This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Aabdallah, I.B., Bouteraa, Y. and Rekik, C. (2016). ‘Design of smart robot for wrist rehabilitation’. International journal of smart sensing and intelligent systems. vol. 9, no. 2.10.21307/ijssis-2017-906Search in Google Scholar
Mehdi, H., & Boubaker, O. (2012). ‘Robot-assisted therapy: design, control and optimization’. International Journal on Smart Sensing and Intelligent Systems, 5(4), 1044-1062.10.21307/ijssis-2017-522Search in Google Scholar
Orihuela-Espina, F., Roldán, G. F., Sánchez-Villavicencio, I., Palafox, L., Leder, R., Sucar, L. E., & Hernández-Franco, J. (2016). ‘Robot training for hand motor recovery in subacute stroke patients: A randomized controlled trial’. Journal of Hand Therapy, 29(1), 51-57.10.1016/j.jht.2015.11.00626847320Search in Google Scholar
Y. Bouteraa and I. Ben Abdallah, Exoskeleton robots for upper-limb rehabilitation, 2016 13th International Multi-Conference on Systems, Signals & Devices (SSD), Leipzig, pp 1-6.10.1109/SSD.2016.7473769Search in Google Scholar
Mazzoleni, S., Sale, P., Franceschini, M., Bigazzi, S., Carrozza, M.C., Dario, P. and Posteraro, F. (2013). ‘Effects of proximal and distal robot-assisted upper limb rehabilitation on chronic stroke recovery’. NeuroRehabilitation, 33 (1) 33–39.10.3233/NRE-13092523949024Search in Google Scholar
Gerloff, C., Corwell, B., Chen, R., Hallett, M. and Cohen, L.G. (1998), ‘The role of the human motor cortex in the control of complex and simple finger movement sequences’. Brain, 121(9), 1695-1709.10.1093/brain/121.9.16959762958Search in Google Scholar
Heo, P., Gu, G. M., Lee, S. J., Rhee, K., & Kim, J. (2012). ‘Current hand exoskeleton technologies for rehabilitation and assistive engineering’. International Journal of Precision Engineering and Manufacturing, 13(5), 807-824.10.1007/s12541-012-0107-2Search in Google Scholar
Bos, R. A., Haarman, C. J., Stortelder, T., Nizamis, K., Herder, J. L., Stienen, A. H., & Plettenburg, D. H. (2016). ‘A structured overview of trends and technologies used in dynamic hand orthoses’. Journal of NeuroEngineering and Rehabilitation, 13(1), 62.10.1186/s12984-016-0168-z492833127357107Search in Google Scholar
Cesqui, B., Tropea, P., Micera, S., & Krebs, H. I. (2013). ‘EMG-based pattern recognition approach in post stroke robot-aided rehabilitation: a feasibility study’. Journal of neuroengineering and rehabilitation, 10(1), 1.10.1186/1743-0003-10-75372953723855907Search in Google Scholar
Song, R., Tong, K. Y., Hu, X., & Zhou, W. (2013). ‘Myoelectrically controlled wrist robot for stroke rehabilitation’. Journal of neuroengineering and rehabilitation, 10(1), 1.10.1186/1743-0003-10-52368557023758925Search in Google Scholar
Ryait, H. S., Arora, A. S., & Agarwal, R. (2009). ‘Study of issues in the development of surface EMG controlled human hand’. Journal of Materials Science: Materials in Medicine, 20(1), 107-114.Search in Google Scholar
Lee, S. W., Wilson, K. M., Lock, B. A., & Kamper, D. G. (2011). ‘Subject-specific myoelectric pattern classification of functional hand movements for stroke survivors’. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 19(5), 558-566.10.1109/TNSRE.2010.2079334401015520876030Search in Google Scholar
Ho, N. S. K., Tong, K. Y., Hu, X. L., Fung, K. L., Wei, X. J., Rong, W., & Susanto, E. A. (2011, June). ‘An EMG-driven exoskeleton hand robotic training device on chronic stroke subjects: task training system for stroke rehabilitation’. In Proceedings of the 2011 IEEE international conference on rehabilitation robotics (pp. 1-5).10.1109/ICORR.2011.597534022275545Search in Google Scholar
Kiguchi, K. (2007, June). ‘A study on emg-based human motion prediction for power assist exoskeletons’. In Proceedings of the 2007 International Symposium on Computational Intelligence in Robotics and Automation (pp. 190-195).10.1109/CIRA.2007.382917Search in Google Scholar
Masia, L., Krebs, H. I., Cappa, P., & Hogan, N. (2007, June). ‘Design, characterization, and impedance limits of a hand robot’. In Proceedings of the 2007 IEEE 10th International Conference on Rehabilitation Robotics (pp. 1085-1089).10.1109/ICORR.2007.4428558Search in Google Scholar
Takahashi, C. D., Der-Yeghiaian, L., Le, V., Motiwala, R. R., & Cramer, S. C. (2008). ‘Robot-based hand motor therapy after stroke’. Brain, 131(2), 425-437.10.1093/brain/awm31118156154Search in Google Scholar
Kawasaki, H., Ito, S., Ishigure, Y., Nishimoto, Y., Aoki, T., Mouri, T.& Abe, M. (2007, June). ‘Development of a hand motion assist robot for rehabilitation therapy by patient selfmotion control’. In Proceedings of the 2007 IEEE 10th International Conference on Rehabilitation Robotics (pp. 234-240).10.1109/ICORR.2007.4428432Search in Google Scholar
Hasegawa, Y., Mikami, Y., Watanabe, K., Firouzimehr, Z., & Sankai, Y. (2008, September). ‘Wearable handling support system for paralyzed patient’. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 741-746).10.1109/IROS.2008.4651199Search in Google Scholar
Lambercy, O., Dovat, L., Yun, H., Wee, S. K., Kuah, C., Chua, K.& Burdet, E. (2009, June). ‘Rehabilitation of grasping and forearm pronation/supination with the Haptic Knob’. In Proceedings of the IEEE International Conference on Rehabilitation Robotics (pp. 22-27).10.1109/ICORR.2009.5209520Search in Google Scholar
Dovat, L., Lambercy, O., Gassert, R., Maeder, T., Milner, T., Teo C. and Burdet, E. (2008), ‘HandCARE: A cable-actuated rehabilitation system to train hand function after stroke’, IEEE Transaction in Neural Systems and Rehabilitation Engineering, 16(6), pp. 582–591.10.1109/TNSRE.2008.201034719144590Search in Google Scholar
Felipe, J., Pereyra, A. and Castillo-Castaneda, E. (2016), ‘Design of a Reconfigurable Robotic System for Flexoextension Fitted to Hand Fingers Size’, Applied Bionics and Biomechanics, vol. 2016, Article ID 1712831, 10 pages.10.1155/2016/1712831497626127524880Search in Google Scholar
Schabowsky, C. N., Godfrey, S. B., Holley, R. J., & Lum, P. S. (2010). ‘Development and pilot testing of HEXORR: hand EXOskeleton rehabilitation robot’. Journal of neuroengineering and rehabilitation, 7(1), 1.10.1186/1743-0003-7-36292029020667083Search in Google Scholar
Borboni, A., Mor, M. and Faglia, R. (2016), ‘Gloreha-Hand Robotic Rehabilitation: Design, Mechanical Model, and Experiments’ J. Dyn. Sys., Meas., Control 138(11), 111003.10.1115/1.4033831Search in Google Scholar
The Amadeo® System, Tyromotion. [Online]. Available: http://www.tyromotion.com/en/products/amadeo/.Search in Google Scholar
Maestra Hand and Wrist CPM, Sammons Preston. [Online]. Available: http://www.sammonspreston.com/app.aspx?cmd=get_product&id=91378.Search in Google Scholar
Heo, P., Gu, G. M., Lee, S. J., Rhee, K., & Kim, J. (2012). ‘Current hand exoskeleton technologies for rehabilitation and assistive engineering’. International Journal of Precision Engineering and Manufacturing, 13(5), 807-824.10.1007/s12541-012-0107-2Search in Google Scholar
Aguilar-Pereyra, J.F. and Castillo-Castaneda, E. (2016) ‘Design of a Reconfigurable Robotic System for Flexoextension Fitted to Hand Fingers Size’. Applied Bionics and Biomechanics, vol. 2016, Article ID 1712831, 10 pages.10.1155/2016/1712831497626127524880Search in Google Scholar
Negi, S., Dhiman, S., & Kumar Sharma, R. (2014). ‘Basics and applications of rapid prototyping medical models’. Rapid Prototyping Journal, 20(3), 256-267.10.1108/RPJ-07-2012-0065Search in Google Scholar
Hieu, L. C., Sloten, J. V., Hung, L. T., Khanh, L., Soe, S., Zlatov, N., ...& Trung, P. D. (2010, September). ‘Medical reverse engineering applications and methods’. In 2ND International Conference on Innovations, Recent Trends and Challenges in Mechatronics, Mechanical Engineering and New High-Tech Products Development, MECAHITECH (Vol. 10, pp. 232-246).Search in Google Scholar
Baronio, G., Harran, S. and Signoroni, A. (2016), ‘A critical analysis of a hand orthosis reverse engineering and 3D printing process’, Applied Bionics and Biomechanics, vol. 2016, Article ID 8347478, 7 pages.10.1155/2016/8347478499393127594781Search in Google Scholar
Yeow, C. H., Baisch, A. T., Talbot, S. G., & Walsh, C. J. (2014). ‘Cable-Driven Finger Exercise Device With Extension Return Springs for Recreating Standard Therapy Exercises’. Journal of Medical Devices, 8(1), 014502.10.1115/1.4025449Search in Google Scholar
Cram, J. R., Kasman, G. S. and Holtz, J. (2010), ‘Introduction to Surface Electromyography’, 2nd ed. Jones and Bartlett Publishers, 2010.Search in Google Scholar
Phinyomark, A., Phukpattaranont, P., & Limsakul, C. (2012). ‘Fractal analysis features for weak and single-channel upper-limb EMG signals’. Expert Systems with Applications, 39(12), 11156-11163.10.1016/j.eswa.2012.03.039Search in Google Scholar
Mello, R. G., Oliveira, L. F., & Nadal, J. (2007). ‘Digital Butterworth filter for subtracting noise from low magnitude surface electromyogram’. Computer methods and programs in biomedicine, 87(1), 28-35.10.1016/j.cmpb.2007.04.00417548125Search in Google Scholar
De Luca, C.J., Donald, L.G., Mikhail, K. and Serge, H.R. (2010). ‘Filtering the surface EMG signal: Movement artifact and baseline noise contamination’. Journal of Biomechanics, 43 (8), pp. 1573–1579.10.1016/j.jbiomech.2010.01.02720206934Search in Google Scholar
Phinyomark, A., Phukpattaranont, P., & Limsakul, C. (2012c). ‘Feature reduction and selection for EMG signal classification’. Expert Systems with Applications, 39(8), 7420–7431.10.1016/j.eswa.2012.01.102Search in Google Scholar
Oskoei, M. A., & Hu, H. (2008). ‘Support vector machine-based classification scheme for myoelectric control applied to upper limb’. IEEE transactions on biomedical engineering, 55(8), 1956-1965.10.1109/TBME.2008.91973418632358Search in Google Scholar
Phinyomark, A., Limsakul, C., & Phukpattaranont, P. (2009a). ‘A novel feature extraction for robust EMG pattern recognition’, Journal of Computing, 1(1), 71–80.Search in Google Scholar