Hostname: page-component-78c5997874-g7gxr Total loading time: 0 Render date: 2024-10-31T03:03:32.416Z Has data issue: false hasContentIssue false

Robotic Care: A Low Cost Design to Assist Therapy for Brain Stroke Rehabilitation

Published online by Cambridge University Press:  26 July 2019

Pablo Prieto*
Affiliation:
Universidad Técnica Federico Santa María. Engineering Design Department.;
Fernando Auat
Affiliation:
Universidad Técnica Federico Santa María. Department of Electronic;
Maria Escobar
Affiliation:
Universidad Técnica Federico Santa María. Department of Electronic;
Ronny Vallejos
Affiliation:
Universidad Técnica Federico Santa María. Department of Mathematics;
Paula Maldonado
Affiliation:
Peñablanca Hospital.
Cristobal Larrain
Affiliation:
Peñablanca Hospital.
Martin Serey
Affiliation:
Universidad Técnica Federico Santa María. Engineering Design Department.;
*
Contact: Prieto, Pablo, Universidad Técnica Federico Santa María, Engineering Design Department, Chile, pablo.prieto@usm.cl

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

A low cost robotic-assisted prototype for finger and hand rehabilitation of people affected by a stroke is presented. The system was developed by a team of undergraduate students led by a Design lecturer in collaboration with the Rehabilitation Unit of the Peñablanca Public Hospital in Chile.

The system consists of a flexion sensor equipped glove, a hand exoskeleton and an Arduino control unit. The patient wears the glove in his healthy hand. When s/he performs movements with the healthy hand, the sensors register the flexion of the fingers and send this information to the servo motors installed in an exoskeleton attached to the affected hand. In this way, the affected hand reproduces the movement of the healthy hand. The system uses a combination of the mirror therapy (the patient sees his/her affected hand moving in the same way that the healthy hand does) and passive exercising (as the exoskeleton produces the movement of the hand affected by the stroke). The combination of two types of therapy in a single low cost system makes the present work unique. In the near future, the developed prototype will be used to validate the effectiveness of the new proposed robotic therapy.

Type
Article
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
© The Author(s) 2019

References

Bouzit, M., Burdea, G., Popescu, G. and Boian, R. (2002), “The Rutgers Master II-new design force-feedback glove”, IEEE/ASME Transactions on Mechatronics, Vol. 7 No. 2, pp. 256263. http://doi.org/10.1109/TMECH.2002.1011262Google Scholar
Brokaw, E.B., Black, I., Holley, R.J. and Lum, P.S. (2011), “Hand Spring Operated Movement Enhancer (HandSOME): a portable, passive hand exoskeleton for stroke rehabilitation”, IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol. 19 No. 4, pp. 391399. http://doi.org/10.1109/TNSRE.2011.2157705Google Scholar
Carey, J.R., Durfee, W.K., Bhatt, E., Nagpal, A., Weinstein, S.A., Anderson, K.M. and Lewis, S.M. (2007), “Comparison of finger tracking versus simple movement training via telerehabilitation to alter hand function and cortical reorganization after stroke”, Neurorehabilitation and Neural Repair, Vol. 21 No. 3, pp. 216232. https://doi.org/10.1177/1545968306292381Google Scholar
Duschau-Wicke, A., Caprez, A. and Riener, R. (2010), “Patient-cooperative control increases active participation of individuals with SCI during robot-aided gait training”, Journal Of Neuroengineering and Rehabilitation, Vol. 7 No. 1, p. 43. https://doi.org/10.1186/1743-0003-7-43Google Scholar
Fanin, C., Gallina, P., Rossi, A., Zanatta, U. and Masiero, S. (2003), “Nerebot: a wire-based robot for neurorehabilitation”, 8th International Conference on Rehabilitation Robotics ICORR03, Daejeon, Republic of Korea, New York (NY), IEEE, pp. 2326.Google Scholar
Feigin, V., Norrving, B. and Mensah, G.A. (2017), “Global burden stroke”, Circulation Research, Vol. 120, No. 3, pp. 439448. http://doi.org/10.1161/CIRCRESAHA.116.308413Google Scholar
Fischer, H.C., Stubblefield, K., Kline, T., Luo, X., Kenyon, R.V. and Kamper, D.G. (2007), “Hand rehabilitation following stroke: a pilot study of assisted finger extension training in a virtual environment”, Topics in Stroke Rehabilitation, Vol. 14 No. 1, pp. 112. https://doi.org/10.1310/tsr1401-1Google Scholar
Folgheraiter, M., Gini, G.C. and Vercesi, D.L. (2005), “A glove interface with tactile feeling display for humanoid robotics and virtual reality systems”, International Conference on Informatics in Control, Automation and Robotics ICINCO, Barcelona, September 14-17 2005, pp. 353360.Google Scholar
Goic, A. (2015), “The Chilean Health Care System: The task ahead”, Revista Médica de Chile, Vol. 143 No. 6, http://doi.org/10.4067/S0034-98872015000600011Google Scholar
Hesse, S., Schulte-Tigges, G., Konrad, M., Bardeleben, A. and Werner, C. (2003), “Robot-assisted arm trainer for the passive and active practice of bilateral forearm and wrist movements in hemiparetic subjects”, Archives of Physical Medicine and Rehabilitation, Vol. 84 No. 6, pp. 915920. http://doi.org/10.1016/S0003-9993(02)04954-7Google Scholar
Hidler, J., Nichols, D., Pelliccio, M. and Brady, K. (2005), “Advances in the understanding and treatment of stroke impairment using robotic devices”, Topics in Stroke Rehabilitation, Vol. 12 No. 2, pp. 2235. https://doi.org/10.1310/RYT5-62N4-CTVX-8JTEGoogle Scholar
Iqbal, J. and Baizid, K.(2015), “Stroke rehabilitation using exoskeleton-based robotic exercisers: Mini Review”, Biomedical Research. Vol. 26 No. 1, pp. 197201.Google Scholar
Iqbal, J., Tsagarakis, N.G. and Caldwell, D.G. (2011), “Design of a wearable direct-driven optimized hand exoskeleton device” 4th International Conference on Advances in Computer-Human Interactions (ACHI), Gosier, France, pp. 142146.Google Scholar
JACE Systems, “JACE H440 hand CPM”. Available at http://www.jace-systems.de/produkte/finger.html. Last accessed 16 December 2018Google Scholar
Kamper, D.G., Harvey, R.L., Suresh, S. and Rymer, W.Z. (2003), “Relative contributions of neural mechanisms versus muscle mechanics in promoting finger extension deficits following stroke”, Muscle & Nerve: Official Journal of the American Association of Electrodiagnostic Medicine, Vol. 28 No. 3, pp. 309318. https://doi.org/10.1002/mus.10443Google Scholar
Kwakkel, G., Kollen, B.J. and Krebs, H.I. (2008), “Effects of robot-assisted therapy on upper limb recovery after stroke: a systematic review”, Neurorehabilitation and Neural Repair, Vol. 22 No. 2, pp. 111121. https://doi.org/10.1177/1545968307305457Google Scholar
Kwakkel, G., Kollen, B.J., van der Grond, J. and Prevo, A.J. (2003), “Probability of regaining dexterity in the flaccid upper limb: impact of severity of paresis and time since onset in acute stroke”, Stroke, Vol. 34 No. 9, pp. 21812186. https://doi.org/10.1161/01.STR.0000087172.16305.CDGoogle Scholar
Lambercy, O., Dovat, L., Gassert, R., Burdet, E., Teo, C.L. and Milner, T. (2007), “A haptic knob for rehabilitation of hand function”, IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol. 15 No. 3, pp. 356366. http://doi.org/10.1109/TNSRE.2007.903913Google Scholar
Langhorne, P., Bernhardt, J. and Kwakkel, G. (2011), “Stroke rehabilitation”, The Lancet, Vol. 377 No. 9778, pp. 16931702. http://doi.org/10.1016/S0140-6736(11)60325-5Google Scholar
Lelieveld, M.J., Maeno, T. and Tomiyama, T. (2006), “Design and development of two concepts for a 4 DOF portable haptic interface with active and passive multi-point force feedback for the index finger”, ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, American Society of Mechanical Engineers, Philadelphia, USA, pp. 547556. http://doi.org/10.1115/DETC2006-99111Google Scholar
Loureiro, R.C., Harwin, W.S., Nagai, K. and Johnson, M. (2011), “Advances in upper limb stroke rehabilitation: a technology push”, Medical & biological engineering & computing, Vol. 49 No. 10, p. 1103. http://doi.org/10.1007/s11517-011-0797-0Google Scholar
Lum, P.S., Burgar, C.G., Shor, P.C., Majmundar, M. and Van der Loos, M. (2002), “Robot-assisted movement training compared with conventional therapy techniques for the rehabilitation of upper-limb motor function after stroke”, Archives of Physical Medicine and Rehabilitation, Vol. 83 No. 7, pp. 952959. https://doi.org/10.1053/apmr.2001.33101Google Scholar
Minsal, Ministerio de Salud (2014), “Plan de acción ataque cerebro vascular”, Subsecretaría de Salud Pública, División de Control y Prevención de Enfermedades, Departamento de Enfermedades No Transmisibles 2nd Ed.Google Scholar
Motorika, (07 of April 2019),”Advanced upper limb therapy system ReoGo TM”. Available at: http://motorika.com/reogo/Google Scholar
Moyano, Á. (2010), “El accidente cerebrovascular desde la mirada del rehabilitador”, Revista Hospital Clínico Universidad de Chile, Vol. 21, pp. 348355.Google Scholar
Nef, T., Guidali, M., Klamroth-Marganska, V. and Riener, R., 2009. “ARMin-exoskeleton robot for stroke rehabilitation”. In World Congress on Medical Physics and Biomedical Engineering, September 7-12, 2009, Munich, Germany, pp. 127130, Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03889-1_35Google Scholar
Norouzi-Gheidari, N., Archambault, P.S. and Fung, J. (2012). “Effects of robot-assisted therapy on stroke rehabilitation in upper limbs: systematic review and meta-analysis of the literature”. Journal of Rehabilitation Research & Development, Vol. 49 No. 4. http://doi.org/10.1682/JRRD.2010.10.0210Google Scholar
Ochoa, J.M., Narasimhan, Y.J.D. and Kamper, D.G. (September 2009), “Development of a portable actuated orthotic glove to facilitate gross extension of the digits for therapeutic training after stroke”. In Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE, pp. 69186921. http://doi.org/10.1109/IEMBS.2009.5333630Google Scholar
Paik, Y.R., Kim, S.K., Lee, J.S. and Jeon, B.J. (2014), “Simple and task-oriented mirror therapy for upper extremity function in stroke patients: a pilot study”, Hong Kong Journal of Occupational Therapy, Vol. 24 No. 1, pp. 612. https://doi.org/10.1016/j.hkjot.2014.01.002Google Scholar
Pomeroy, V., Aglioti, S.M., Mark, V.W., McFarland, D., Stinear, C., Wolf, S.L., Corbetta, M. and Fitzpatrick, S.M. (2011), “Neurological principles and rehabilitation of action disorders: rehabilitation interventions”, Neurorehabilitation and Neural Repair, Vol. 25 No. 5 suppl, pp. 33S43S. https://doi.org/10.1177/1545968311410942Google Scholar
Prange, G.B., Jannink, M.J., Groothuis-Oudshoorn, C.G., Hermens, H.J. and IJzerman, M.J. (2006), “Systematic review of the effect of robot-aided therapy on recovery of the hemiparetic arm after stroke”, Journal of Rehabilitation Research & Development, Vol. 43 No. 2, pp. 171184. http://doi.org/10.1682/JRRD.2005.04.0076Google Scholar
Rothgangel, A.S., Braun, S.M., Beurskens, A.J., Seitz, R.J. and Wade, D.T. (2011), “The clinical aspects of mirror therapy in rehabilitation: a systematic review of the literature”, International Journal of Rehabilitation Research, Vol. 34 No. 1, pp. 113. http://doi.org/10.1097/MRR.0b013e3283441e98Google Scholar
Sarakoglou, I., Tsagarakis, N.G. and Caldwell, D.G. (September 2004), “Occupational and physical therapy using a hand exoskeleton based exerciser”. In Intelligent Robots and Systems, Proceedings. 2004 IEEE/RSJ International Conference on Vol. 3, pp. 29732978. http://doi.org/10.1109/IROS.2004.1389861Google Scholar
Susanto, E.A., Tong, R.K., Ockenfeld, C. and Ho, N.S. (2015), “Efficacy of robot-assisted fingers training in chronic stroke survivors: a pilot randomized-controlled trialJournal of Neuroengineering and Rehabilitation, Vol. 12 No. 1, p. 42. https://doi.org/10.1186/s12984-015-0033-5Google Scholar
Taheri, H., Rowe, J.B., Gardner, D., Chan, V., Gray, K., Bower, C., Reinkensmeyer, D.J. and Wolbrecht, E.T. (2014), “Design and preliminary evaluation of the FINGER rehabilitation robot: controlling challenge and quantifying finger individuation during musical computer game play”, Journal of Neuroengineering and Rehabilitation, Vol. 11 No. 1, p. 10. https://doi.org/10.1186/1743-0003-11-10Google Scholar
Tzafestas, C.S. (2003). “Whole-hand kinesthetic feedback and haptic perception in dextrous virtual manipulation”. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, Vol. 33 No. 1, pp. 100113. https://doi.org/10.1109/TSMCA.2003.812600Google Scholar
Wang, J., Li, J., Zhang, Y. and Wang, S. (September 2009), “Design of an exoskeleton for index finger rehabilitation”. In Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE, pp. 59575960. IEEE. http://doi.org/10.1109/IEMBS.2009.5334779Google Scholar
Wege, A. and Hommel, G. (August 2005). “Development and control of a hand exoskeleton for rehabilitation of hand injuries”. In Intelligent Robots and Systems, 2005 IEEE/RSJ International Conference on pp. 30463051. http://doi.org/10.1109/IROS.2005.1545506Google Scholar