Intelligent Systems for Rehabilitation Engineering. Группа авторов

Чтение книги онлайн.

СКАЧАТЬ machine interface, assistive, motion detection, limb injury, etc. They have been used to aid surgeries and therapies, to take care of neurological disorders of patients, assisting patients for movement, etc. Adaptive robotics has been developed catering to patient needs and abilities. Moreover, the application of robots in orthotics, prosthetics, and neuro-rehabilitation has been intriguing. This chapter also presents the scenario of rehabilitation robotics in Europe and the northern part of America. The scope of research lies in the exploration of virtual reality, neural networks, and SVM, and application to robotics. The use of sensing technology in the rehabilitation robots with various degrees of freedom is also worthy of attention. The readers are encouraged to pursue this line of research.

References

      1. Speich, J.E. and Rosen, J., Medical robotics, in: Encyclopedia of biomaterials and biomedical engineering, vol. 983, p. 993, 2004.

      2. Loureiro, R.C., Harwin, W.S., Nagai, K., Johnson, M., Advances in upper limb stroke rehabilitation: a technology push. Med. Biol. Eng. Comput., 49, 10, 1103, 2011.

      3. Yue, Z., Zhang, X., Wang, J., Hand rehabilitation robotics on post-stroke motor recovery. Behav. Neurol., 2017, 2017. 3908135.://doi.org/ 10.1155/2017/3908135

      4. Tefertiller, C., Pharo, B., Evans, N., Winchester, P., Efficacy of rehabilitation robotics for walking training in neurological disorders: A review. J. Rehabil. Res. Dev., 48, 4, 387–416, 2011.

5. Nef, T., Guidali, M., Klamroth-Marganska, V., Riener, R., ARM in-exoskeleton robot for stroke rehabilitation, in: World Congress on Medical Physics and Biomedical Engineering, Munich, Germany, September 7-12, 2009, Springer, Berlin, Heidelberg, pp. 127–130, 2009.

      6. Cardona, M., Destarac, M., Cena, C.G., Robotics for Rehabilitation: A State of the Ar, in: Exoskeleton Robots for Rehabilitation and Healthcare Devices, pp. 1–11, Springer, Singapore, 2020.

      7. Pignolo, L., Robotics in neuro-rehabilitation. J. Rehabil. Med., 41, 12, 955-960, 2009.

      8. Krebs, H.I., Rehabilitation robotics: an academic engineer perspective, in: 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2011, August, IEEE, pp. 6709–6712.

      9. Yakub, F., Khudzari, A.Z.M., Mori, Y., Recent trends for practical rehabilitation robotics, current challenges and the future. Int. J. Rehabil. Res., 37, 1, 9–21, 2014.

      10. Gelderblom, G.J., De Wilt, M., Cremers, G., Rensma, A., Rehabilitation robotics in robotics for healthcare; a roadmap study for the European Commission, in: 2009 IEEE International Conference on Rehabilitation Robotics, 2009, June, IEEE, pp. 834–838.

      11. Rogers, E., Owens, D.H., Werner, H., Freeman, C.T., Lewin, P.L., Kichhoff, S., Lichtenberg, G., Norm optimal iterative learning control with application to problems in accelerator based free electron lasers and rehabilitation robotics. Eur. J. Control, 16, 5, 497–524, 2010.

      12. Pons, J.L., Rehabilitation exoskeletal robotics. IEEE Eng. Med. Biol. Mag., 29, 3, 57–63, 2010.

      13. Dai, J.S., Zhao, T., Nester, C., Sprained ankle physiotherapy based mechanism synthesis and stiffness analysis of a robotic rehabilitation device. Auton. Robots, 16, 2, 207–218, 2004.

      14. Loureiro, R.C. and Harwin, W.S., Reach & grasp therapy: design and control of a 9-DOF robotic neuro-rehabilitation system, in: 2007 IEEE 10th International Conference on Rehabilitation Robotics, 2007, June, IEEE, pp. 757–763.

      15. Novak, D. and Riener, R., Control strategies and artificial intelligence in rehabilitation robotics. Ai Mag., 36, 4, 23-33, 2015.

      16. Krebs, H.I., et al., A paradigm shift for rehabilitation robotics. IEEE Eng. Med. Biol. Mag., 27, 4, 61–70, 2008.

      17. Hillman, M.R., Pullin, G.M., Gammie, A.R., Stammers, C.W., Orpwood, R.D., Clinical experience in rehabilitation robotics. J. Biomed. Eng., 13, 3, 239–243, 1991.

      18. Brunetti, F., Garay, A., Moreno, J.C., Pons, J.L., Enhancing functional electrical stimulation for emerging rehabilitation robotics in the framework of hyper project, in: 2011 IEEE International Conference on Rehabilitation Robotics, 2011, June, IEEE, pp. 1–6.

19. Dogmus, Z., Papantoniou, A., Kilinc, M., Yildirim, S.A., Erdem, E., Patoglu, V., Rehabilitation robotics ontology on the cloud, in: 2013 IEEE 13th International Conference on Rehabilitation Robotics (ICORR), 2013, June, IEEE, pp. 1–6.

      20. Yap, H.K., Lim, J.H., Nasrallah, F., Low, F.Z., Goh, J.C., Yeow, R.C., MRC-glove: A fMRI compatible soft robotic glove for hand rehabilitation application, in: 2015 IEEE International Conference on Rehabilitation Robotics (ICORR), 2015, August, IEEE, pp. 735–740.

      21. Dogmus, Z., Erdem, E., Patoglu, V., RehabRobo-Query: Answering natural language queries about rehabilitation robotics ontology on the cloud. Semant. Web, 10, 3, 605–629, 2019.

      22. Sebastian, G., Li, Z., Crocher, V., Kremers, D., Tan, Y., Oetomo, D., Interaction Force Estimation Using Extended State Observers: An Application to Impedance-Based Assistive and Rehabilitation Robotics. IEEE Robot. Autom. Lett., 4, 2, 1156–1161, 2019.

      23. Krebs, H.I., Volpe, B., Hogan, N., A working model of stroke recovery from rehabilitation robotics practitioners. J. Neuroeng. Rehabil., 6, 1, 6, 2009.

      24. Berezny, N., Dowlatshahi, D., Ahmadi, M., Novel Concept of a Lower-limb Rehabilitation Robot Targeting Bed-bound Acute Stroke Patients. CMBES Proceedings, vol. 42, 2019.

      25. Penalver-Andres, J., Duarte, J., Vallery, H., Klamroth-Marganska, V., Riener, R., Marchal-Crespo, L., Rauter, G., Do we need complex rehabilitation robots for training complex tasks?, in: 2019 IEEE 16th International Conference on Rehabilitation Robotics (ICORR), 2019, June, IEEE, pp. 1085–1090.

      26. Yu, K.P., Yeung, L.F., Ng, S.W., Tong, K.Y., Bionic robotics for post polio walking, in: Intelligent Biomechatronics in Neurorehabilitation, pp. 83–109, Cambridge, Massachusetts, Academic Press, 2020.

      27. Tejima, N., Rehabilitation robotics: a review. Adv. Rob., 14, 7, 551–564, 2001.

      28. Hillman, M., 2 rehabilitation robotics from past to present–a historical perspective, in: Advances in Rehabilitation Robotics, pp. 25–44, Springer, Berlin, Heidelberg, 2004.

      29. Fong, J., Ocampo, R., Gross, D.P., Tavakoli, M., Intelligent Robotics Incorporating Machine Learning Algorithms for Improving Functional Capacity Evaluation and Occupational Rehabilitation. J. Occup. Rehabil., 30, 3, 362–370, 2020.

      30. Mohammadi, A. and Dallali, H., Disturbance observer applications in rehabilitation robotics: an overview, in: Powered Prostheses, pp. 113–133, Cambridge, Massachusetts, Academic Press, 2020.

      31. van Vliet, P. and Wing, A.M., A new challenge—robotics in the rehabilitation of the neurologically motor impaired. Phys. Ther., 71, 1, 39–47, 1991.

      32. Knestel, M., Hofer, E.P., Barillas, S.K., Rupp, R., The artificial muscle as an innovative actuator in rehabilitation robotics. IFAC Proc. Volumes, 41, 2, 773–778, 2008.

33. Munih, M. and Bajd, T., Rehabilitation robotics. Technol. Healthcare, 19, 6, 483–495, 2011.

      34. Krebs, H.I., and Volpe, СКАЧАТЬ