• DocumentCode
    3064753
  • Title

    Frequency domain approach for activity classification using accelerometer

  • Author

    Chung, Wan-Young ; Purwar, Amit ; Sharma, Annapurna

  • Author_Institution
    Division of Computer & Information Engineering, Dongseo University, Busan 617-716, Korea
  • fYear
    2008
  • fDate
    20-25 Aug. 2008
  • Firstpage
    1120
  • Lastpage
    1123
  • Abstract
    Activity classification was performed using MEMS accelerometer and wireless sensor node for wireless sensor network environment. Three axes MEMS accelerometer measures body´s acceleration and transmits measured data with the help of sensor node to base station attached to PC. On the PC, real time accelerometer data is processed for movement classifications. In this paper, Rest, walking and running are the classified activities of the person. Both time and frequency analysis was performed to classify running and walking. The classification of rest and movement is done using Signal magnitude area (SMA). The classification accuracy for rest and movement is 100%. For the classification of walk and Run two parameters i.e. SMA and Median frequency were used. The classification accuracy for walk and running was detected as 81.25% in the experiments performed by the test persons.
  • Keywords
    Acceleration; Accelerometers; Base stations; Frequency domain analysis; Legged locomotion; Micromechanical devices; Performance analysis; Performance evaluation; Testing; Wireless sensor networks; Acceleration; Algorithms; Humans; Monitoring, Physiologic; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; Telemetry; Transducers;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2008. EMBS 2008. 30th Annual International Conference of the IEEE
  • Conference_Location
    Vancouver, BC
  • ISSN
    1557-170X
  • Print_ISBN
    978-1-4244-1814-5
  • Electronic_ISBN
    1557-170X
  • Type

    conf

  • DOI
    10.1109/IEMBS.2008.4649357
  • Filename
    4649357