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Design and Evaluation of a Soft Assistive Lower Limb Exoskeleton

Published online by Cambridge University Press:  26 February 2019

Christian Di Natali ,
Tommaso Poliero ,
Matteo Sposito ,
Eveline Graf ,
Christoph Bauer ,
Carole Pauli ,
Eliza Bottenberg ,
Adam De Eyto ,
Leonard O’Sullivan  and
Andrés F. Hidalgo
...Show all authors
Christian Di Natali*
Affiliation:
Department of Advanced Robotics, Istituto Italiano di Tecnologia, Genoa, Italy E-mails: [email protected], [email protected], [email protected], [email protected]
Tommaso Poliero
Affiliation:
Department of Advanced Robotics, Istituto Italiano di Tecnologia, Genoa, Italy E-mails: [email protected], [email protected], [email protected], [email protected] Department of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genoa, Genoa, Italy
Matteo Sposito
Affiliation:
Department of Advanced Robotics, Istituto Italiano di Tecnologia, Genoa, Italy E-mails: [email protected], [email protected], [email protected], [email protected]
Eveline Graf
Affiliation:
Institute of Physiotherapy, ZHAW Zurich University of Applied Sciences, Winterthur, Switzerland E-mails: [email protected], [email protected], [email protected]
Christoph Bauer
Affiliation:
Institute of Physiotherapy, ZHAW Zurich University of Applied Sciences, Winterthur, Switzerland E-mails: [email protected], [email protected], [email protected]
Carole Pauli
Affiliation:
Institute of Physiotherapy, ZHAW Zurich University of Applied Sciences, Winterthur, Switzerland E-mails: [email protected], [email protected], [email protected]
Eliza Bottenberg
Affiliation:
Smart Functional Materials Research Group, Saxion University of Applied Sciences, Enschede, The Netherlands. E-mail: [email protected]
Adam De Eyto
Affiliation:
Design Factors Group, University of Limerick, Limerick, Ireland. E-mails: [email protected], [email protected]
Leonard O’Sullivan
Affiliation:
Design Factors Group, University of Limerick, Limerick, Ireland. E-mails: [email protected], [email protected]
Andrés F. Hidalgo
Affiliation:
Centre for Automation and Robotics Consejo Superior de Investigaciones Cientificas (CSIC), Madrid, Spain. E-mail: [email protected]
Daniel Scherly
Affiliation:
Institute of Mechatronic Systems, ZHAW Zurich University of Applied Sciences, Winterthur, Switzerland. E-mails: [email protected], [email protected]
Konrad S. Stadler
Affiliation:
Institute of Mechatronic Systems, ZHAW Zurich University of Applied Sciences, Winterthur, Switzerland. E-mails: [email protected], [email protected]
Darwin G. Caldwell
Affiliation:
Department of Advanced Robotics, Istituto Italiano di Tecnologia, Genoa, Italy E-mails: [email protected], [email protected], [email protected], [email protected]
Jesús Ortiz
Affiliation:
Department of Advanced Robotics, Istituto Italiano di Tecnologia, Genoa, Italy E-mails: [email protected], [email protected], [email protected], [email protected]
*
*Corresponding author. E-mail: [email protected]
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Summary

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Wearable devices are fast evolving to address mobility and autonomy needs of elderly people who would benefit from physical assistance. Recent developments in soft robotics provide important opportunities to develop soft exoskeletons (also called exosuits) to enable both physical assistance and improved usability and acceptance for users. The XoSoft EU project has developed a modular soft lower limb exoskeleton to assist people with low mobility impairments. In this paper, we present the design of a soft modular lower limb exoskeleton to improve person’s mobility, contributing to independence and enhancing quality of life. The novelty of this work is the integration of quasi-passive elements in a soft exoskeleton. The exoskeleton provides mechanical assistance for subjects with low mobility impairments reducing energy requirements between 10% and 20%. Investigation of different control strategies based on gait segmentation and actuation elements is presented. A first hip–knee unilateral prototype is described, developed, and its performance assessed on a post-stroke patient for straight walking. The study presents an analysis of the human–exoskeleton energy patterns by way of the task-based biological power generation. The resultant assistance, in terms of power, was 10.9% ± 2.2% for hip actuation and 9.3% ± 3.5% for knee actuation. The control strategy improved the gait and postural patterns by increasing joint angles and foot clearance at specific phases of the walking cycle.

Keywords

Soft exoskeletonExosuitRobotic wearable deviceQuasi-passive actuationLegged locomotionGait assistance
Type
Articles
Information
Robotica , Volume 37 , Special Issue 12: Wearable Robotics: Dynamics, Control and Applications , December 2019 , pp. 2014 - 2034
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - SA
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike licence (http://creativecommons.org/licenses/by-nc-sa/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the same Creative Commons licence is included and the original work is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use.
Copyright
© Cambridge University Press 2019

References

Available at http://ec.europa.eu/eurostat/statistics-explained/index.php/Population_structure_and_ageing/.Google Scholar
Lakshminarayan, K., Berger, A. K., Fuller, C. C., Jacobs, D. R., Anderson, D. C., Steffen, L. M., Sillah, A. and Luepker, R. V., “Trends in 10-year survival of patients with stroke hospitalized between 1980 and 2000: The Minnesota stroke survey,” Stroke 45(9), 2575–2581 (2014).CrossRefGoogle ScholarPubMed
Yan, T., Cempini, M., Oddo, C. M. and Vitiello, N., “Review of assistive strategies in powered lower-limb orthoses and exoskeletons,” Rob. Auton. Syst. 64, 120–136 (2015).CrossRefGoogle Scholar
Sankai, Y., “HAL: Hybrid Assistive Limb Based on Cybernics,” In: Robotics Research (Springer, Berlin, Heidelberg, 2010) pp. 25–34.CrossRefGoogle Scholar
Hyon, S.-H., Morimoto, J., Matsubara, T., Noda, T. and Kawato, M., “XoR: Hybrid Drive Exoskeleton Robot that can Balance,” 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), San Francisco, CA, USA (IEEE, 2011) pp. 3975–3981.CrossRefGoogle Scholar
Jun, M., Tomoyuki, N. and Sang-Ho, H., “Extraction of Latent Kinematic Relationships Between Human Users and Assistive Robots,” 2012 IEEE International Conference on Robotics and Automation (ICRA), St. Paul, Minnesota, USA (2012) pp. 3090–3915.Google Scholar
Yeh, T.-J., Wu, M.-J., Lu, T.-J., Wu, F.-K. and Huang, C.-R., “Control of McKibben pneumatic muscles for a power-assist, lower-limb orthosis,” Mechatronics 20(6), 686–697 (2010).CrossRefGoogle Scholar
Nakamura, T., Saito, K., Wang, Z. and Kosuge, K., “Realizing Model-Based Wearable Antigravity Muscles Support with Dynamics Terms,” 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2005, IROS 2005, Edmonton, Alberta, Canada (IEEE, 2005) pp. 2694–2699.CrossRefGoogle Scholar
Nakamura, T., Saito, K. and Kosuge, K., “Control of Wearable Walking Support System Based on Human-Model and GRF,” Proceedings of the 2005 IEEE International Conference on Robotics and Automation, 2005, ICRA 2005, Barcelona, Spain (IEEE, 2005) pp. 4394–4399.Google Scholar
Ikehara, T., Nagamura, K., Ushida, T., Tanaka, E., Saegusa, S., Kojima, S. and Yuge, L., “Development of Closed-Fitting-Type Walking Assistance Device for Legs and Evaluation of Muscle Activity,” 2011 IEEE International Conference on Rehabilitation Robotics (ICORR), Zurich, Switzerland (IEEE, 2011) pp. 1–7.CrossRefGoogle Scholar
Kong, K. and Jeon, D., “Design and control of an exoskeleton for the elderly and patients,” IEEE/ASME Trans. Mechatron. 11(4), 428–432 (2006).CrossRefGoogle Scholar
Awad, L. N., Bae, J., O’Donnell, K., De Rossi, S. M., Hendron, K., Sloot, L. H., Kudzia, P., Allen, S., Holt, K. G., Ellis, T. D., and Walsh, C. J., “A soft robotic exosuit improves walking in patients after stroke,” Sci. Trans. Med. 9(400), eaai9084 (2017).CrossRefGoogle ScholarPubMed
Jin, S., Iwamoto, N., Hashimoto, K. and Yamamoto, M., “Experimental evaluation of energy efficiency for a soft wearable robotic suit,” IEEE Trans. Neural Syst. Rehabil. Eng. 25(8), 1192–1201 (2017).CrossRefGoogle ScholarPubMed
Schmidt, K., Duarte, J. E., Grimmer, M., Sancho-Puchades, A., Wei, H., Easthope, C. S. and Riener, R., “The myosuit: Bi-articular anti-gravity exosuit that reduces hip extensor activity in sitting transfers,” Front. Neurorob. 11, 57 (2017).CrossRefGoogle ScholarPubMed
Ortiz, J., Rocon, E., Power, V., de Eyto, A., O’Sullivan, L., Wirz, M., Bauer, C., Schülein, S., Stadler, K. S., Mazzolai, B., and Teeuw, W. B., “XoSoft-A Vision for a Soft Modular Lower Limb Exoskeleton,” In: Wearable Robotics: Challenges and Trends (Springer, Cham, 2017) pp. 83–88.CrossRefGoogle Scholar
Power, V., O’Sullivan, L., de Eyto, A., Schülein, S., Nikamp, C., Bauer, C., Mueller, J. and Ortiz, J., “Exploring User Requirements for a Lower Body Soft Exoskeleton to Assist Mobility,” Proceedings of the 9th ACM International Conference on PErvasive Technologies Related to Assistive Environments, Corfu, Greece (ACM, 2016) p. 69.CrossRefGoogle Scholar
Ortiz, J., Poliero, T., Cairoli, G., Graf, E. and Caldwell, D. G., “Energy efficiency analysis and design optimization of an actuation system in a soft modular lower limb exoskeleton,” IEEE Rob. Autom. Lett. 3(1), 484–491 (2018).CrossRefGoogle Scholar
Poliero, T., Di Natali, C., Sposito, M., Ortiz, J., Graf, E., Pauli, C., Bottenberg, E., de Eyto, A. and Caldwell, D. G., “Soft Wearable Device for Lower Limb Assistance: Assessment of an Optimized Energy Efficient Actuation Prototype,” IEEE-RAS International Conference on Soft Robotics (RoboSoft), Livorno, Italy (IEEE, 2018) pp. 559–564.Google Scholar
Endo, K., Paluska, D. and Herr, H., “A Quasi-passive Model of Human Leg Function in Level-Ground Walking,” 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, Beijing, China (IEEE, 2006) pp. 4935–4939.CrossRefGoogle Scholar
Winter, D. A., Biomechanics and Motor Control of Human Gait: Normal, Elderly and Pathological (University of Waterloo Press, Ontario, Canada, 1991).Google Scholar
Mecheels, J. and Umbach, K. H., “The Psychrometric Range of Clothing Systems,” In: Clothing Comfort (Ann Arbor Science, Michigan, 1977) pp. 133–151.Google Scholar
Mateos, L. A., Ortiz, J., Toxiri, S., Fernández, J., Masood, J. and Caldwell, D. G., “Exoshoe: A Sensory System to Measure Foot Pressure in Industrial Exoskeleton,” 2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob), Singapore (IEEE, 2016), pp. 99–105.CrossRefGoogle Scholar
Söderkvist, I. and Wedin, P.-Å., “Determining the movements of the skeleton using well-configured markers,” J. Biomech. 26(12), 1473–1477 (1993).CrossRefGoogle ScholarPubMed
Grood, E. S. and Suntay, W. J., “A joint coordinate system for the clinical description of three-dimensional motions: Application to the knee,” J. Biomech. Eng. 105(2), 136–144 (1983).CrossRefGoogle ScholarPubMed
Totaro, M., Poliero, T., Mondini, A., Lucarotti, C., Cairoli, G., Ortiz, J. and Beccai, L., “Soft smart garments for lower limb joint position analysis,” Sensors 17(10), 2314 (2017).CrossRefGoogle ScholarPubMed
List, R., Gülay, T., Stoop, M. and Lorenzetti, S., “Kinematics of the trunk and the lower extremities during restricted and unrestricted squats,” J. Strength Conditioning Res. 27(6), 1529–1538 (2013).CrossRefGoogle ScholarPubMed
Wu, G., Siegler, S., Allard, P., Kirtley, C., Leardini, A., Rosenbaum, D., Whittle, M., D’Lima, D. D., Cristofolini, L., Witte, H. and Schmid, O., “ISB recommendation on definitions of joint coordinate system of various joints for the reporting of human joint motion–part I: Ankle, hip, and spine,” J. Biomechan. 35(4), 543–548 (2002).CrossRefGoogle ScholarPubMed
Wu, G. and Cavanagh, P. R., “ISB recommendations for standardization in the reporting of kinematic data,” J. Biomechan. 28(10), 1257–1261 (1995).CrossRefGoogle ScholarPubMed
Winter, D. A., Biomechanics and Motor Control of Human Movement (John Wiley & Sons, NJ, USA, 2009).CrossRefGoogle Scholar