• DocumentCode
    728598
  • Title

    Unscented Kalman Filter based finger tracking utilising magnetoresistive sensors

  • Author

    Simmons, Luke P. ; Welsh, James S.

  • Author_Institution
    Sch. of Electr. Eng. & Comput. Sci., Univ. of Newcastle, Callaghan, NSW, Australia
  • fYear
    2015
  • fDate
    1-3 July 2015
  • Firstpage
    5128
  • Lastpage
    5133
  • Abstract
    In this paper we utilise magnetoresistive sensors and an Unscented Kalman Filter to develop a finger tracking system for physical therapy and human-machine interaction. The aim of this finger tracking system is to provide a light weight apparatus with a prolonged operational period. The finger tracking algorithm utilises two-dimensional measurements of each joint relative to a magnetic field reference point to obtain an accurate model of the finger position as opposed to other light weight systems that provide information in only one dimension. The nonlinear interaction between joint movements and sensor measurement requires a nonlinear filtering technique, as such, a Kalman filter that utilises an unscented transformation was utilised.
  • Keywords
    Kalman filters; biomagnetism; human computer interaction; magnetic sensors; magnetoresistive devices; medical signal processing; nonlinear filters; object tracking; patient rehabilitation; 2D joint measurements; human-machine interaction; magnetic field reference point; magnetoresistive sensors; nonlinear filtering technique; physical therapy; unscented Kalman filter based finger tracking; Joints; Kalman filters; Kinematics; Magnetic recording; Magnetic sensors; Sensor systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference (ACC), 2015
  • Conference_Location
    Chicago, IL
  • Print_ISBN
    978-1-4799-8685-9
  • Type

    conf

  • DOI
    10.1109/ACC.2015.7172139
  • Filename
    7172139