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Development of real-time gait phase detection system for a lower extremity exoskeleton robot

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Abstract

In this paper, we develop an insole sensor system that can determine various dynamic models of a lower extremity exoskeleton. The study analyzed the kinematic model of exoskeleton robot for lower limb that changes according to the gait phase detection of a human. Based on the ground reaction force (GRF) that is generated when walking, the sensing type, location, and the number of sensors were selected to proceed on insole sensor development. Using the COP, an algorithm was developed that is capable of detecting gait phase with small number of sensors. An experiment was conducted to evaluate the developed insole sensor system and the gait phase detection algorithm.

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References

  1. Lee, H., Kim, W., Han, J., and Han, C., “The Technical Trend of the Exoskeleton Robot System for Human Power Assistance,” Int. J. Precis. Eng. Manuf., Vol. 13, No. 8, pp. 1491–1497, 2012.

    Article  Google Scholar 

  2. Kazerooni, H., Racine, J.-L., Huang, L., and Steger, R., “On the Control of the Berkeley Lower Extremity Exoskeleton (BLEEX),” Proc. of IEEE International Conference on Robotics and Automation, pp. 4353–4360, 2005.

    Google Scholar 

  3. Zoss, A., Kazerooni, H., and Chu, A., “On the Mechanical Design of the Berkeley Lower Extemity Exoskeleton,” IEEE IROS, Edmunton Canada, 2005. (DOI: 10.1109/IROS.2005.1545453)

    Google Scholar 

  4. Kazerooni, H., Steger, R., and Huang, L., “Hybrid Control of the Berkeley Lower Extremity Exoskeleton (BLEEX),” The International Journal of Robotics Research, Vol. 25, Nos. 5-6, pp. 561–573, 2006.

    Article  Google Scholar 

  5. Abellanas, A., Frizera, A., Ceres, R., and Gallego, J., “Estimation of Gait Parameters by Measuring Upper Limb–Walker Interaction Forces,” Sensors and Actuators A: Physical, Vol. 162, No. 2, pp. 276–283, 2010.

    Article  Google Scholar 

  6. Bae, J. and Tomizuka, M., “A Tele-Monitoring System for Gait Rehabilitation with an Inertial Measurement Unit and a Shoe-Type Ground Reaction Force Sensor,” Mechatronics, Vol. 23, No. 6, pp. 646–651, 2013.

    Article  Google Scholar 

  7. Skelly, M. M. and Chizeck, H. J., “Real-Time Gait Event Detection for Paraplegic Fes Walking,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol. 9, No. 1, pp. 59–68, 2001.

    Article  Google Scholar 

  8. Kong, K. and Tomizuka, M., “A Gait Monitoring System Based on Air Pressure Sensors Embedded in a Shoe,” IEEE/ASME Transactions on Mechatronics, Vol. 14, No. 3, pp. 358–370, 2009.

    Article  Google Scholar 

  9. Bae, J., Kong, K., Byl, N., and Tomizuka, M., “A Mobile Gait Monitoring System for Gait Analysis,” Proc. of IEEE International Conference on Rehabilitation Robotics, pp. 73–79, 2009.

    Google Scholar 

  10. Huang, B., Chen, M., Shi, X., and Xu, Y., “Gait Event Detection with Intelligent Shoes,” Proc. of International Conference on Information Acquisition, pp. 579–584, 2007.

    Google Scholar 

  11. Pappas, I. P. I., Keller, T., Mangold, S., Popovic, M. R., Dietz, V., and Morari, M., “A Reliable Gyroscope-Based Gait-Phase Detection Sensor Embedded in a Shoe Insole,” IEEE Sensors Journal, Vol. 4, No. 2, pp. 268–274, 2004.

    Article  Google Scholar 

  12. I. P. I. Pappas et al. “A Reliable, Insole Embedded Gait Phase Detection Sensor for FES-Assisted Walking,” Journal of IEEE Sensors, Vol. 4, No. 2, pp. 268–274, 2004.

  13. Pappas, I. P. I., Popovic, M. R., Keller, T., Dietz, V., and Morari, M., “A Reliable Gait Phase Detection System,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol. 9, No. 2, pp. 113–125, 2001.

    Article  Google Scholar 

  14. Kim, W.-S., Lee, S.-H., Ryu, J.-K., Baek, J.-H., Kim, D.-W., et al., “Gait Pattern Generation for Lower Extremity Exoskeleton Robot and Verification of Energy Efficiency,” J. Korean Soc. Precis. Eng., Vol. 29, No. 3, pp. 346–353, 2012.

    Article  Google Scholar 

  15. Perry, J. and Burnfield, J. M., “Gait Analysis: Normal and Pathological Function,” SLACK Incorporated, 1992.

    Google Scholar 

  16. Kim, S. J., “A Study on the Assessment Method of Gait Analysis for Normal and above Knee Amputee Using Ground Reaction Force,” M.Sc. Thesis, Konkuk University, 2005.

    Google Scholar 

  17. Park, S.-J. and Kim, J.-S., “The Analysis of Center of Pressure (COP) Displacement Under Loading Position during Walking,” Journal of the Korean Society of Physical Medicine, Vol. 5, No. 1, pp. 15–24, 2010.

    Google Scholar 

  18. Racine, J.-L.C., “Control of a Lower Extremity Exoskeleton for Human Performance Amplification,” Ph.D. Thesis, University of California, 2003.

    Google Scholar 

  19. Interlink Electronics, “FSR 402,” http://www.interlinkelectronics.com/ FSR402.php (Accessed 20 APR 2017)

  20. Tekscan, “FlexiForce A401 Sensor,” https://www.tekscan.com/products-solutions/force-sensors/a401 (Accessed 20 APR 2017)

  21. Pressure Profile Systems, “Capacitive Tactile Sensors,” http://www.pressureprofile.com/capacitive-sensors (Accessed 20 APR 2017)

  22. Seong, D.-H., Jeong, U.-S., and Jo, Y.-J., “A Study on the Categorization of Korean Foot Shapes,” Journal of the Ergonomics Society of Korea, Vol. 25, No. 2, pp. 107–118, 2006.

    Article  Google Scholar 

  23. Hopkins, J. T., Coglianese, M., Glasgow, P., Reese, S., and Seeley, M. K., “Alterations in Evertor/Invertor Muscle Activation and Center of Pressure Trajectory in Participants with Functional Ankle Instability,” Journal of Electromyography and Kinesiology, Vol. 22, No. 2, pp. 280–285, 2012.

    Article  Google Scholar 

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Correspondence to Chang-Soo Han.

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Lim, DH., Kim, WS., Kim, HJ. et al. Development of real-time gait phase detection system for a lower extremity exoskeleton robot. Int. J. Precis. Eng. Manuf. 18, 681–687 (2017). https://doi.org/10.1007/s12541-017-0081-9

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  • DOI: https://doi.org/10.1007/s12541-017-0081-9

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