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, B.T., Rehabilitation robotics, in: Handbook of clinical neurology, vol. 110, pp. 283–294, Amsterdam, Elsevier, 2013.
35. Rosier, J.C. et al., Rehabilitation robotics: The MANUS concept, in: Fifth International Conference on Advanced Robotics’ Robots in Unstructured Environments, 1991, June, IEEE, pp. 893–898.
36. Krebs, H.I., Palazzolo, J.J., Dipietro, L., Ferraro, M., Krol, J., Rannekleiv, K., Hogan, N., Rehabilitation robotics: Performance-based progressive robot-assisted therapy. Auton. Robots, 15, 1, 7–20, 2003.
37. Riener, R., Frey, M., Bernhardt, M., Nef, T., Colombo, G., Human-centered rehabilitation robotics, in: 9th International Conference on Rehabilitation Robotics, 2005. ICORR 2005, 2005, June, IEEE, pp. 319–322.
38. Weinberg, B., Nikitczuk, J., Patel, S., Patritti, B., Mavroidis, C., Bonato, P., Canavan, P., Design, control and human testing of an active knee rehabilitation orthotic device, in: Proceedings 2007 IEEE International Conference on Robotics and Automation, 2007, April, IEEE, pp. 4126–4133.
39. Chisholm, K.J., Klumper, K., Mullins, A., Ahmadi, M., A task oriented haptic gait rehabilitation robot. Mechatronics, 24, 8, 1083–1091, 2014.
40. O’Neill, C. et al., Inflatable soft wearable robot for reducing therapist fatigue during upper extremity rehabilitation in severe stroke. IEEE Rob. Autom. Lett., 5, 3, 3899–3906, 2020.
41. Kwee, H.H., Rehabilitation robotics-softening the hardware. IEEE Eng. Med. Biol. Mag., 14, 3, 330–335, 1995.
42. Rocon, E., Belda-Lois, J.M., Ruiz, A.F., Manto, M., Moreno, J.C., Pons, J.L., Design and validation of a rehabilitation robotic exoskeleton for tremor assessment and suppression. IEEE Trans. Neural Syst. Rehabil. Eng., 15, 3, 367–378, 2007.
43. Rocon, E., Moreno, J.C., Ruiz, A.F., Brunetti, F., Miranda, J.A., Pons, J.L., Application of inertial sensors in rehabilitation robotics, in: 2007 IEEE 10th International Conference on Rehabilitation Robotics, 2007, June, IEEE, pp. 145–150.
44. Sartori, M., Reggiani, M., Mezzato, C., Pagello, E., A lower limb EMG-driven biomechanical model for applications in rehabilitation robotics, in: 2009 International Conference on Advanced Robotics, 2009, June, IEEE, pp. 1–7.
45. Guo, K., Zha, S., Liu, Y., Liu, B., Yang, H., Li, Z., Experimental Study On Wearable Ankle Rehabilitation Device, in: 2019 International Conference on Mathematics, Big Data Analysis and Simulation and Modelling (MBDASM 2019), 2019, October, Atlantis Press.
46. Harwin, W.S., Gosine, R.G., Kazi, Z., Lees, D.S., Dallaway, J.L., A comparison of rehabilitation robotics languages and software. Robotica, 15, 2, 133–151, 1997.
47. Galindo, C., Gonzalez, J., Fernández-Madrigal, J.A., An architecture for cognitive human-robot integration. Application to rehabilitation robotics, in: IEEE International Conference Mechatronics and Automation, 2005, 2005, July, vol. 1, IEEE, pp. 329–334.
48. Beckerle, P., Salvietti, G., Unal, R., Prattichizzo, D., Rossi, S., Castellini, C., Mastrogiovanni, F., A human–robot interaction perspective on assistive and rehabilitation robotics. Front. Neurorob., 11, 24, 2017.
49. Sabatini, A.M., Genovese, V., Maini, E.S., Toward low-cost vision-based 2D localisation systems for applications in rehabilitation robotics, in: IEEE/RSJ International Conference on Intelligent Robots and Systems, 2002, October, vol. 2, IEEE, pp. 1355–1360.
50. Mokhtari, M., Abdulrazak, B., Feki, M.A., Rodriguez, R., Grandjean, B., Integration of rehabilitation robotics in the context of smart homes: Application to assistive robotics. Int. J. Human-friendly Welfare Robot. Syst. (HWRSERS), 4, 2, 29–32, 2003.
51. Buerger, S.P., Palazzolo, J.J., Krebs, H.I., Hogan, N., Rehabilitation robotics: adapting robot behavior to suit patient needs and abilities, in: Proceedings of the 2004 American Control Conference, 2004, June, vol. 4, IEEE, pp. 3239–3244.
52. Rittenhouse, D.M., Abdullah, H.A., Runciman, R.J., Basir, O., A neural network model for reconstructing EMG signals from eight shoulder muscles: Consequences for rehabilitation robotics and biofeedback. J. Biomech., 39, 10, 1924–1932, 2006.
53. Riener, R., Wellner, M., Nef, T., Von Zitzewitz, J., Duschau-Wicke, A., Colombo, G., Lunenburger, L., A view on VR-enhanced rehabilitation robotics, in: 2006 International Workshop on Virtual Rehabilitation, 2006, August, IEEE, pp. 149–154.
54. Appel, V.C., Belini, V.L., Jong, D.H., Magalhães, D.V., Caurin, G.A., Classifying emotions in rehabilitation robotics based on facial skin temperature, in: 5th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics, 2014, August, IEEE, pp. 276–280.
55. Wang, W.S., Mendonca, R., Kording, K., Avery, M., Johnson, M.J., Towards Data-Driven Autonomous Robot-Assisted Physical Rehabilitation Therapy, in: 2019 IEEE 16th International Conference on Rehabilitation Robotics (ICORR), 2019, June, IEEE, pp. 34–39.
56. Kovács, L.L. and Stépán, G., Dynamics of digital force control applied in rehabilitation robotics. Meccanica, 38, 2, 213–226, 2003.
57. Patton, J.L., Dawe, G., Scharver, C., Mussa-Ivaldi, F.A., Kenyon, R., Robotics and virtual reality: the development of a life-sized 3-D system for the rehabilitation of motor function, in: The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2004, September, vol. 2, IEEE, pp. 4840–4843.
58. Wolbrecht, E.T., Leavitt, J., Reinkensmeyer, D.J., Bobrow, J.E., Control of a pneumatic orthosis for upper extremity stroke rehabilitation, in: 2006 International Conference of the IEEE Engineering in Medicine and Biology Society, 2006, August, IEEE, pp. 2687–2693.
59. Banala, S.K., Agrawal, S.K., Scholz, J.P., Active Leg Exoskeleton (ALEX) for gait rehabilitation of motor-impaired patients, in: 2007 IEEE 10th International Conference on Rehabilitation Robotics, 2007, June, IEEE, pp. 401–407.
60. Mihelj, M., Novak, D., Ziherl, J., Olenšek, A., Munih, M., Challenges in biocooperative rehabilitation robotics, in: 2011 IEEE International Conference on Rehabilitation Robotics, 2011, June, IEEE, pp. 1–6.
61. Zhang, J., Cheah, C.C., Collins, S.H., Stable human-robot interaction control for upper-limb rehabilitation robotics, in: 2013 IEEE International Conference on Robotics and Automation, 2013, May, IEEE, pp. 2201–2206.
62. Koçak, M., Ayar, O., Gezgın, E., Preliminary Study on the Admittance Control of a Hand Rehabilitation System, in: 2019 Medical Technologies Congress (TIPTEKNO), 2019, October, IEEE, pp. 1–4.
63. Feil-Seifer, D. and Mataric, M.J., Defining socially assistive robotics, in: 9th International Conference on Rehabilitation Robotics, 2005. ICORR 2005, 2005, June, IEEE, pp. 465–468.
64. Matarić, M.J., Eriksson, J., Feil-Seifer, D.J., Winstein, C.J., Socially assistive robotics for post-stroke rehabilitation. J. NeuroEng. Rehabil., 4, 1, 5, 2007.
65. Fasoli, S.E. and Adans-Dester, C.P., A Paradigm Shift: Rehabilitation Robotics, Cognitive Skills Training and Function after Stroke. Front. Neurol., 10, 1088, 2019.
66. Aguirre, A., Casas, J., Céspedes, N., Múnera, M., Rincon-Roncancio, M., Cuesta-Vargas, A., Cifuentes, C.A., Feasibility study: Towards Estimation