Matrix Pad Transducer

Conference paper
Part of the Mechanisms and Machine Science book series (Mechan. Machine Science, volume 2)

Abstract

Human trait detection could be a useful job for an automat system. Animal abilities of space detection are strictly oriented to help them to survive. Dog use, first, the smell receptivity, but snake uses the infrared sensors. The matrix pressure sensor for human gait detection needs such a structure in order to be able to acquire a set of data to describe the human footprint as a spatial-temporal function p(x,y,t). Any element of the transducer takes a position that is defined by the matrix coordinate. All the elements are pressure sensors. A difficulty of this transducer design is the achievement of the signal. A simple grid connection is not adequate to obtain p(x,y,t) versus s(t) signal. The analogical signal has to be converted to digital one. Finally the matrix must be analyzed with an image strategy: segmentation, ROI establishing, Fast Fourier Analyze etc.

Keywords

Matrix Transducer Pressure sensor Pad Recognition 

References

  1. 1.
    Abdelkader, C. B., Cutler, R., Nanda, H., Davis, L.: Eigen-Gait: Motion-Based Recognition Using Image Self-Similarity. In: Third Proceedings of the Audio- and Video-Based Biometric Person Authentication, Halmstaadt, Sweden, 2001.Google Scholar
  2. 2.
    Chew Yean Yam, Nixon, M. S., Carter, J. D.: Automated Person Recognition by Walking and Running Via Model-Based Approaches. In: The Journal of the Pattern Recognition Society, 2003.Google Scholar
  3. 3.
    Daehee, K., Seungwon, L., Jooki, P.: Active Shape Model-Based Gait Recognition Using Infrared Images. In: International Journal of Signal Processing, Image Processing and Pattern Recognition, Vol.2, No.4, 2009.Google Scholar
  4. 4.
    Dehelean, L. M., Dehelean, N. M.: On Matrix Sensor Category Dedicated to a Gait Detection System. In: Scientific Journal of Polytechnic Institute from Iaşi, Vol. LII(LVI), Issue 7A, 2006, p. 101-106.Google Scholar
  5. 5.
    Dehelean, L. M., Dehelean, N. M., Stănescu, D.: A Minimal System Structure for Human Trait-Detection, In: Proceedings of the 7th Conference on Technical Informatics CONTI’2006, Timişoara, 2006, p. 189-194.Google Scholar
  6. 6.
    Descatoire, A., Thevenont, A., Moretto, A.: Baropodometric Information Return Device for Foot Unloading. In: Medical Engineering and Physics 31(2009), p. 607-613, http://www.elsevier.com/locate/medengphy.CrossRefGoogle Scholar
  7. 7.
    Foster, J., Nixon, M., Prugel-Bennett, A.: New Area Based Matrices for Automatic Gait Recognition. In: Proceedings of the British Machine Vision Conference, Manchester, UK, 2001.Google Scholar
  8. 8.
    Hohm, K., Weigl, A., Krüger B., Schwartz, M., Tolle, H.: Using a Multisensory Gripper System for Robot Assisted Disassembly of Electronic Devices. Darmstadt University of Technology, Control System Theory and Robotics Dept, Darmstadt, Germany.Google Scholar
  9. 9.
    Holweg, E. G. M., Hoeve, H., Jongkind, W., Marconi, L., Melchiorri, C., Bonivento, C.: Slip Detection by Tactile Sensors: Algorithms and Experimental Results. In: ICRA’96, IEEE International Conference on Robotics and Automation, Minneapolis, MN, 1996.Google Scholar
  10. 10.
    Holweg, E. G. M., Eusebi, A., Marconi, L.: Reflex Control by a Rubber-Based Tactile Sensor. In: “Advances in Robotics. The ERNET Perspective”, Proceedings of the Research Workshop of ERNET, C. Bonivento, C. Melchiorri and H. Tolle Eds., p.117-126, 1996.Google Scholar
  11. 11.
    Johnson, A. Y., Bobick, A. F.: A Multi-View Method for Gait Recognition Using Static Body Parameters. In: Third Proceedings of the Audio- and Video-Based Biometric Person Authentication, Halmstaadt, Sweden, 2001.Google Scholar
  12. 12.
    Marconi, L.: Tactile Sensor Data Elaboration for Object Recognition and Interpretation. In: Second TELEMAN Students Congress, Leeuwenhorst Congress Centrum, Noordwijkerhout, the Netherland, 1995.Google Scholar
  13. 13.
    Nguyen, N. T., Venkatesh, S., West, G., Bui, H.: Learning People Movement from Multiple Cameras for Behaviour Recognition. BMVC99, 1999.Google Scholar
  14. 14.
    Niyogi, S. A., Adelson, E. A.: Analyzing and Recognizing Walking Figures in XYT. In: Proceedings of the Conference of Computer Vision and Pattern Recognition, Seattle, WA, 1994.Google Scholar
  15. 15.
    Shutler, J. D., Nixon, M. S., Harris, C. J.: Statistical Gait Recognition via Temporal Moments. In: Fourth IEEE Southwest Symposium on Image Analysis and Interpretation, Austin, Texas, 2000.Google Scholar
  16. 16.
    Thordarson, D. B.: Running Biomechanics. Clin. Sports Med. 16(2), 1997.Google Scholar

Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  1. 1.Department of Mechatronics“POLITEHNICA” University of TimisoaraTimisoaraRomania

Personalised recommendations