Non-contact capacitance sensing for continuous locomotion mode recognition: Design specifications and experiments with an amputee

IEEE International Conference on Rehabilitation Robotics

Volumn , Issue , 2013, Pages

  Zheng, Enhao ^a   Wang, Long ^a   Luo, Yimin ^b   Wei, Kunlin ^a   Wang, Qining ^a  

^a PEKING UNIVERSITY   (China)

^b National Rehabilitation Center for Rehabilitation Technical Aids   (China)

Author keywords

[No Author keywords available]

Indexed keywords

CAPACITANCE SENSING; CLASSIFICATION METHODS; CONTINUOUS LOCOMOTION; DESIGN SPECIFICATION; LOWER LIMB PROSTHESIS; QUADRATIC DISCRIMINANT ANALYSIS; RECOGNITION ACCURACY; TRANSTIBIAL AMPUTEES;

CAPACITANCE; DISCRIMINANT ANALYSIS; ELECTROLYTIC CAPACITORS; EXPERIMENTS; ROBOTICS; SENSORS;

ARTIFICIAL LIMBS;

AMPUTATION; HUMAN; LEG; LOCOMOTION; MALE; MIDDLE AGED; PROSTHESIS;

AMPUTATION; HUMANS; LEG; LOCOMOTION; MALE; MIDDLE AGED; PROSTHESIS DESIGN;

EID: 84891112871     PISSN: 19457898     EISSN: 19457901     Source Type: Conference Proceeding    
DOI: 10.1109/ICORR.2013.6650410     Document Type: Conference Paper

References (21)

1. S. Au, M. Berniker, and H. Herr, Powered ankle-foot prosthesis to assist level-ground and stair-descent gaits, Neural Netw., vol. 21, no. 4, pp. 654-666, May 2008.
2. R. Versluys, A. Desomer, G. Lenaerts, M. Van Damme, P. Bey, G. Van der Perre, L. Peeraer, and D. Lefeber, A pneumatically powered below-knee prosthesis: Design specifications and first experiments with an amputee, Proc. of the 2nd IEEE/RAS-EMBS Int. Conf. Biomedical Robotics and Biomechatronics, 2008, pp. 372-377.
3. S. Au, J.Weber, and H. Herr, Powered ankle-foot prosthesis improves walking metabolic economy, IEEE Trans. Robotics, vol. 25, no. 1, pp. 51-66, 2009.
4. F. Sup, H.A. Varol, J. Mitchell, T. Withrow, and M. Goldfarb, Preliminary evaluations of a self-contained anthropomorphic transfemoral prosthesis, IEEE/ASME Trans. Mechatronics, vol. 14, no. 6, pp. 667-676, 2009.
5. J. Zhu, Q. Wang, L. Wang, PANTOE 1: Biomechanical design of powered ankle-foot prosthesis with compliant joints and segmented foot, Proc. of the IEEE/ASME International Conference on Advanced Intelligent Mechatronics, 2010, pp. 31-36.
6. K. Yuan, J. Zhu, Q. Wang, and L. Wang, Finite-state control of powered below-knee prosthesis with ankle and toe, Proc. of the 18th IFAC World Congress, 2011, pp. 2865-2870.
7. B.E. Lawson, H.A. Varol, and M. Goldfarb, Standing stability enhancement with an intelligent powered transfemoral prosthesis, IEEE Trans Biomed. Eng., vol. 58, no. 9, pp. 2617-2624, 2011.
8. Q. Wang, J. Zhu, Y. Huang, K. Yuan, and L. Wang, Segmented foot with compliant actuators and its applications to lower-limb prostheses and exoskeletons, Smart actuation and sensing systems-Recent advances and future challenges, edited by G. Berselli, R. Vertechy, G. Vassura, I-Tech Education and Publishing, 2012.
9. H. Huang, T. A. Kuiken, and R. D. Lipschutz, A strategy for identifying locomotion modes using surface electromyography, IEEE Trans. Biomed. Eng., vol. 56, no. 1, pp. 65-72, 2009.
10. X. Zhang, Y. Liu, F. Zhang, J. Ren, Y. L. Sun, Q. Yang, and H. Huang, On design and implementation of neural-machine interface for artificial legs, IEEE Trans. Ind. Inform., vol. 8, pp. 418-429, 2012.
11. H. Huang, F. Zhang, Y. Sun, and H. He, Design of a robust EMG sensing interface for pattern classification, J. Neural. Eng., vol. 7, pp. 056005, 2010.
12. H. Huang, F. Zhang, L. J. Hargrove, Z. Dou, D. R. Rogers, and K. B. Englehart, Continuous locomotion-mode identification for prosthetic legs based on neuromuscular-mechanical fusion, IEEE Trans. Biomed. Eng., vol. 58, no. 10, pp. 2867-2875, 2011.
13. A. Y. Yang, R. Jafari, S. S. Sastry, and R. Bajcsy, Distributed recognition of human actions using wearable motion sensor networks, Journ. Amb. Intell. Smart Env., vol. 1, pp. 103-115, 2009.
14. D. Gafurov and E. Snekkenes, Gait recognition using wearable motion recording sensors, EURASIP Journ. Adv. Signal Process., 2009.
15. L. Atallah, B. Lo, R. Ali, R. King, and G. Z. Yang, Real-time activity classification using ambient and wearable sensors, IEEE Trans. Info. Tech. Biomed., vol. 13, pp. 1031-1039, 2009.
16. X. Wang, Q. Wang, E. Zheng, K. Wei, and L. Wang, A wearable plantar pressure measurement system: design specifications and first experiments with an amputee, Proc. of the 12th Int. Conf. Intelligent Autonomous Systems, 2012, pp. 273-281.
17. S. Jain, G. Singhal, R. J. Smith, R. Kaliki, and N. Thakor, Improving long term myoelectric decoding, using an adaptive classifier with label correction, Proc. of the 4th IEEE/RAS-EMBS Int. Conf. Biomedical Robotics and Biomechatronics, 2012, pp. 532-537.
18. E. Zheng, B. Chen, Q. Wang, K. Wei, and L. Wang, A wearable capacitive sensing system with phase-dependent classifier for locomotion mode recognition, Proc. of the 4th IEEE RAS/EMBS Int. Conf. Biomedical Robotics and Biomechatronics, 2012, pp. 1747-1752.
19. S. Bamberg, A. Y. Benbasat, D. M. Scarborough, D. E. Krebs, and J. A. Paradiso, Gait analysis using a shoe-integrated wireless sensor system, IEEE Trans. Inform. Techn. Biomed., vol. 12, pp. 413-423, 2008.
20. K. Kong and M. Tomizuka, A gait monitoring system based on air pressure sensors embedded in a shoe, IEEE/ASME Trans. Mech., vol. 14, pp. 358-370, 2009.
21. R. G. Lyons, Understanding digital signal processing, third edition, Pearson Education, Inc., 2011.