• DocumentCode
    3588070
  • Title

    Patient-centric on-body sensor localization in smart health systems

  • Author

    Saeedi, Ramyar ; Amini, Navid ; Ghasemzadeh, Hassan

  • Author_Institution
    Embedded & Pervasive Syst. Lab., Washington State Univ., Pullman, WA, USA
  • fYear
    2014
  • Firstpage
    2081
  • Lastpage
    2085
  • Abstract
    A major obstacle in widespread adoption of current wearable monitoring systems is that sensors must be worn on predefined locations on the body. In order to continuously detect sensor locations, we propose a localization algorithm that allows patients to wear the sensors on different body locations without having to adhere to a specific installation protocol. Our approach achieves localization accuracy of 90.8% even when the sensor nodes are mis-oriented. Integration of the resulting location information as a feature in an activity recognition classifier significantly increased the recognition accuracy from 23.5% to 99.5%.
  • Keywords
    biomechanics; body sensor networks; medical signal processing; patient monitoring; activity recognition classifier; localization algorithm; patient-centric on-body sensor localization; pedometer; recognition accuracy; smart health systems; wearable monitoring systems; Accelerometers; Accuracy; Biomedical monitoring; Feature extraction; Machine learning algorithms; Monitoring; Smart phones;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signals, Systems and Computers, 2014 48th Asilomar Conference on
  • Print_ISBN
    978-1-4799-8295-0
  • Type

    conf

  • DOI
    10.1109/ACSSC.2014.7094840
  • Filename
    7094840