Human Motion Assistance using Walking-aid Robot and Wearable Sensors

Jian Huang, Wenxia Xu, Zhen Shu, Samer Mohammed

Abstract

An omni-directional walking-aid robot is developed for the elderly in this study. A motion control strategy of walking-aid robot based on observing human status by wearable sensors is proposed. During normal walking, the robot is controlled by a conventional admittance control scheme. When the tendency of a fall is detected, the robot will immediately react to prevent the user from falling down. The distance between the human Centre of Pressure (COP) and the midpoint of two human feet is assumed to be a significant feature to detecting the fall events. Dubois possibility theory is applied to describe the membership function of ‘normal walking’ state. A threshold based fall detection approach is obtained from online evaluation of the walking status. Finally, experiments demonstrate the validity of the proposed strategy.

References

  1. Alwan, M., Felder, R. A., 2008. Eldercare Technology for Clinical Practitioners Totowa, NJ: Humana Press.
  2. Baek J., Lee G., Park W., et al. 2004. Accelerometer Signal Processing for User Activity Detection. Knowledge-Based Intelligent Information and Engineering Systems Lecture Notes in Computer Science, 32(15): 610-617.
  3. Dubowsky, S., Genot, F., Godding, S., K. Skwersky, H. A. Yu, H., and Yu, L., 2000. Pamm-A robotic aid to the elderly for mobility assistance and monitoring: A “helping-hand” for the elderly, Proceeding of IEEE International Conference on Robotics and Automation, San Francisco, CA, 570-576.
  4. Dubois D., Prade H., 2003. Possibility Theory and Its Applications: A Retrospective and Prospective View. Proceeding of IEEE International Conference on Fuzzy Systems, 25-28.
  5. Griffiths, C., Rooney, C., Brock, A., 2008. Leading causes of death in England and Wales-how should we group causes? Health Statistics Quarterly 28. Office for National Statistics.
  6. Hirata, Y., Baba, T., and Kosuge, K., 2003. Motion control of omni-directional type walking support system 'walking helper', Proceeding of ROMAN, Millbrace, CA, 85-90.
  7. Hirata, Y., Hara, A., Kosuge, K., 2004. Passive-type Intelligent Walking Support System “RT Walker”, Proceedings of the 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems, 3871- 3876.
  8. Huang J., Di P., Wakita, K., Fukuda, T., Sekiyama, K., 2008. Study of Fall Detection Using Intelligent Cane Based on Sensor Fusion. 2008 International Symposium on Micro-Nano Mechatronics and Human Science, 495-500.
  9. Huang, J., Di, P.; Fukuda, T., Matsuno, T., 2008. Motion control of omni-directional type cane robot based on human intention. IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS, 273-278.
  10. Jonsson, L., 2001. The Importance of the 4- WheeledWalker for Elderly Women Living in their Home Environment, The Swedish Handicap Institute.
  11. Lee, C. Y., Jeong, I. K., Lee, I. H., 2004. Development of Rehabilitation Robot Systems for Walking-Aid, Proceeding of IEEE International Conference on Robotics & Automation, New Orleans, LA. 3: 2468- 2473.
  12. Lee H. J., Chou L. S., 2006. Detection of Gait Instability Using the Center of Mass and Center of Pressure Inclination Angles. Archives of Physical Medicine and Rehabilitation, 87(4): 569-575.
  13. Masaki S., Toshiyo T., Metin A., etc al. 2002. Discrimination of Walking Patterns Using WaveletBased Fractal Analysis, IEEE transactions on neural systems and rehabilitation engineering, 10(3): 188- 196.
  14. Mohammed, S., Yacine A. and Hala R., 2012. Lower-limb movement assistance through wearable robots: state of the Art and challenges. Advanced Robotics, 26(1-2): 1- 22.
  15. Mubashir, M., Shao, L., Seed, L., 2013. A survey on fall detection: Principles and approaches. Neurocomputing, 100(16): 144-152.
  16. Rentschler, A. J., Cooper, R. A., Blaschm, B., Boninger, M. L., 2003. Intelligent walkers for the elderly Performance and safety testing of VA-PAMAID robotic walker, Journal of Rehabilitation Research and Development, 40(5): 423-432.
  17. Wang N., Eliathamby A., Nigel H. L., Branko G. C., 2007. Accelerometry Based Classification of Walking Patterns Using Time-frequency Analysis, Proceedings of the 29th Annual International, Conference of the IEEE EMBS, Lyon, France, 4899-4902.
  18. Wakita K., Huang J., Di P., Sekiyama K., Fukuda T., 2012. Human-Walking-Intention-Based Motion Control of an Omnidirectional-Type Cane Robot. IEEE/ASME Trans on Mechatronics. (Online Available)
  19. Ye J. Y., Huang J., He J. P., Tao C. J., Wang X. T., 2012. Development of a width-changeable intelligent walking-aid robot. IEEE International Conference on Micro-Nano Mechatronics and Human Science, 358- 363.
  20. Yu H., Spenko M., Dubowsky S., 2003. An adaptive shared control system for an intelligent mobility aid for the elderly, Autom. Robots, 15(1): 53-66.
  21. Zhu R., and Zhou Z. Y., 2004, A Real-Time Articulated Human Motion Tracking Using Tri-Axis Inertial/Magnetic Sensors Package. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 12(2): 295-302.
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Paper Citation


in Harvard Style

Huang J., Xu W., Shu Z. and Mohammed S. (2013). Human Motion Assistance using Walking-aid Robot and Wearable Sensors . In Proceedings of the International Congress on Neurotechnology, Electronics and Informatics - Volume 1: RoboAssist, (NEUROTECHNIX 2013) ISBN 978-989-8565-80-8, pages 199-204. DOI: 10.5220/0004664101990204


in Bibtex Style

@conference{roboassist13,
author={Jian Huang and Wenxia Xu and Zhen Shu and Samer Mohammed},
title={Human Motion Assistance using Walking-aid Robot and Wearable Sensors},
booktitle={Proceedings of the International Congress on Neurotechnology, Electronics and Informatics - Volume 1: RoboAssist, (NEUROTECHNIX 2013)},
year={2013},
pages={199-204},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004664101990204},
isbn={978-989-8565-80-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Congress on Neurotechnology, Electronics and Informatics - Volume 1: RoboAssist, (NEUROTECHNIX 2013)
TI - Human Motion Assistance using Walking-aid Robot and Wearable Sensors
SN - 978-989-8565-80-8
AU - Huang J.
AU - Xu W.
AU - Shu Z.
AU - Mohammed S.
PY - 2013
SP - 199
EP - 204
DO - 10.5220/0004664101990204