Abstract The rise in the cases of motor impairing illnesses demands the research for improvements in rehabilitation therapy. Due to the current situation that the service of the professional therapists cannot meet the need of the motorimpaired subjects, a cloud robotic system is proposed to provide an Internet-based process for upper-limb rehabilitation with multimodal interaction. In this system, therapists and subjects are connected through the Internet using client/server architecture. At the client site, gradual virtual games are introduced so that the subjects can control and interact with virtual objects through the interaction devices such as robot arms. Computer graphics show the geometric results and interaction haptic/force is fed back during exercising. Both video/audio information and kinematical/physiological data are transferred to the therapist for monitoring and analysis. In this way, patients can be diagnosed and directed and therapists can manage therapy sessions remotely. The rehabilitation process can be monitored through the Internet. Expert libraries on the central server can serve as a supervisor and give advice based on the training data and the physiological data. The proposed solution is a convenient application that has several features taking advantage of the extensive technological utilization in the area of physical rehabilitation and multimodal interaction.
This work was supported by the National Key Research and Development Program of China under Grant No. 2016YFB1001300, the National Natural Science Foundation of China under Grant No. 61403080, and the Natural Science Foundation of Jiangsu Province Technology Support Plan under Grant No. BK20140641.
About author: Hui-Jun Li received her B.S. degree in measurement and control in 1999, and M.S. degree in condensed matter physics in 2002 from Zhengzhou University, Zhengzhou, and Ph.D. degree in measurement and control from Southeast University, Nanjing, in 2005. She is currently an associate professor with the School of Instrument Science and Engineering, Southeast University, Nanjing. Her research interests are on teleoperation, space robot and rehabilitation robot.
Cite this article:
Hui-Jun Li, Ai-Guo Song.Architectural Design of a Cloud Robotic System for Upper-Limb Rehabilitation with Multimodal Interaction[J] Journal of Computer Science and Technology, 2017,V32(2): 258-268
 Van Elk M G, Driessen B J F, Dorrepaal M, van der Werff J J, van der Meche E G, Aulbers A P. A motorized gravity compensation mechanism used for active rehabilitation of upper limbs. In Proc. the 9th IEEE International Conference on Rehabilitation Robotics, June 28-July 1, 2005, pp.152-155. Hussain S, Xie S Q, Jamwal P K. Effect of cadence regulation on muscle activation patterns during robot-assisted gait:A dynamic simulation study. IEEE J. Biomed. Health Inform., 2013, 17(2):442-451. Riener R, Nef T, Colombo G. Robot-aided neurorehabilitation of the upper extremities. Med. Biol. Eng. Comput., 2005, 43(1):2-10. Kan P, Huq R, Hoey J, Goetschalckx R, Mihailidis A. The development of an adaptive upper-limb stroke rehabilitation robotic system. J. Neuroeng. Rehabil., 2011, 8:33. Stein J. Robotics in rehabilitation:Technology as destiny. Am. J. Phys. Med. Rehabil., 2012, 91(11 Suppl. 3):S199-S203. Jeon B J, Kim W H, Park E Y. Effect of task-oriented training for people with stroke:A meta-analysis focused on repetitive or circuit training. Topics in Stroke Rehabi litation, 2015, 22(1):34-43. Burgar C G, Lum P S, Shor P C, Machiel Van der Loos H F. Development of robots for rehabilitation therapy:The Palo Alto VA/Stanford experience. J. Rehabil. Res. Dev., 2000, 37(6):663-673. Reinkensmeyer D J, Kahn L E, Arerbuch M, McKenna-Cole A, Schmit B D, Rymer W Z. Understanding and treating arm movement impairment after chronic brain injury:Progress with the arm guide. J. Rehabil. Res. Dev., 2000, 37(6):653-662. Krebs H I, Volpe B T, Aisen M L, Hogan N. Increasing productivity and quality of care:Robot-aided neurorehabilitation. J. Rehabil. Res. Dev., 2000, 37(6):639-652. Zhang Y B,Wang Z X, Ji L H, Bi S. The clinical application of the upper extremity compound movements rehabilitation training robot. In Proc. the 9th International Conference on Rehabilitation Robotics, June 28-July 1, 2005, pp.91-94. Hesse S, Hess A, Werner C C, Kabbert N, Buschfort R. Effect on arm function and cost of robot-assisted group therapy in subacute patients with stroke and a moderately to severely affected arm:A randomized controlled trial. Clinical Rehabilitation, 2014, 28(7):637-647. Daly J J, Hogan N, Perepezko E M, Krebs H I, Rogers J M, Goyal K S, Dohring M E, Fredrickson E, Nethery J, Ruff R L. Response to upper-limb robotics and functional neuromuscular stimulation following stroke. Journal of Rehabilitation Research and Development, 2005, 42(6):723-736. Xu G S, Song A G, Li H J. Control system design for an upper-limb rehabilitation robot. Adv. Robot., 2011, 25(1):229-251. Pan L Z, Song A G, Xu G Z, Li H J, Xu B G, Xiong P W. Hierarchical safety supervisory control strategy for robotassisted rehabilitation exercise. Robotica, 2013, 31(5):757-766. Sivan M, O'Connor R J, Makower S, Levesley M, Bhakta B. Systematic review of outcome measures used in the evaluation of robot-assisted upper limb exercise in stroke. J. Rehabil. Med., 2011, 43(3):181-189. Krebs H I, Hogan N, Aisen M L, Volpe B T. Robot-aided neurorehabilitation. IEEE Trans. Rehabil. Eng., 1998, 6(1):75-87. Lum P S, Burgar C G, Loos M V. The use of a robotic device for post-stroke movement therapy. In Proc. the Conference on Rehabilitation Robotics, April 1997, pp.107-110. Carpinella I, Cattaneo D, Abuarqub S, Ferrarin M. Robotbased rehabilitation of the upper limbs in multiple sclerosis:Feasibility and preliminary results. J. Rehabil. Med., 2009, 41(12):966-970. Shahbazi M, Atashzar S F, Patel R V. A framework for supervised robotics-assisted mirror rehabilitation therapy. In Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems, Sept. 2014, pp.3567-3572. Huijgen B C, Vollenbroek-Hutten M M, Zampolini M, Opisso E, Bernabeu M, van Nieuwenhoven J, Ilsbroukx S, Magni R, Giacomozzi C, Marcellari V, Marchese S S, Hermens H J. Feasibility of a home-based telerehabilitation system compared to usual care:Arm/hand function in patients with stroke, traumatic brain injury and multiple sclerosis. J. Telemed. Telecare, 2008, 14(5):249-256. Forducey P G, Ruwe W D, Dawson S J, Scheideman-Miller C, McDonald N B, Hantla M R. Using telerehabilitation to promote TBI recovery and transfer of knowledge. NeuroRehabilitation, 2003, 18(2):103-111. Zou T, Wang J C, Zhang F Y. Information service model with mobile agent supported. J. Comput. Sci. Technol., 2000, 15(2):150-157. Jadhav C, Nair P, Krovi V. Individualized interactive homebased haptic telerehabilitation. IEEE MultiMedia, 2006, 13(3):32-39. Reinkensmeyer D J, Pang C T, Nessler J A, Painter C C. Web based telerehabilitation for the upper extremity after stroke. IEEE Trans. Neural Syst. Rehabil. Eng., 2002, 10(2):102-108. Song A G,Wu J, Qin G, HuangWY. A novel self-decoupled four degree-of-freedom wrist force/torque sensor. Measurement, 2007, 40(9/10):883-891.
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