The rehabilitation of patients should not only be limited to the first phases during intense hospital care but also support and therapy should be guaranteed in later stages, especially during daily life activities if the patient’s state requires this. However, aid should only be given to the patient if needed and as much as it is required. To allow this, automatic self-initiated movement support and patient-cooperative control strategies have to be developed and integrated into assistive systems. In this work, we first give an overview of different kinds of neuromuscular diseases, review different forms of therapy, and explain possible fields of rehabilitation and benefits of robotic aided rehabilitation. Next, the mechanical design and control scheme of an upper limb orthosis for rehabilitation are presented. Two control models for the orthosis are explained which compute the triggering function and the level of assistance provided by the device. As input to the model fused sensor data from the orthosis and physiology data in terms of electromyography (EMG) signals are used. 1. Introduction The requirements on a social, well-functioning, and modern health care system—including elderly care—are demanding: it must be flexible enough to encounter the increasing process of change and the related challenges. These changes and challenges are triggered, among other things, by the demographic changes, the increase in chronic diseases, the rising costs, and the impending skills shortage [1]. To assure the achievement of these objectives in medical care, the publicly financed science plays a major role. In this context, robotics research is an important element which is increasingly gaining significance [2]. Nowadays, robotic systems are used in various medical disciplines and different highly specialized applications, for example, in the field of minimally invasive surgery [3]. Furthermore, technical therapy approaches in physiotherapy and occupational therapy are given more and more importance. In this context, particular assistance and training devices are in the center of interest. These could be systems like powered exoskeletons, active orthoses, or special end-effector-based therapy robots [4]. On the one hand, these systems could provide important support in medical rehabilitation for the therapist and patient and, on the other hand, they could be a help in everyday activities for the elderly or motor-impaired people in their home environment [5]. Due to the aging society and probably significant increase in chronic diseases of the musculoskeletal and the
References
[1]
C. Fuchs, “Demografischer wandel und notwendigkeit der priorisierung im gesundheitswesen. Positionsbestimmung der ？rzteschaft,” Bundesgesundheitsbl Gesundheitsforsch Gesundheitsschutz, vol. 83, pp. 435–440, 2010.
[2]
H. I. Krebs, J. J. Palazzolo, L. Dipietro et al., “Rehabilitation robotics: performance-based progressive robot-assisted therapy,” Autonomous Robots, vol. 15, no. 1, pp. 7–20, 2003.
[3]
M. J. H. Lum, D. Trimble, J. Rosen et al., “Multidisciplinary approach for developing a new minimally invasive surgical robotic system,” in Proceedings of the 1st IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob '06), pp. 841–846, Tuscany, Italy, February 2006.
[4]
S. Hesse, H. Schmidt, C. Werner, and A. Bardeleben, “Upper and lower extremity robotic devices for rehabilitation and for studying motor control,” Current Opinion in Neurology, vol. 16, no. 6, pp. 705–710, 2003.
[5]
R. C. V. Loureiro, W. S. Harwin, K. Nagai, and M. Johnson, “Advanahces in upper limb stroke rehabilitation: a technology push,” Medical & Biological Engineering & Computing, vol. 49, no. 10, pp. 1103–1118, 2011.
[6]
H. Masur, “Sinnvoller einsatz von robotern in der neurorehabilitation—fiktion oder realit？t?” Deutsches ？rzteblatt, vol. 105, no. 18, p. 329, 2008.
[7]
T. Henze, “Moderne rehabilitation nach schlaganfall,” NeuroTransmitter, no. 10, pp. 59–67, 2007.
[8]
E. A. Kirchner, J. C. Albiez, A. Seeland, M. Jordan, and F. Kirchner, “Towards assistive robotics for home rehabilitation,” in Proceedings of the 6th International Conference on Biomedical Electronics and Devices (BIODEVICES '13), pp. 168–177, SciTePress, Barcelona, Spain, 2013.
[9]
L. M. V. Benitez, N. Will, M. Tabie, S. Schmidt, E. Kirchner, and J. Albiez, “An EMG-based assistive orthosis for upper limb rehabilitation,” in Proceedings of the International Conference on Biomedical Electronics and Devices (BIODEVICES '13), pp. 323–328, SciTePress, Barcelona, Spain, February 2013.
[10]
C. Deaton, E. S. Froelicher, L. H. Wu, C. Ho, K. Shishani, and T. Jaarsma, “The global burden of cardiovascular disease,” European Journal of Cardiovascular Nursing, vol. 10, supplement 2, pp. S5–S13, 2011.
[11]
S. J. Albert and J. Kesselring, “Neurorehabilitation of stroke,” Journal of Neurology, vol. 259, no. 5, pp. 817–832, 2012.
[12]
J. H. Cauraugh and J. J. Summers, “Neural plasticity and bilateral movements: a rehabilitation approach for chronic stroke,” Progress in Neurobiology, vol. 75, no. 5, pp. 309–320, 2005.
[13]
S. Hesse, C. Werner, and J. Brocke, “Use of machines and robots in neuro rehabilitation expectations of the clinics,” Orthop？die-Technik, vol. 2, pp. 74–77, 2009.
[14]
P. Frommelt and H. L？sslein, Neuro Rehabilitation, Springer, Berlin, Germany, 2010.
[15]
H. C. Diener, W. Hacke, and M. Forsting, Eds., Schlaganfall, Georg Thieme, Berlin, Germany, 2004.
[16]
K. Müller, C. M. Bütefisch, R. J. Seitz, and V. H？mberg, “Mental practice improves hand function after hemiparetic stroke,” Restorative Neurology and Neuroscience, vol. 25, no. 5-6, pp. 501–511, 2007.
[17]
J. H. Morris, F. van Wijck, S. Joice, S. A. Ogston, I. Cole, and R. S. MacWalter, “Bilaterales oder unilaterales training der oberen extremit？t nach schlaganfall? Eine randomisierte kontrollierte studie,” Physioscience, vol. 4, no. 4, pp. 194–195, 2008.
[18]
C. J. Winstein, D. K. Rose, S. M. Tan, R. Lewthwaite, H. C. Chui, and S. P. Azen, “A randomized controlled comparison of upper-extremity rehabilitation strategies in acute stroke: a pilot study of immediate and long-term outcomes,” Archives of Physical Medicine and Rehabilitation, vol. 85, no. 4, pp. 620–628, 2004.
[19]
C. Dohle, J. Püllen, A. Nakaten, J. Küst, C. Rietz, and H. Karbe, “Mirror therapy promotes recovery from severe hemiparesis: a randomized controlled trial,” Neurorehabilitation and Neural Repair, vol. 23, no. 3, pp. 209–217, 2009.
[20]
B. R. Brewer, S. K. McDowell, and L. C. Worthen-Chaudhari, “Poststroke upper extremity rehabilitation: a review of robotic systems and clinical results,” Topics in Stroke Rehabilitation, vol. 14, no. 6, pp. 22–44, 2007.
[21]
L. Pignolo, “Robotics in neuro-rehabilitation,” Journal of Rehabilitation Medicine, vol. 41, no. 12, pp. 955–960, 2009.
[22]
G. B. Prange, M. J. A. Jannink, C. G. M. Groothuis-Oudshoorn, H. J. Hermens, and M. J. Ijzerman, “Systematic review of the effect of robot-aided therapy on recovery of the hemiparetic arm after stroke,” Journal of Rehabilitation Research and Development, vol. 43, no. 2, pp. 171–184, 2006.
[23]
S. Hesse, J. Mehrholz, and C. Werner, “Roboter—und ger？tegestützte rehabilitation nach schlaganfall,” Deutsches ？rzteblatt, vol. 105, no. 18, pp. 330–336, 2008.
[24]
S. J. Housman, K. M. Scott, and D. J. Reinkensmeyer, “A randomized controlled trial of gravity-supported, computer-enhanced arm exercise for individuals with severe hemiparesis,” Neurorehabilitation and Neural Repair, vol. 23, no. 5, pp. 505–514, 2009.
[25]
T. Nef, G. Colombo, and R. Riener, “ARMin—robot for movement therapy of the upper extremities,” Automatisierungstechnik, vol. 53, no. 12, pp. 597–606, 2005.
[26]
N. Hogan, H. I. Krebs, J. Charnnarong, P. Srikrishna, and A. Sharon, “MIT-MANUS: a workstation for manual therapy and training. I,” in Proceedings of the IEEE International Workshop on Robot and Human Communication (ROMAN '92), pp. 161–165, Tokyo, Jaban, September 1992.
[27]
P. S. Lum, M. Van der Loos, P. Shor, and C. G. Burgar, “A robotic system for upper-limb exercises to promote recovery of motor function following stroke,” in Proceedings of the International Conference on Rehabilitation Robotics (ICORR '99), Stanford University, 1999.
[28]
A. Mayr, M. Kofler, and L. Saltuari, “ARMOR: an electromechanical robot for upper limb training following stroke. A prospective randomised controlled pilot study,” Handchirurgie Mikrochirurgie Plastische Chirurgie, vol. 40, no. 1, pp. 66–73, 2008.
[29]
G. Kwakkel, B. J. Kollen, and H. I. Krebs, “Effects of robot-assisted therapy on upper limb recovery after stroke: a systematic review,” Neurorehabilitation and Neural Repair, vol. 22, no. 2, pp. 111–121, 2008.
[30]
T. Nef, M. Mihelj, G. Kiefer, C. Perndl, R. Müller , and R. Riener, “ARMin—exoskeleton for arm therapy in stroke patients,” in Proceedings of the IEEE 10th International Conference on Rehabilitation Robotics (ICORR '07), pp. 68–74, Noordwijk, Netherlands, June 2007.
[31]
S. J. Housman, V. Le, T. Rahman, R. J. Sanchez Jr., and D. J. Remkensrneyer, “Arm-training with T-WREX after chronic stroke: preliminary results of a randomized controlled trial,” in Proceedings of the IEEE 10th International Conference on Rehabilitation Robotics (ICORR '07), pp. 562–568, Noordwijk, Netherlands, June 2007.
[32]
G. B. Prange, M. J. A. Jannink, A. H. A. Stienen, H. Van Der Kooij, M. J. Ijzerman, and H. J. Hermens, “Influence of gravity compensation on muscle activation patterns during different temporal phases of arm movements of stroke patients,” Neurorehabilitation and Neural Repair, vol. 23, no. 5, pp. 478–485, 2009.
[33]
H. I. Krebs, B. T. Volpe, D. Williams et al., “Robot-aided neurorehabilitation: a robot for wrist rehabilitation,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 15, no. 3, pp. 327–335, 2007.
[34]
J. Stein, K. Narendran, J. McBean, K. Krebs, and R. Hughes, “Electromyography-controlled exoskeletal upper-limb-powered orthosis for exercise training after stroke,” American Journal of Physical Medicine and Rehabilitation, vol. 86, no. 4, pp. 255–261, 2007.
[35]
L. Marchal-Crespo and D. J. Reinkensmeyer, “Review of control strategies for robotic movement training after neurologic injury,” Journal of NeuroEngineering and Rehabilitation, vol. 6, no. 20, 2009.
[36]
A. Jackson, R. Culmer, S. Makower et al., “Initial patient testing of iPAM—a robotic system for Stroke rehabilitation,” in Proceedings of the IEEE 10th International Conference on Rehabilitation Robotics (ICORR '07), pp. 250–256, Noordwijk, Netherlands, June 2007.
[37]
T. Rahman, W. Sample, R. Seliktar et al., “Design and testing of a functional arm orthosis in patients with neuromuscular diseases,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 15, no. 2, pp. 244–251, 2007.
[38]
B. Schmitz, R. Wiegand, Ch. Pylatiuk, R. Rupp, and St. Schulz, “Erste erfahrungen mit dem orthojacket,” Orthop？die-Technik, vol. 4, no. 11, pp. 256–261, 2011.
[39]
E. Rocon, J. M. Belda-Lois, A. F. Ruiz, M. Manto, J. C. Moreno, and J. L. Pons, “Design and validation of a rehabilitation robotic exoskeleton for tremor assessment and suppression,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 15, no. 3, pp. 367–378, 2007.
[40]
M. DiCicco, L. Lucas, and Y. Matsuoka, “Comparison of control strategies for an EMG controlled orthotic exoskeleton for the hand,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA '04), pp. 1622–1627, New Orleans, La, USA, May 2004.
[41]
J. Rosen and J. C. Perry, “Upper limb powered exoskeleton,” International Journal of Humanoid Robotics, vol. 4, no. 3, pp. 529–548, 2007.
[42]
E. E. Cavallaro, J. Rosen, J. C. Perry, and S. Burns, “Real-time myoprocessors for a neural controlled powered exoskeleton arm,” IEEE Transactions on Biomedical Engineering, vol. 53, no. 11, pp. 2387–2396, 2006.
[43]
F. Le, I. Markovsky, C. Freeman, and E. Rogers, “Online identification of electrically stimulated muscle models,” in Proceedings of the American Control Conference (ACC '11), pp. 90–95, San Francisco, Calif, USA, July 2011.
[44]
M. Folgheraiter, E. A. Kirchner, A. Seeland et al., “A multimodal brain-arm interface for operation of complex robotic systems and upper limb motor recovery,” in Proceedings of the International Conference on Biomedical Electronics and Devices (BIODEVICES '11), pp. 150–162, Rome, Italy, January 2011.
[45]
D. Tsetserukou, K. Sato, and S. Tachi, “ExoInterfaces: novel exosceleton haptic interfaces for virtual reality, augmented sport and rehabilitation,” in Proceedings of the 1st Augmented Human International Conference (AH '10), H. Saito, J.-M. Seigneur, G. Moreau, and P. Mistry, Eds., April 2010.
[46]
J. Rosen, M. Brand, M. B. Fuchs, and M. Arcan, “A myosignal-based powered exoskeleton system,” IEEE Transactions on Systems, Man, and Cybernetics Part A, vol. 31, no. 3, pp. 210–222, 2001.
[47]
D. S. Andreasen, S. K. Allen, and D. A. Backus, “Exoskeleton with EMG based active assistance for rehabilitation,” in Proceedings of the IEEE 9th International Conference on Rehabilitation Robotics (ICORR '05), pp. 333–336, July 2005.
[48]
D. W. Robinson, Design and analysis of series elasticity in closed-loop actuator force control [Ph.D. thesis], Massachusetts Institute of Technology (MIT), Cambridge, Mass, USA, 2000.
[49]
M. Tabie and E. A. Kirchner, “EMG onset detection—comparison of different methods for a movement prediction task based on EMG,” in Proceedings of the 6th International Conference on Bio-inspired Systems and Signal Processing (BIOSIGNALS '13), I. S. Alvarez, J. Solé-Casals, A. Fred, and H. Gamboa, Eds., pp. 242–247, SciTePress, Barcelona, Spain, February 2013.
[50]
I. Landau and G. Zito, Digital Control Systems, Springer, Berlin, Germany, 2006.
[51]
M. Folgheraiter, M. Jordan, L. M. V. Benitez et al., “Development of a low-pressure fluidic servovalve for wearable haptic interfaces and lightweight robotic systems,” in Informatics in Control, Automation and Robotics, J. Filipe, J. A. Cetto, and J.-L. Ferrier, Eds., vol. 89 of Lecture Notes in Electrical Engineering, pp. 239–253, Springer, Berlin, Germany, 2011.
