Journal of the Korean Society for Precision Engineering (한국정밀공학회지)

Korean Society for Precision Engineering (한국정밀공학회)
권호 표지
DOI QR코드

DOI QR Code

A Study on Particular Abnormal Gait Using Accelerometer and Gyro Sensor

가속도센서와 각속도센서를 이용한 특정 비정상보행에 관한 연구

  • Heo, Geun-Sub (School of Mechanical Engineering, Kyungpook National University) ;
  • Yang, Seung-Han (School of Mechanical Engineering, Kyungpook National University) ;
  • Lee, Sang-Ryong (School of Mechanical Engineering, Kyungpook National University) ;
  • Lee, Jong-Gyu (Institute of Mechanical Engineering Technology, Kyungpook National University) ;
  • Lee, Choon-Young (School of Mechanical Engineering, Kyungpook National University)
  • Received : 2011.07.15
  • Accepted : 2012.07.26
  • Published : 2012.11.01
Download PDF
⟨ Previous Next ⟩

Abstract

Recently, technologies to help the elderly or disabled people who have difficulty in walking are being developed. In order to develop these technologies, it is necessary to construct a system that gathers the gait data of people and analysis of these data is also important. In this research, we constructed the development of sensor system which consists of pressure sensor, three-axis accelerometer and two-axis gyro sensor. We used k-means clustering algorithm to classify the data for characterization, and then calculated the symmetry index with histogram which was produced from each cluster. We collected gait data from sensors attached on two subjects. The experiment was conducted for two kinds of gait status. One is walking with normal gait; the other is walking with abnormal gait (abnormal gait means that the subject walks by dragging the right leg intentionally). With the result from the analysis of acceleration component, we were able to confirm that the analysis technique of this data could be used to determine gait symmetry. In addition, by adding gyro components in the analysis, we could find that the symmetry index was appropriate to express symmetry better.

Keywords

References

  1. Steger, R., Kim, S. H., and Kazerooni, H., "Control Scheme and Networked Control Architecture for the Berkeley Lower Extremity Exoskeleton (BLEEX)," Proceedings IEEE Int. Conf. on Robotics and Automation, pp. 3469-3476, 2006.
  2. Hayashi, T., Kawamoto, H., and Sankai, Y., "Control Method of Robot Suit HAL Working as Operator's Muscle using Biological and Dynamical Information," IEEE Int. Conf. on Intelligent Robots and Systems, pp. 3063-3068, 2005.
  3. Ko, J. H., Son, K., Park, J. H., and Suh, J. T., "Gait Study on the Normal and ACL Deficient Patients after Ligament Reconstruction Surgey using Chaos Analysis Method," J. of the KSPE, Vol. 23, No. 2, pp. 164-171, 2006.
  4. Choi, J. S., Oh, H. S., Kang, D. W., Mun, K. R., Choi, M. H., Lee, S. J., Jeong, S. C., and Tack, G. R., "Comparison of Differences among Alzheimer's Disease, Mild Cognitive Impairment and Healthy Elderly using Gait and Cognitive Function," Proc. of KSPE Spring Conference, pp. 1403-1404, 2010.
  5. Muniz, A. M. S., Manfio, E. F., Andrade, M. C., and Nadal, J., "Principal Component Analysis of Vertical Ground Reaction Force: a Powerful Method to Discriminate Normal and Abnormal Gait and Assess Treatment," 28th IEEE EMBS, pp. 2683-2686, 2010.
  6. Skelly, M. M. and Chizeck, H. J., "Real Time Gait Event Detection during FES Paraplegic Walking," 19th IEEE EMBS, pp. 1934-1937, 1997.
  7. Kang, D. W., Tack, G. K., Choi, J. S., Bang, Y. H., and Kang, M. S., "Measurement of Gait Pattern using Inertial Sensors," Proc. of KSPE Autumn Conference, pp. 959-960, 2010.
  8. Heo, J. U., Kim, C. S., and Eom, G. M., "Gait-Event Detection for FES Locomotion," J. of the KSPE, Vol. 22, No. 3, pp. 170-178, 2005.
  9. Ahn, S. C., Hwang, S. J., Kang, S. J., and Kim, Y. H., "Development and Evaluation of a New Gait Phase Detection System using FSR Sensors and a Gyrosensor," J. of the KSPE, Vol. 21, No. 10, pp. 196-203, 2004.
  10. Sagawa, K., Inooka, H., and Satoh, Y., "Nonrestricted measurement of walking distance," IEEE Int. Conf. on Systems, Man, and Cybernetics, Vol. 3, pp. 1847-1852, 2000.
  11. Ciobanu, R., Dontu, O., Besnea, D., Avarvarei, I., and Voiculescu, I., "Inertial system used to analyze normal and pathological human gait," IEEE Int. Conf. on Mechanical and Electrical Technology, pp. 109-112, 2010.
  12. Bamberg, S., Benbasat, A. Y., Scarborough, D. M., Krebs, D. E., and Paradiso, J. A., "Gait Analysis Using a Shoe-Integrated Wireless Sensor System," IEEE Transactions on Information Technology in Biomedicine, Vol. 12, No. 4, pp. 413-423, 2008. https://doi.org/10.1109/TITB.2007.899493
  13. Paradiso, J., Hu, E., and Hsiao, K. Y., "The CyberShoe: A Wireless Multisensor Interface for a Dancer's Feet," International Dance and Technology 99, 1999.
  14. AVRMALL, "ATmega2561 datasheet," http://www.avrmall.com
  15. INTERLINK ELECTRONICS, "Force Sensing Resistor Integration Guide and Evaluation Parts Catalog," http://www.interlinkelectronics.com
  16. NEWTC Co. Ltd., "AM-3AXIS V02 Manual," http://www.NewTC.co.kr
  17. Ding, Y., Yang, X., Kavs, A. J., and Li, J., "A Novel Piecewise Linear Segmentation for Time Series," 2nd Int. Conf. on Computer and Automation Engineering, pp. 52-55, 2010.
  18. Wikipedia, "k-means Clustering," http://en.wikipedia.org
  19. Anna, A. S. and Wickström, N., "A Symbol-Based Approach to Gait Analysis from Acceleration Signals: Identification and Detection of Gait Events and a New Measure of Gait Symmetry," IEEE Transactions on Information Technology in Biomedicine, Vol. 14, No. 5, pp. 1180-1187, 2010. https://doi.org/10.1109/TITB.2010.2047402