Keywords
    Bluetooth; body sensor networks; data acquisition; electrocardiography; electromyography; medical signal detection; medical signal processing; smart phones; telemedicine; Android-based mobile devices; Bluetooth; ECG data acquisition; EMG data acquisition; Pan-Tompkins algorithm; QRS-detection; Shimmer sensors; biking; electrocardiography; electromyography; heart beat detection rate; real-time ECG analysis; real-time EMG analysis; Electrocardiography; Electromyography; Heart beat; Mobile handsets; Real-time systems; Signal processing algorithms; Training; android application; biomedical signal analysis; electrocardiography; electromyography; training support; wearable body sensor networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Wearable and Implantable Body Sensor Networks (BSN), 2014 11th International Conference on
  • Conference_Location
    Zurich
  • Print_ISBN
    978-1-4799-4932-8
  • Type

    conf

  • DOI
    10.1109/BSN.2014.20
  • Filename
    6855625