Journal of Biomedical Engineering Research (대한의용생체공학회:의공학회지)

The Korean Society of Medical and Biological Engineering (대한의용생체공학회)
권호 표지

Development of a Portable Gait Phase Detection System for Patients with Gait Disorders

  • Ahn Seung Chan (Department of Biomedical Engineering and Institute of Medical Engineering, Yonsei University) ;
  • Hwang Sung Jae (Department of Biomedical Engineering and Institute of Medical Engineering, Yonsei University) ;
  • Kang Sung Jae (Department of Biomedical Engineering and Institute of Medical Engineering, Yonsei University) ;
  • Kim Young Ho (Department of Biomedical Engineering and Institute of Medical Engineering, Yonsei University)
  • Published : 2005.06.01
Download PDF
⟨ Previous Next ⟩

Abstract

A new gait detection system using both FSR (force sensing resistor) sensors and a gyrosensor was developed to detect various gait patterns. FSR sensors were put in self-designed shoe insoles and a gyrosensor was attached to the heel of a shoe. An algorithm was also developed to determine eight different gait transitions during four gait phases: heel-strike, foot-flat, heel-off and swing. The developed system was evaluated from nine heathy mans and twelve hemiplegic patients. Healthy volunteers were asked to walk in various gait patterns: level walking, fore-foot walking and stair walking. Only the level walking was performed in hemiplegic patients. The gait detection system was compared with a optical motion analysis system and the outputs of the FSR sensors. In healthy subjects, the developed system detected successfully more than $99\%$ for both level walking and fore-foot walking. For stair walking, the successful detection rate of the system was above$97\%$. In hemiplegic patients, the developed system detected approximately 98% of gait transitions. The developed gait phase detection system will be helpful not only to determine pathological gait phases but also to apply prosthetics, orthotics and functional electrical stimulation for patients with various gait disorders.

Keywords

References

  1. Vodovik, L., Kralj, A., Stanic, U., Acimovic, R. and Gros, N., 'Recent application of functional electrical stimulation to stroke patients in Ljubljana' , Clin, Orthop., Vol. 131, pp.64-70, 1978
  2. Ott, E., Munih, M., Benko, H. 'Comparison of foot-switch and hand FES correction of foot drop', in Proc. Workshop FES, pp.22-24, 1998
  3. Ng, S. K. and Chizeck, H. J., 'Fuzzy model identification or classification of gait events in paraplegics', IEEE Trans. Fuzzy Syst., Vol. 5, pp.536-544, 1977 https://doi.org/10.1109/91.649904
  4. Kostov, A., Andrews, B. J., Popovic, D. B., Stein, R. B. and Armstrong, W., 'Machine learning in control of functional electrical stimulation systems for locomotion', IEEE Trans. Biomed. Eng., Vol. 42, pp.541-551, 1995 https://doi.org/10.1109/10.387193
  5. Dai, R., Stein, R. B., Andrews, B. J., James, K. B. and Wieler, M., 'Application of tilt sensors in functional electrical stimulation', IEEE Trans. Rehab. Eng, Vol. 4, pp.63-72, 1999 https://doi.org/10.1109/86.506403
  6. Tong, K. and Grant, H. M., 'A practical gait analysis system using gyroscope', Med, Eng. Phys., Vol. 21, pp.87-94, 1999 https://doi.org/10.1016/S1350-4533(99)00030-2
  7. Willemsen, A., Bloemhof, F. and Boom, H., 'Automatic stance-swing phase detection from accelerometer data for peroneal nerve stimulation', IEEE Trans. Biomed. Eng., Vol. 37, pp.1201-1208, 1990 https://doi.org/10.1109/10.64463
  8. Williamson, R. and Andrews, B. J., 'Gait event detection for FES using accelerometers and supervised machine learning', IEEE Trans. Rehab. Eng. Vol. 8, pp.312-319, 2000 https://doi.org/10.1109/86.867873
  9. Kang, S. J. and Kim, Y. H., 'Gait improvement of polio patients using an electromechanical KAFO' , Journal of the Korean Society of Precision Engineering, Vol. 20, No.1, pp.39-46, 2003
  10. Lee, K. W., Kang, S. J., Kim, Y. H. and Cho, K. H., 'Development of the automatic knee joint control system for a knee-ankle-foot orthosis using an electromechanical clutch:', J. Biomed. Eng. Res., Vol. 22. No.4, pp.359-368, 2001
  11. Davis, R. B., Ounpuu, S., Tyburski, D. and Gage, J. R., 'A gait analysis data collection and reduction technique', Human Movement Sci, Vol. 10, pp.575-587, 1991 https://doi.org/10.1016/0167-9457(91)90046-Z