Page 349 - Handbook of Biomechatronics
P. 349
342 Borna Ghannadi et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology
Society. IEEE, pp. 6277–6280. Available from: http://ieeexplore.ieee.org/document/
6091549/.
Frisoli,A.,Loconsole,C.,Leonardis,D.,Banno,F.,Barsotti,M.,Chisari,C.,Bergamasco,M.,
2012. A new gaze-BCI-driven control of an upper limb exoskeleton for rehabilitation
in real-world tasks. IEEE Trans. Syst. Man Cybern. Part C Appl. Rev. 1094-
697742 (6), 1169–1179. https://doi.org/10.1109/TSMCC.2012.2226444. Available
from: http://ieeexplore.ieee.org/document/6392463/.
Fulk, G., O’sullivan, S.B., Schmitz, T.J., 2014. Physical Rehabilitation, sixth ed. F.A. Davis
Company. ISBN 978-0-8036-2579-2.
Ghannadi, B., Mehrabi, N., Sharif Razavian, R., McPhee, J., 2017. Nonlinear model pre-
dictive control of an upper extremity rehabilitation robot using a two-dimensional
human-robot interaction model. In: IEEE/RSJ International Conference on Intelligent
Robots and Systems (IROS). IEEE, Vancouver, British Columbia, Canada,
pp. 502–507. Available from: http://ieeexplore.ieee.org/document/8202200/.
Goodrich,M.A.,Schultz,A.C.,2007.Human-robotinteraction:asurvey.Found.TrendsHum.
Comput. Interact. 1551-39551 (3), 203–275. https://doi.org/10.1561/1100000005.
Available from: http://www.nowpublishers.com/article/Details/HCI-005.
Gopura, R.A.R.C., Bandara, D.S.V., Kiguchi, K., Mann, G.K.I., 2016. Developments in
hardware systems of active upper-limb exoskeleton robots: a review. Robot. Auton.
Syst. 0921889075, 203–220. https://doi.org/10.1016/j.robot.2015.10.001. Available
from: http://www.sciencedirect.com/science/article/pii/S0921889015002274.
Guidali, M., Schmiedeskamp, M., Klamroth, V., Riener, R., 2009. Assessment and training
of synergies with an arm rehabilitation robot. In: 2009 IEEE International Conference
on Rehabilitation Robotics (ICORR). IEEE, pp. 772–776. Available from: http://
ieeexplore.ieee.org/document/5209516/.
Guidali, M., Duschau-Wicke, A., Broggi, S., Klamroth-Marganska, V., Nef, T., Riener, R.,
2011. A robotic system to train activities of daily living in a virtual environment. Med.
Biol. Eng. Comput. 0140-011849 (10), 1213–1223. https://doi.org/10.1007/s11517-
011-0809-0. Available from: http://link.springer.com/10.1007/s11517-011-0809-0.
http://www.ncbi.nlm.nih.gov/pubmed/21796422.
Guo, S., Zhang, W., Wei, W., Guo, J., Ji, Y., Wang, Y., 2013. A kinematic model of an upper
limb rehabilitation robot system. In: 2013 IEEE International Conference on
Mechatronics and Automation. IEEE, pp. 968–973. Available from: http://ieeexplore.
ieee.org/document/6618046/.
Gupta, A., O’Malley, M.K., 2006. Design of a haptic arm exoskeleton for training and rehabil-
itation. IEEE/ASME Trans. Mechatron. 1083-443511 (3), 280–289. https://doi.org/
10.1109/TMECH.2006.875558. Available from: http://ieeexplore.ieee.org/document/
1642690/.
Hatem,S.M.,Saussez,G.,dellaFaille,M.,Prist,V.,Zhang,X.,Dispa,D.,Bleyenheuft,Y.,2016.
Rehabilitation of motor function after stroke: a multiple systematic review focused ontech-
niques to stimulate upper extremity recovery. Front. Hum. Neurosci. 1662-516110, 442.
https://doi.org/10.3389/fnhum.2016.00442. Available from: http://journal.frontiersin.
org/Article/10.3389/fnhum.2016.00442/abstract. http://www.ncbi.nlm.nih.gov/pubmed
/27679565.
Herna ´ndez Arieta, A., Kato, R., Yu, W., Yokoi, H., 2007. The man-machine interaction:
the influence of artificial intelligence on rehabilitation robotics. In: 50 Years of Artificial
IntelligenceSpringer, Berlin, Heidelberg, pp. 221–231. Available from: http://link.
springer.com/10.1007/978-3-540-77296-5_21.
Hesse, S., Schmidt, H., Werner, C., Bardeleben, A., 2003. Upper and lower extremity
robotic devices for rehabilitation and for studying motor control. Curr. Opin. Neurol.
1350-754016, 705–710. https://doi.org/10.1097/00019052-200312000-00010.