Wearable Joint-Angle Measurement with Modulated Magnetic Field from L/C Oscilators

  • Michael Barry
  • Agnes Grünerbl
  • Paul Lukowicz
Part of the IFMBE Proceedings book series (IFMBE, volume 13)


We demonstrate how modulated magnetic field generated by an simple LC oscilator can be used to measure joint angles, which are a key element in posture recognition and many motion analysis applications. Our method uses the same physical principle as large stationary motion trackers, however it applies the principle in a way suitable for a small, low power wearable system. It has the potential to be more accurate while being smaller and cheaper then inertial tracking (MARG) approaches that today are state of the art in wearable motion tracking. The paper describes the principle behind our method, discusses the advantages and problems and presents our prototype implementation. On a large data set with an hour of recording, hundreds of motions and tens of thousands of measurement-points we demonstrate, that even with an initial crude system implementation reasonable accuracy (between 6 and 9 percent average error) can be achieved.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [1]
    Masayuki Kanbara Akihiro Hamaguchi and Naokazu Yokoya. User localization using wearable electromagnetic tracker and orientation sensor. Proc. Tenth Internartional Symposium on Wearable Computers ISWC 2006, Montreux, Switzerland, 00, 2006.Google Scholar
  2. [2]
    Eric R. Bachmann, Robert B. McGhee, Xiaoping Yun, and Michael J. Zyda. Inertial and magnetic posture tracking for inserting humans into networked virtual environments. In VRST’ 01: Proceedings of the ACM symposium on Virtual reality software and technology, pages 9–16, New York, NY, USA, 2001. ACM Press.Google Scholar
  3. [3]
    Jonny Farringdon, Andrew J. Moore, Nancy Tilbury, James Church, and Pieter D. Biemond. Wearable sensor badge and sensor jacket for context awareness. Proc. Internartional Symposium on Wearable Computers ISWC 99, 00:107, 1999.Google Scholar
  4. [4]
    Juha Kela, Panu Korpip, Jani Mantyjarvi, Sanna Kallio, Giuseppe Savino, Luca Jozzo, and Di Marca. Accelerometer-based gesture control for a design environment. Personal Ubiquitous Comput., 10(5):285–299, 2006.CrossRefGoogle Scholar
  5. [5]
    Paul Lukowicz, Jamie A. Ward, Holger Junker, Mathias Stäger, Gerhard Tröster, Amin Atrash, and Thad Starner. Recognizing workshop activity using body worn microphones and accelerometers. In Pervasive Computing: Proceedings of the 2nd International Conference, pages 18–22. Springer-Verlag Heidelberg: Lecture Notes in Computer Science, April 2004.Google Scholar
  6. [6]
    Corinne Mattmann, Tünde Kirstein, and Gerhard Tröster. A method to measure elongations of clothing. In Proc. 1st International Scientific Conference Ambience 05, September 2005.Google Scholar
  7. [7]
    Matja; Mihelj. Inverse kinematics of human arm based on multisensor data integration. J. Intell. Robotics Syst., 47(2):139–153, 2006.CrossRefGoogle Scholar
  8. [8]
    Greg Welch and Eric Foxlin. Motion tracking: No silver bullet, but a respectable arsenal. IEEE Comput. Graph. Appl., 22(6):24–38, 2002.CrossRefGoogle Scholar

Copyright information

© International Federation for Medical and Biological Engineering 2007

Authors and Affiliations

  • Michael Barry
    • 1
  • Agnes Grünerbl
    • 1
  • Paul Lukowicz
    • 1
    • 2
  1. 1.UMITHall in TirolAustria
  2. 2.University of PassauGermany

Personalised recommendations