Design of active orthoses for a robotic gait rehabilitation system

doi:10.1007/s11465-015-0350-1

Front. Mech. Eng.

2015, Vol. 10

Issue (3) : 242-254 https://doi.org/10.1007/s11465-015-0350-1

REVIEW ARTICLE

Design of active orthoses for a robotic gait rehabilitation system

A. C. VILLA-PARRA^1,^2,^*(

),L. BROCHE³,D. DELISLE-RODRÍGUEZ^1,⁴,R. SAGARÓ³,T. BASTOS¹,A. FRIZERA-NETO¹

1. Post-Graduate Program in Electrical Engineering, Universidade Federal do Espírito Santo, Vitória 29075-910, Brazil
2. Grupo de Investigación en Ingeniería Biomédica GIIB, Universidad Politécnica Salesiana, Cuenca 010105, Ecuador
3. Mechanical and Design Engineering Department, Universidad de Oriente, Santiago de Cuba 90500, Cuba
4. Center of Medical Biophysics, Universidad de Oriente, Santiago de Cuba 90500, Cuba

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Abstract

An active orthosis (AO) is a robotic device that assists both human gait and rehabilitation therapy. This work proposes portable AOs, one for the knee joint and another for the ankle joint. Both AOs will be used to complete a robotic system that improves gait rehabilitation. The requirements for actuator selection, the biomechanical considerations during the AO design, the finite element method, and a control approach based on electroencephalographic and surface electromyographic signals are reviewed. This work contributes to the design of AOs for users with foot drop and knee flexion impairment. However, the potential of the proposed AOs to be part of a robotic gait rehabilitation system that improves the quality of life of stroke survivors requires further investigation.

Keywords active orthosis gait rehabilitation electroencephalography surface electromyography

Corresponding Author(s): A. C. VILLA-PARRA

Online First Date: 08 September 2015 Issue Date: 23 September 2015

Cite this article:

A. C. VILLA-PARRA,L. BROCHE,D. DELISLE-RODRÍGUEZ, et al. Design of active orthoses for a robotic gait rehabilitation system[J]. Front. Mech. Eng., 2015, 10(3): 242-254.

URL:

https://academic.hep.com.cn/fme/EN/10.1007/s11465-015-0350-1
https://academic.hep.com.cn/fme/EN/Y2015/V10/I3/242

Fig.1 Robotic system developed in Universidade Federal do Espírito Santo (Brazil) to assist gait rehabilitation

Tab.1 Design criteria for active orthoses

Fig.2 Forces at the joints, knee, and ankle

Fig.3 Representation of knee and ankle values during walking. (a) Joint angle and torque; (b) knee angle versus torque [15]

Fig.4 Block diagram of the acquisition wireless module. (a) EEG; (b) sEMG

Fig.5 (a) FSR locations; (b) gait-phase pattern recognized by the insole

Fig.6 Block diagram of the control approach

Fig.7 (a) Structure of CAD modeling; (b) stress distribution in the structure; (c) distribution of safety factor

Fig.8 (a) Plaster cast of a right leg to develop the positive (solid) mold; (b) the ankle foot orthosis in polypropylene plastic; (c) 1—Power supply and electric circuit; 2—Shank segment, which can be adjusted to different diameters; 3—Powered joint; 4—Potentiometer; 5—Foot segment and sensor insole; (d) AAFO modeling; (e) AAFO work positions

Fig.9 (a) Foot structure mesh; (b) stress distribution in the structure; (c) distribution of safety factor; (d) foot structure with a heel-off load

Tab.2 Active orthoses specifications

Tab.3 Concordance correlation coefficient of the frequency response tests intra-observer

Fig.10 Frequency response. (a) EEG channel; (b) sEMG channel

Fig.11 (a) EEG signal from the occipital lobe (alpha band); (b) sEMG signal from the tibial anterior muscle

Fig.12 Representation of the power spectra on the occipital lobe. (a) Power spectrum for visual stimulus of 6.4 Hz; (b) power spectrum for visual stimuli of 8.0 Hz

Fig.13 Representation of the ERD and ERS. (a) C3-FZ electrodes; (b) C4-FZ electrodes

Fig.14 Synchronized measurements. (a) Gait-phase acquisition; (b) knee trajectory; (c) rectus femoris sEMG; (d) gastrocnemius sEMG

1	Belda-Lois J M, Mena-del Horno S, Bermejo-Bosch I, Rehabilitation of gait after stroke: A review towards a top-down approach. Journal of Neuroengineering and Rehabilitation, 2011, 8(1): 66 https://doi.org/10.1186/1743-0003-8-66 pmid: 22165907
2	Shorter K A, Xia J, Hsiao-Wecksler E T, Technologies for powered ankle-foot orthotic systems: Possibilities and challenges. IEEE/ASME Transactions on Mechatronics, 2013, 18(1): 337–347 https://doi.org/10.1109/TMECH.2011.2174799
3	Viteckova S, Kutilek P, Jirina M. Wearable lower limb robotics: A review. Biocybernetics and Biomedical Engineering, 2013, 33(2): 96–105 https://doi.org/10.1016/j.bbe.2013.03.005
4	Prange G B, Jannink M J A, Groothuis-Oudshoorn C G M, Systematic review of the effect of robot-aided therapy on recovery of the hemiparetic arm after stroke. Journal of Rehabilitation Research and Development, 2006, 43(2): 171–184 https://doi.org/10.1682/JRRD.2005.04.0076 pmid: 16847784
5	Pons J L, Moreno J C, Brunetti F J, Lower-limb wearable exoskeleton. In: Kommu S S, ed. Rehabilitation Robotics. Vienna: Itech Education and Publishing, 2007, 1: 648
6	Valadao C, Lotério F, Cardoso V, Robotic walker to assist and monitor physiotherapy sessions. In: Proceedings of the 1st International Workshop on Assistive Technologies. Vitória, 2015
7	Tausel L, Cifuentes C A, Rodriguez C, Human-walker interaction on slopes based on LRF and IMU sensors. In: Biomedical Robotics and Biomechatronics (2014 5th IEEE RAS EMBS International Conference). Sao Paulo: IEEE, 2014, 227–232
8	Hussain S, Xie S Q, Liu G. Robot assisted treadmill training: Mechanisms and training strategies. Medical Engineering & Physics, 2011, 33(5): 527–533 https://doi.org/10.1016/j.medengphy.2010.12.010 pmid: 21216650
9	Low K H, Yin Y. An integrated lower exoskeleton system towards design of a portable active orthotic device. International Journal of Robotics and Automation, 2007, 22(1): 32–43 https://doi.org/10.2316/Journal.206.2007.1.206-1003
10	Hussain S, Xie S Q, Jamwal P K. Adaptive impedance control of a robotic orthosis for gait rehabilitation. IEEE Transactions on Cybernetics, 2013, 43(3): 1025–1034 https://doi.org/10.1109/TSMCB.2012.2222374 pmid: 23193241
11	Bortole M, Venkatakrishnan A, Zhu F, The H2 robotic exoskeleton for gait rehabilitation after stroke: Early findings from a clinical study. Journal of Neuroengineering and Rehabilitation, 2015, 12(1): 54 https://doi.org/10.1186/s12984-015-0048-y pmid: 26076696
12	Yoshizawa N. Active AFO with ankle joint brake friction control using force observer. In: Proceedings of Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE. San Diego: IEEE, 2012, 1900–1903 https://doi.org/10.1109/EMBC.2012.6346324 pmid: 23366285
13	Onen U, Botsali F M, Kalyoncu M, Design and actuator selection of a lower extremity exoskeleton. IEEE/ASME Transactions on Mechatronics, 2013, 1: 1–10
14	Winter D A. Biomechanics and Motor Control of Human Movement. 2nd ed. Hoboken: John Wiley & Sons, 2009
15	Pons J L. Wearable Robots: Biomechatronic Exoskeletons. Hoboken: John Wiley & Sons, 2008
16	Madeti B K, Chalamalasetti S R, siva rao Bolla Pragada S K S. Biomechanics of knee joint—A review. Frontiers of Mechanical Engineering, 2015, 10(2): 1–10 https://doi.org/10.1007/s11465-014-0306-x
17	McGibbon C A, Krebs D E. Discriminating age and disability effects in locomotion: Neuromuscular adaptations in musculoskeletal pathology. Journal of Applied Physiology, 2004, 96(1): 149–160 https://doi.org/10.1152/japplphysiol.00422.2003 pmid: 12949019
18	Lobo-Prat J, Kooren P N, Stienen A H, Non-invasive control interfaces for intention detection in active movement-assistive devices. Journal of Neuroengineering and Rehabilitation, 2014, 11(1): 168 https://doi.org/10.1186/1743-0003-11-168 pmid: 25516421
19	Chaffin B, Gunnar B, Andersson J, Occupational biomechanics, 4th edition. Professional Safety, 2006, 51(8): 58
20	Kelly B M, Spires M C, Restrepo J A. Orthotic and prosthetic prescriptions for today and tomorrow. Physical Medicine and Rehabilitation Clinics of North America, 2007, 18(4): 785–858 https://doi.org/10.1016/j.pmr.2007.08.001 pmid: 17967365
21	Mills P M, Barrett R S. Swing phase mechanics of healthy young and elderly men. Human Movement Science, 2001, 20(4–5): 427–446 https://doi.org/10.1016/S0167-9457(01)00061-6 pmid: 11750671
22	Pfurtscheller G, Lopes da Silva F H. Event-related EEG/MEG synchronization and desynchronization: Basic principles. Clinical Neurophysiology: Official Journal of the International Federation of Clinical Neurophysiology, 1999, 110(11): 1842–1857 https://doi.org/10.1016/S1388-2457(99)00141-8 pmid: 10576479
23	Merletti R, Parker P. Electromyography: Physiology, Engineering, and Noninvasive Applications. Hoboken: John Wiley & Sons, 2004
24	Wafai L, Zayegh A, Begg R, Asymmetry detection during pathological gait using a plantar pressure sensing system. In: Proceedings of 2013 7th IEEE GCC Conference and Exhibition (GCC). Doha: IEEE, 2013, 182–187
25	Lin L I. A concordance correlation coefficient to evaluate reproducibility. Biometrics, 1989, 45(1): 255–268 https://doi.org/10.2307/2532051 pmid: 2720055
26	Vijay M. The Digital Signal Processing Handbook. Boca Raton: CRC Press, 2009
27	Lalitharatne T D, Teramoto K, Hayashi Y, Towards hybrid EEG-EMG-based control approaches to be used in bio-robotics applications: Current status, challenges and future directions. Paladyn Journal of Behavioral Robotics, 2013, 4: 147–154
28	Nymark J R, Balmer S J, Melis E H, Electromyographic and kinematic nondisabled gait differences at extremely slow overground and treadmill walking speeds. Journal of Rehabilitation Research and Development, 2005, 42(4): 523–534 https://doi.org/10.1682/JRRD.2004.05.0059 pmid: 16320147
29	Ishikura T. Biomechanical analysis of weight bearing force and muscle activation levels in the lower extremities during gait with a walker. Acta Medica Okayama, 2001, 55(2): 73–82 pmid: 11332202
30	Martins M, Elias A, Cifuentes C, Assessment of walker-assisted gait based on principal component analysis and wireless inertial sensors. Revista Brasileira de Engenharia Biomédica, 2014, 30(3): 220–231 https://doi.org/10.1590/rbeb.2014.020
31	Browning R C, Kram R. Effects of obesity on the biomechanics of walking at different speeds. Medicine and Science in Sports and Exercise, 2007, 39(9): 1632–1641 https://doi.org/10.1249/mss.0b013e318076b54b pmid: 17805097
32	Chironis N P, Sclater N. Mechanisms and Mechanical Devices Sourcebook. 3rd ed. New York: McGraw-Hill, 2001
33	Veneman J F. A series elastic- and Bowden-cable-based actuation system for use as torque actuator in exoskeleton-type robots. International Journal of Robotics Research, 2006, 25(3): 261–281 https://doi.org/10.1177/0278364906063829
34	Karavas N C, Tsagarakis N G, Caldwell D G. Design, modeling and control of a series elastic actuator for an assistive knee exoskeleton. In: Proceedings of 2012 4th IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob). Sao Paulo: IEEE, 2012, 1813–1819
35	Veneva I. Intelligent device for control of active ankle-foot orthosis. Biomedical Engineering, 2010, 7: 100–105 https://doi.org/10.2316/Journal.216.2010.7.680-080
36	Cheung J T M, Zhang M. Parametric design of pressure-relieving foot orthosis using statistics-based finite element method. Medical Engineering & Physics, 2008, 30(3): 269–277 https://doi.org/10.1016/j.medengphy.2007.05.002 pmid: 17584519
37	Chin R, Hsiao-Wecksler E T, Loth E, A pneumatic power harvesting ankle-foot orthosis to prevent foot-drop. Journal of Neuroengineering and Rehabilitation, 2009, 6(19): 1–11 https://doi.org/10.1186/1743-0003-6-19

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