Hostname: page-component-cd9895bd7-p9bg8 Total loading time: 0 Render date: 2024-12-28T03:10:20.446Z Has data issue: false hasContentIssue false
  • English
  • Français

Adaptive Proxy-Based Controller of an Active Ankle Foot Orthosis to Assist Lower Limb Movements of Paretic Patients

Published online by Cambridge University Press:  18 March 2019

Weiguang Huo Open the ORCID record for Weiguang Huo [Opens in a new window] ,
Victor Arnez-Paniagua ,
Guangzheng Ding ,
Yacine Amirat  and
Samer Mohammed
Weiguang Huo*
Affiliation:
Department of Mechanical Engineering, Imperial College London, UK
Victor Arnez-Paniagua
Affiliation:
Laboratoire Images, Signaux et Systèmes Intelligents (LISSI), Université Paris-Est Créteil (UPEC), 94400 Vitry-sur-Seine, France. E-mails: victor.arnezpaniagua@univ-paris-est.fr; amirat@u-pec.fr; m201672442@hust.edu.cn; samer.mohammed@u-pec.fr
Guangzheng Ding
Affiliation:
Laboratoire Images, Signaux et Systèmes Intelligents (LISSI), Université Paris-Est Créteil (UPEC), 94400 Vitry-sur-Seine, France. E-mails: victor.arnezpaniagua@univ-paris-est.fr; amirat@u-pec.fr; m201672442@hust.edu.cn; samer.mohammed@u-pec.fr
Yacine Amirat
Affiliation:
Laboratoire Images, Signaux et Systèmes Intelligents (LISSI), Université Paris-Est Créteil (UPEC), 94400 Vitry-sur-Seine, France. E-mails: victor.arnezpaniagua@univ-paris-est.fr; amirat@u-pec.fr; m201672442@hust.edu.cn; samer.mohammed@u-pec.fr
Samer Mohammed
Affiliation:
Laboratoire Images, Signaux et Systèmes Intelligents (LISSI), Université Paris-Est Créteil (UPEC), 94400 Vitry-sur-Seine, France. E-mails: victor.arnezpaniagua@univ-paris-est.fr; amirat@u-pec.fr; m201672442@hust.edu.cn; samer.mohammed@u-pec.fr
*
*Corresponding author. E-mail: w.huo@imperial.ac.uk
Get access Rights & Permissions [Opens in a new window]

Summary

This paper deals with the control of an active ankle foot orthosis (AAFO) for paretic patients. State of the art methods using an AAFO try to track a predefined trajectory of the ankle joint while guaranteeing the wearer’s safety in the presence of a large tracking error. Combining the wearer’s safety and tracking accuracy is generally difficult to achieve at the same time, hence a trade-off should be found. Proxy-based sliding mode control (PSMC) offers great performances in both position tracking and safety guarantee. However, its tracking performance is subject to the influences of parameter uncertainties and external disturbances that generally occur during walking. This paper introduces an adaptation interaction method to the basic PSMC with an online adaptation of the proportional, integral and derivative parameters. At the same time, a gait phase-based ankle reference generation algorithm was proposed to adjust the joint reference trajectory in real time. The experiments using the AAFO show better tracking results with respect to basic PSMC while guaranteeing the safety.

Keywords

Active ankle foot orthosisOnline reference generationAdaptive PSMCWearable robotGait rehabilitation
Type
Articles
Information
Robotica , Volume 37 , Special Issue 12: Wearable Robotics: Dynamics, Control and Applications , December 2019 , pp. 2147 - 2164
Copyright
© Cambridge University Press 2019 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Blaya, J. A., Newman, D. and Herr, H., “Active Ankle Foot Orthoses (AAFO),” Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA (2002) pp. 275–277.Google Scholar
Hwang, S., Kim, J., Yi, J., Tae, K., Ryu, K. and Kim, Y., “Development of an Active Ankle Foot Orthosis for the Prevention of Foot Drop and Toe Drag,” International Conference on Biomedical and Pharmaceutical Engineering (ICBPE), IEEE, Singapore (2006) pp. 418–423.Google Scholar
Shorter, K. A., Xia, J., Hsiao-Wecksler, E. T., Durfee, W. K. and Kogler, G. F., “Technologies for powered ankle-foot orthotic systems: Possibilities and challenges,” IEEE ASME Trans. Mechatron. 18(1), 337–347 (2013).CrossRefGoogle Scholar
Blaya, J. A. and Herr, H., “Adaptive control of a variable-impedance ankle-foot orthosis to assist drop-foot gait,” IEEE Trans. Neural. Syst. Rehabil. Eng. 12(1), 24–31 (2004).CrossRefGoogle ScholarPubMed
Hitt, J., Oymagil, A. M., Sugar, T., Hollander, K., Boehler, A. and Fleeger, J., “Dynamically Controlled Ankle-foot Orthosis (DCO) with Regenerative Kinetics: Incrementally Attaining User Portability,” IEEE International Conference on Robotics and Automation (ICRA), IEEE, Roma, Italy (2007) pp. 1541–1546.Google Scholar
Boehler, A. W., Hollander, K. W., Sugar, T. G. and Shin, D., “Design, Implementation and Test Results of a Robust Control Method for a Powered Ankle Foot Orthosis (AFO),” IEEE International Conference on Robotics and Automation (ICRA), IEEE, Pasadena, CA, USA (2008) pp. 2025–2030.Google Scholar
Moltedo, M., Baˇcek, T., Langlois, K., Junius, K., Vanderborght, B. and Lefeber, D., “Design and Experimental Evaluation of a Lightweight, High-torque and Compliant Actuator for an Active Ankle Foot Orthosis,” IEEE International Conference on Rehabilitation Robotics (ICORR), IEEE, London, UK (2017) pp. 283–288.Google Scholar
Ward, J. A., Hitt, J., Sugar, T. and Bharadwaj, K., “Dynamic Pace Controller for the Robotic Gait Trainer,” International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC-CIE (2006), ASME, Pennsylvania, USA (2006) pp. 575–581.Google Scholar
Ferris, D. P., Gordon, K. E., Sawicki, G. S. and Peethambaran, A., “An improved powered ankle–foot orthosis using proportional myoelectric control,” Gait Posture 23(4), 425–428 (2006).CrossRefGoogle ScholarPubMed
Shorter, K. A., Kogler, G. F., Loth, E., Durfee, W. K. and Hsiao-Wecksler, E. T., “A portable powered anklefoot orthosis for rehabilitation,” J. Rehabil. Res. Dev. 48(4), 459–472 (2011).CrossRefGoogle Scholar
Jamwal, P. K., Xie, S. Q., Hussain, S. and Parsons, J. G., “An adaptive wearable parallel robot for the treatment of ankle injuries,” IEEE/ASME Trans. Mechatron. 19(1), 64–75 (2014).CrossRefGoogle Scholar
Ren, Y., Wu, Y.-N., Yang, C.-Y., Xu, T., Harvey, R. and Zhang, L.-Q., “Developing a wearable ankle rehabilitation robotic device for in-bed acute stroke rehabilitation,” IEEE Trans. Neural Syst. Rehabil. Eng. 25(6), 589–596 (2016).CrossRefGoogle ScholarPubMed
Arnez-Paniagua, V., Rifaï, H., Amirat, Y. and Mohammed, S., “Adaptive Control of an Actuated-Ankle-Foot-Orthosis,” IEEE International Conference on Rehabilitation Robotics (ICORR), IEEE, London, UK (2017) pp. 1584–1589.Google Scholar
Ab Patar, M. N. A., Said, A. F., Mahmud, J., Majeed, A. P. A. and Razman, M. A., “System Integration and Control of Dynamic Ankle Foot Orthosis for Lower Limb Rehabilitation,” IEEE International Symposium on Technology Management and Emerging Technologies (ISTMET), IEEE, Bandung, Indonesia (2014) pp. 82–85.Google Scholar
Arnez-Paniagua, V., Huo, W., Colorado-Cervantes, I., Mohammed, S. and Amirat, Y., “A Hybrid Approach Towards Assisting Ankle Joint of Paretic Patients,” International Functional Electrical Stimulation Society Conference (IFESS) (2016), La Grande-Motte, France (2016) pp. 1–4.Google Scholar
Pérez-Ibarra, J. C. and Siqueira, A. A. G., “Comparison of Kinematic and EMG Parameters between Unassisted, Fixed-and Adaptive-stiffness Robotic-assisted Ankle Movements in Post-stroke Subjects,” International Conference on Rehabilitation Robotics (ICORR), IEEE, London, UK (2017) pp. 461–466.CrossRefGoogle Scholar
el Zahraa Wehbi, F., Huo, W., Amirat, Y., El Rafei, M., Khalil, M. and Mohammed, S., “Active Impedance Control of a Knee-joint Orthosis during Swing Phase,” IEEE International Conference on Rehabilitation Robotics (ICORR), IEEE, London, UK (2017) pp. 435–440.Google Scholar
Lawn, M. J., Takashima, M., Ninomiya, M., Yu, J., Soma, K. and Ishimatsu, T., “Development of an actuation system for a rotary hydraulic brake on a low cost light weight knee-ankle-foot orthosis,” IEEE Sensors, 1–4 (2015).Google Scholar
Roy, A., Krebs, H. I., Iqbal, K., Macko, N. R., Macko, R. F. and Forrester, L. W., “Facilitating Push-off Propulsion: A Biomechanical Model of Ankle Robotics Assistance for Plantarflexion Gait Training in Stroke,” IEEE International Conference on Biomedical Robotics and Biomechatronics, IEEE, Sao Paulo, Brazil (2014) pp. 656–663.CrossRefGoogle Scholar
Rifaï, H., Mohammed, S., Hassani, W. and Amirat, Y., “Nested saturation based control of an actuated knee joint orthosis,” Mechatronics 23(8), 1141–1149 (2013).CrossRefGoogle Scholar
Brahmi, B., Saad, M., Ochoa-Luna, C. and Rahman, M. H., “Adaptive Control of an Exoskeleton Robot with Uncertainties on Kinematics and Dynamics,” International Conference on Rehabilitation Robotics (ICORR), IEEE, London, UK (2017) pp. 1369–1374.CrossRefGoogle Scholar
Zhang, M., Cao, J., Xie, S. Q., Zhu, G., Zeng, X., Huang, X. and Xu, Q., “A preliminary study on robot-assisted ankle rehabilitation for the treatment of drop foot,” J. Intell. Robot. Syst. 91(2), 1–9 (2017).Google Scholar
Bharadwaj, K., Sugar, T. G., Koeneman, J. B. and Koeneman, E. J., “Design of a robotic gait trainer using spring over muscle actuators for ankle stroke rehabilitation,” J. Biomech. Eng. 127(6), 1009–1013 (2005).CrossRefGoogle ScholarPubMed
Huo, W., Mohammed, S., Moreno, J. C. and Amirat, Y., “Lower limb wearable robots for assistance and rehabilitation: A state of the art,” IEEE Syst. J. 10(3), 1068–1081 (2016).CrossRefGoogle Scholar
Ward, J., Sugar, T., Standeven, J. and Engsberg, J. R., “Stroke Survivor Gait Adaptation and Performance after Training on a Powered Ankle Foot Orthosis,” International Conference on Robotics and Automation (ICRA), IEEE, Anchorage, Alaska (2010) pp. 211–216.Google Scholar
Veneva, I. and Ferreira, N., “Adaptive System for Control of Active Ankle-foot Orthosis and Gait Analysis,” In : Mathematical Methods in Engineering (Springer, Dordrecht, 2014) pp. 153–163.Google Scholar
Arnez-Paniagua, V., Rifaï, H., Amirat, Y. and Mohammed, S., “Adaptive Control of an Actuated-Ankle- Foot-Orthosis,” International Conference on Rehabilitation Robotics (ICORR), IEEE, London, UK (2017) pp. 1584–1589.CrossRefGoogle Scholar
Jiménez-Fabián, R. and Verlinden, O., “Review of control algorithms for robotic ankle systems in lower-limb orthoses, prostheses, and exoskeletons,” Med. Eng. Phys. 34(4), 397–408 (2012).CrossRefGoogle ScholarPubMed
Cain, S. M., Gordon, K. E. and Ferris, D. P., “Locomotor adaptation to a powered ankle-foot orthosis depends on control method,” J. Neuroeng. Rehabil. 4(1), 1 (2007).CrossRefGoogle ScholarPubMed
Van Damme, M., Vanderborght, B., Verrelst, B., Van Ham, R., Daerden, F. and Lefeber, D., “Proxy-based sliding mode control of a planar pneumatic manipulator,” Int. J. Rob. Res. 28(2), 266–284 (2009).CrossRefGoogle Scholar
Huang, J., Guan, Z.-H., Matsuno, T., Fukuda, T. and Sekiyama, K., “Sliding-mode velocity control of mobilewheeled inverted-pendulum systems,” IEEE Trans. Rob. 26(4), 750–758 (2010).CrossRefGoogle Scholar
Yao, B. and Tomizuka, M., “Adaptive robust control of SISO nonlinear systems in a semi-strict feedback form,” Automatica 33(5), 893–900 (1997).CrossRefGoogle Scholar
Kikuuwe, R. and Fujimoto, H., “Proxy-based SlidingMode Control for Accurate and Safe Position Control,” IEEE International Conference on Robotics and Automation (ICRA), IEEE, Orlando, Florida (2006) pp. 25–30.Google Scholar
Huang, M., Huang, X., Tu, X., Li, Z. and Wen, Y., “An online gain tuning proxy-based sliding mode control using neural network for a gait training robotic orthosis,” Cluster Comput. 19(4), 1987–2000 (2016).CrossRefGoogle Scholar
Badreddine, B., Zaremba, A., Sun, J. and Lin, F., “Active damping of engine idle speed oscillation by applying adaptive pid control,” Technical report, SAE Technical Paper (2001).CrossRefGoogle Scholar
Hutin, E., Pradon, D., Barbier, F., Bussel, B., Gracies, J.-M. and Roche, N., “Walking velocity and lower limb coordination in hemiparesis,” Gait Posture 36(2), 205–211 (2012).CrossRefGoogle ScholarPubMed
Kikuuwe, R., Yasukouchi, S., Fujimoto, H. and Yamamoto, M., “Proxy-based sliding mode control: A safer extension of pid position control,” IEEE Trans. Rob. 26(4), 670–683 (2010).CrossRefGoogle Scholar
Barbalata, C., De Carolis, V., Dunnigan, M. W., Petillot, Y. and Lane, D., “An Adaptive Controller for Autonomous Underwater Vehicles,” IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Hamburg, Germany (2015) pp. 1658–1663.CrossRefGoogle Scholar
Brandt, R. D. and Lin, F., “Adaptive interaction and its application to neural networks,” Inf. Sci. 121(3–4), 201–215 (1999).CrossRefGoogle Scholar
Badreddine, B. M. and Lin, F., “Adaptive PID Controller for Stable/unstable Linear and Non-linear Systems,” IEEE International Conference on Control Applications (CCA), IEEE, Mexico City, Mexico (2001) pp. 1031–1036.Google Scholar
Zhao, Z.-Y., Tomizuka, M. and Isaka, S., “Fuzzy gain scheduling of pid controllers,” IEEE Trans. Syst. Man Cybern. 23(5), 1392–1398 (1993).CrossRefGoogle Scholar
Rifai, H., Mohammed, S., Daachi, B. and Amirat, Y., “Adaptive Control of a Human-driven Knee Joint Orthosis,” IEEE International Conference on Robotics and Automation (ICRA), St. Paul, Minnesota, USA (2012) pp. 2486–2491.Google Scholar