Have a personal or library account? Click to login
DESIGN AND DEVELOPMENT OF 3D PRINTED MYOELECTRIC ROBOTIC EXOSKELETON FOR HAND REHABILITATION Cover

DESIGN AND DEVELOPMENT OF 3D PRINTED MYOELECTRIC ROBOTIC EXOSKELETON FOR HAND REHABILITATION

Open Access
|Jun 2017

References

  1. 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-2017-906
  2. 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-2017-522
  3. 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.2015.11.00626847320
  4. 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.2016.7473769
  5. 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-13092523949024
  6. 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/121.9.16959762958
  7. 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/s12541-012-0107-2
  8. 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-z492833127357107
  9. 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), 1.10.1186/1743-0003-10-75372953723855907
  10. Song, R., Tong, K. Y., Hu, X., & Zhou, W. (2013). ‘Myoelectrically controlled wrist robot for stroke rehabilitation’. Journal of neuroengineering and rehabilitation, 10(1), 1.10.1186/1743-0003-10-52368557023758925
  11. 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.
  12. 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.2010.2079334401015520876030
  13. 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.2011.597534022275545
  14. 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.2007.382917
  15. 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.2007.4428558
  16. 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/awm31118156154
  17. 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.2007.4428432
  18. 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.2008.4651199
  19. 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.2009.5209520
  20. 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.2008.201034719144590
  21. 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.10.1155/2016/1712831497626127524880
  22. 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), 1.10.1186/1743-0003-7-36292029020667083
  23. Borboni, A., Mor, M. and Faglia, R. (2016), ‘Gloreha-Hand Robotic Rehabilitation: Design, Mechanical Model, and Experiments’ J. Dyn. Sys., Meas., Control 138(11), 111003.10.1115/1.4033831
  24. The Amadeo® System, Tyromotion. [Online]. Available: http://www.tyromotion.com/en/products/amadeo/.
  25. Maestra Hand and Wrist CPM, Sammons Preston. [Online]. Available: http://www.sammonspreston.com/app.aspx?cmd=get_product&id=91378.
  26. 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/s12541-012-0107-2
  27. 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.10.1155/2016/1712831497626127524880
  28. 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-07-2012-0065
  29. 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).
  30. 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.10.1155/2016/8347478499393127594781
  31. 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), 014502.10.1115/1.4025449
  32. Cram, J. R., Kasman, G. S. and Holtz, J. (2010), ‘Introduction to Surface Electromyography’, 2nd ed. Jones and Bartlett Publishers, 2010.
  33. 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.2012.03.039
  34. 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.2007.04.00417548125
  35. 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.2010.01.02720206934
  36. 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.2012.01.102
  37. 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.2008.91973418632358
  38. Phinyomark, A., Limsakul, C., & Phukpattaranont, P. (2009a). ‘A novel feature extraction for robust EMG pattern recognition’, Journal of Computing, 1(1), 71–80.
Language: English
Page range: 1 - 26
Submitted on: Feb 6, 2017
Accepted on: Apr 15, 2017
Published on: Jun 1, 2017
Published by: Professor Subhas Chandra Mukhopadhyay
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2017 Ismail Ben Abdallah, Yassine Bouteraa, Chokri Rekik, published by Professor Subhas Chandra Mukhopadhyay
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.