• DocumentCode
    261300
  • Title

    A functional ARM movement tracking and monitoring system using electogoniometer

  • Author

    Zimoga, M. Asley ; Padmanaban, L.

  • Author_Institution
    Dept. of ECE, Prathyusha Inst. of Technol. & Manage., Thiruvallur, India
  • fYear
    2014
  • fDate
    27-28 Feb. 2014
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    This paper presents a new sensing system on magnetic linear encoder (MLE), in which the motion of an magnetic encoder on a code strip is converted into the limb joints goniometric data. This project evaluated a non invasive technique for estimating the carrying angle in full extension using a 3-dimensional digitizer. The angle data is essential data for identifying abnormal patterns and characterizing impairments, disabilities and handicaps. The knee angle is measured with an electrogoniometer; angle of knee is controlled by PIC16F877A microcontroller. Capsense technique is used to giving input to the microcontroller PIC16F877A, information are displayed using 16*2 LCD display.
  • Keywords
    analogue-digital conversion; angular measurement; bioelectric phenomena; biomechanics; biomedical equipment; biomedical measurement; capacitive sensors; goniometers; medical disorders; medical signal processing; microcontrollers; patient monitoring; 16*2 LCD display; 3-dimensional digitizer; PIC16F877A microcontroller; abnormal patterns; capsense technique; carrying angle estimation; code strip; disabilities; electogoniometer; functional ARM movement monitoring system; functional ARM movement tracking system; handicaps; impairments; knee angle; limb joints goniometric data; magnetic encoder motion; magnetic linear encoder; Capacitance; Goniometers; Joints; Optical sensors; Semiconductor device measurement; Solids; Capsense technique; Magnetic Linear Encoder;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Communication and Embedded Systems (ICICES), 2014 International Conference on
  • Conference_Location
    Chennai
  • Print_ISBN
    978-1-4799-3835-3
  • Type

    conf

  • DOI
    10.1109/ICICES.2014.7034185
  • Filename
    7034185