References
[1]
Wolfe C D A. The impact of stroke. Brit Med Bull, 2000, 56: 275--286.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Wolfe C D A. The impact of stroke. Brit Med Bull, 2000, 56: 275--286&
[2]
Wang L D. Report on the Chinese Stroke Prevention. Beijing: Peking Union Medical College Press, 2015. 53--62.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Wang L D. Report on the Chinese Stroke Prevention. Beijing: Peking Union Medical College Press, 2015. 53--62&
[3]
Wang S, Marquez P, Langenbrunner J, et al. Toward a Healthy and Harmonious Life in China: Stemming the Rising Tide of Non-communicable Diseases. The World Bank Report Number 62318-CN, 2011. 1--48.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Wang S, Marquez P, Langenbrunner J, et al. Toward a Healthy and Harmonious Life in China: Stemming the Rising Tide of Non-communicable Diseases. The World Bank Report Number 62318-CN, 2011. 1--48&
[4]
Mendis S, Puska P, Norrving B, et al. Global Atlas on Cardiovascular Disease Prevention and Control. Geneva: World Health Organization, 2011. 8--13.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Mendis S, Puska P, Norrving B, et al. Global Atlas on Cardiovascular Disease Prevention and Control. Geneva: World Health Organization, 2011. 8--13&
[5]
Krebs H I, Palazzolo J J, Dipietro L, et al. Rehabilitation robotics: performance-based progressive robot-assisted therapy. Auton Robot, 2003, 15: 7--20.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Krebs H I, Palazzolo J J, Dipietro L, et al. Rehabilitation robotics: performance-based progressive robot-assisted therapy. Auton Robot, 2003, 15: 7--20&
[6]
Mohammad M F, Reza B. Impedance control of robots using voltage control strategy. Nonlinear Dynam, 2013, 74: 277--286.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Mohammad M F, Reza B. Impedance control of robots using voltage control strategy. Nonlinear Dynam, 2013, 74: 277--286&
[7]
Colombo R, Pisano F, Micera S, et al. Assessing mechanisms of recovery during robot-aided neurorehabilitation of the upper extremity. Neurorehab Neural Repair, 2008, 22: 50--63.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Colombo R, Pisano F, Micera S, et al. Assessing mechanisms of recovery during robot-aided neurorehabilitation of the upper extremity. Neurorehab Neural Repair, 2008, 22: 50--63&
[8]
Koh C L, Hoffmann T, Bennett S, et al. Management of patients with cognitive impairment after stroke: a survey of australian occupational therapists. Aust Occup Ther J, 2009, 56: 324--331.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Koh C L, Hoffmann T, Bennett S, et al. Management of patients with cognitive impairment after stroke: a survey of australian occupational therapists. Aust Occup Ther J, 2009, 56: 324--331&
[9]
Hogan N, Krebs H I, Rohrer B, et al. Motions or muscles? some behavioral factors underlying robotic assistance of motor recovery. J Rehabil Res Dev, 2006, 43: 605--618.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Hogan N, Krebs H I, Rohrer B, et al. Motions or muscles? some behavioral factors underlying robotic assistance of motor recovery. J Rehabil Res Dev, 2006, 43: 605--618&
[10]
Riener R, Lunenburger L, Colombo G. Human-centered robotics applied to gait training and assessment. J Rehabil Res Dev, 2006, 43: 679--693.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Riener R, Lunenburger L, Colombo G. Human-centered robotics applied to gait training and assessment. J Rehabil Res Dev, 2006, 43: 679--693&
[11]
Maciejasz P, Eschweiler J, Gerlach-Hahn K, et al. A survey on robotic devices for upper limb rehabilitation. J Neuroeng Rehabil, 2014, 11: 3--32.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Maciejasz P, Eschweiler J, Gerlach-Hahn K, et al. A survey on robotic devices for upper limb rehabilitation. J Neuroeng Rehabil, 2014, 11: 3--32&
[12]
Hu J, Hou Z G, Chen Y X, et al. Lower limb rehabilitation robots and interactive control methods. Act Autom Sin, 2014, 40: 2377--2390.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Hu J, Hou Z G, Chen Y X, et al. Lower limb rehabilitation robots and interactive control methods. Act Autom Sin, 2014, 40: 2377--2390&
[13]
Klamroth-Marganska V, Blanco J, Campen K, et al. Three-dimensional, task-specific robot therapy of the arm after stroke: a multicentre, parallel-group randomised trial. Lancet Neurol, 2014, 13: 159--166.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Klamroth-Marganska V, Blanco J, Campen K, et al. Three-dimensional, task-specific robot therapy of the arm after stroke: a multicentre, parallel-group randomised trial. Lancet Neurol, 2014, 13: 159--166&
[14]
Lo A C, Guarino P D, Richards L G, et al. Robot-assisted therapy for long-term upper-limb impairment after stroke. New Engl J Med, 2010, 362: 1772--1783.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Lo A C, Guarino P D, Richards L G, et al. Robot-assisted therapy for long-term upper-limb impairment after stroke. New Engl J Med, 2010, 362: 1772--1783&
[15]
Buerger S P, Palazzolo J J, Krebs H I, et al. Rehabilitation robotics: adapting robot behavior to suit patient needs and abilities. In: Proceedings of the 2004 American Control Conference, Boston, 2004. 3239--3244.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Buerger S P, Palazzolo J J, Krebs H I, et al. Rehabilitation robotics: adapting robot behavior to suit patient needs and abilities. In: Proceedings of the 2004 American Control Conference, Boston, 2004. 3239--3244&
[16]
Tsukahara A, Hasegawa Y, Eguchi K, et al. Restoration of gait for spinal cord injury patients using HAL with intention estimator for preferable swing speed. IEEE Trans Neural Syst Rehabil Eng, 2015, 23: 308--318.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Tsukahara A, Hasegawa Y, Eguchi K, et al. Restoration of gait for spinal cord injury patients using HAL with intention estimator for preferable swing speed. IEEE Trans Neural Syst Rehabil Eng, 2015, 23: 308--318&
[17]
Lunenburger L, Colombo G, Riener R. Biofeedback for robotic gait rehabilitation. J Neuroeng Rehabil, 2007, 4: 1--11.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Lunenburger L, Colombo G, Riener R. Biofeedback for robotic gait rehabilitation. J Neuroeng Rehabil, 2007, 4: 1--11&
[18]
Goffer A. EP Patent, 1 260 201, 2008-12-10.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Goffer A. EP Patent, 1 260 201, 2008-12-10&
[19]
Prange G B, Jannink M J A, Groothuis-Oudshoorn C G M, et al. Systematic review of the effect of robot-aided therapy on recovery of the hemiparetic arm after stroke. J Rehabil Res Dev, 2006, 43: 171--183.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Prange G B, Jannink M J A, Groothuis-Oudshoorn C G M, et al. Systematic review of the effect of robot-aided therapy on recovery of the hemiparetic arm after stroke. J Rehabil Res Dev, 2006, 43: 171--183&
[20]
Zhang M M, Davies T C, Xie S N. Effectiveness of robot-assisted therapy on ankle rehabilitation-a systematic review. J Neuroeng Rehabil, 2013, 10: 1--16.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Zhang M M, Davies T C, Xie S N. Effectiveness of robot-assisted therapy on ankle rehabilitation-a systematic review. J Neuroeng Rehabil, 2013, 10: 1--16&
[21]
Marchal-Crespo L, Reinkensmeyer D J. Review of control strategies for robotic movement training after neurologic injury. J Neuroeng Rehabil, 2009, 6: 1--15.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Marchal-Crespo L, Reinkensmeyer D J. Review of control strategies for robotic movement training after neurologic injury. J Neuroeng Rehabil, 2009, 6: 1--15&
[22]
Qian B, Yang C J. Human-machine interaction force control: using a model-referenced adaptive impedance device to control an index finger exoskeleton. J Zhejiang Univ Sci C: Comput Electron, 2014, 15: 275--283.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Qian B, Yang C J. Human-machine interaction force control: using a model-referenced adaptive impedance device to control an index finger exoskeleton. J Zhejiang Univ Sci C: Comput Electron, 2014, 15: 275--283&
[23]
Mitsantisuk C, Ohishi K. Robotics-assisted rehabilitation therapy for the hands and wrists using force sensorless bilateral control with shadow and mirror mode. In: Proceedings of IEEE International Conference on Mechatronics, Nagoya, 2015. 541--546.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Mitsantisuk C, Ohishi K. Robotics-assisted rehabilitation therapy for the hands and wrists using force sensorless bilateral control with shadow and mirror mode. In: Proceedings of IEEE International Conference on Mechatronics, Nagoya, 2015. 541--546&
[24]
Johnson M J, Loureiro R C, Harwin W S. Collaborative tele-rehabilitation and robot-mediated therapy for stroke rehabilitation at home or clinic. Intell Serv Robot, 2008, 1: 109--121.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Johnson M J, Loureiro R C, Harwin W S. Collaborative tele-rehabilitation and robot-mediated therapy for stroke rehabilitation at home or clinic. Intell Serv Robot, 2008, 1: 109--121&
[25]
Dai H, Jiang G Y. Rehabilitation Medicine. 3rd ed. Beijing: Peking University Medical Press, 2013. 26--34.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Dai H, Jiang G Y. Rehabilitation Medicine. 3rd ed. Beijing: Peking University Medical Press, 2013. 26--34&
[26]
Pons T P, Garraghty P E, Ommaya A K, et al. Massive cortical reorganization after sensory deafferentation in adult macaques. Science, 1991, 252: 1857--1860.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Pons T P, Garraghty P E, Ommaya A K, et al. Massive cortical reorganization after sensory deafferentation in adult macaques. Science, 1991, 252: 1857--1860&
[27]
Takahashi C D, Der-Yeghiaian L, Le V, et al. Robot-based hand motor therapy after stroke. Brain, 2008, 131: 425--437.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Takahashi C D, Der-Yeghiaian L, Le V, et al. Robot-based hand motor therapy after stroke. Brain, 2008, 131: 425--437&
[28]
Lo H S, Sheng Q X. Exoskeleton robots for upper-limb rehabilitation: state of the art and future prospects. Med Eng Phys, 2012, 34: 261--268.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Lo H S, Sheng Q X. Exoskeleton robots for upper-limb rehabilitation: state of the art and future prospects. Med Eng Phys, 2012, 34: 261--268&
[29]
Formaggio E, Storti S F, Galazzo I B, et al. Modulation of event-related desynchronization in robot-assisted hand performance: brain oscillatory changes in active, passive and imagined movements. J Neuroeng Rehabil, 2013, 10: 80--128.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Formaggio E, Storti S F, Galazzo I B, et al. Modulation of event-related desynchronization in robot-assisted hand performance: brain oscillatory changes in active, passive and imagined movements. J Neuroeng Rehabil, 2013, 10: 80--128&
[30]
Lotze M, Braun C, Birbaumer N, et al. Motor learning elicited by voluntary drive. Brain, 2003, 126: 866--872.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Lotze M, Braun C, Birbaumer N, et al. Motor learning elicited by voluntary drive. Brain, 2003, 126: 866--872&
[31]
Cai L L, Fong A J, Otoshi C K, et al. Implications of assist-as-needed robotic step training after a complete spinal cordinjury on intrinsic strategies of motor learning. J Neurosci, 2006, 26: 10564--10568.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Cai L L, Fong A J, Otoshi C K, et al. Implications of assist-as-needed robotic step training after a complete spinal cordinjury on intrinsic strategies of motor learning. J Neurosci, 2006, 26: 10564--10568&
[32]
Hussain S, Xie S Q, Liu G Y. Robot assisted treadmill training: mechanisms and training strategies. Med Eng Phys, 2011, 33: 527--533.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Hussain S, Xie S Q, Liu G Y. Robot assisted treadmill training: mechanisms and training strategies. Med Eng Phys, 2011, 33: 527--533&
[33]
Huang T H, Huang H P, Cheng C A, et al. Design of a new hybrid control and knee orthosis for human walking and rehabilitation. In: Proceedings of the 25th IEEE/RSJ International Conference on Intelligent Robots and Systems, Algarve, 2012. 3653--3658.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Huang T H, Huang H P, Cheng C A, et al. Design of a new hybrid control and knee orthosis for human walking and rehabilitation. In: Proceedings of the 25th IEEE/RSJ International Conference on Intelligent Robots and Systems, Algarve, 2012. 3653--3658&
[34]
Roy A, Krebs H I, Williams D J, et al. Robot-aided neurorehabilitation: a novel robot for ankle rehabilitation. IEEE Trans Robot, 2009, 25: 569--582.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Roy A, Krebs H I, Williams D J, et al. Robot-aided neurorehabilitation: a novel robot for ankle rehabilitation. IEEE Trans Robot, 2009, 25: 569--582&
[35]
Lawson B E, Varol H A, Goldfarb M. Ground adaptive standing controller for a powered transfemoral prosthesis. In: Proceedings of 2011 IEEE International Conference on Rehabilitation Robotics, Zurich, 2011. 1--6.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Lawson B E, Varol H A, Goldfarb M. Ground adaptive standing controller for a powered transfemoral prosthesis. In: Proceedings of 2011 IEEE International Conference on Rehabilitation Robotics, Zurich, 2011. 1--6&
[36]
Ibarra J C P, Siqueira A A G. Impedance control of rehabilitation robots for lower limbs, review. In: Proceedings of 2014 Joint Conference on Robotics: SBR-LARS Robotics Symposium and Robocontrol, Sao Carlos, 2014. 235--240.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Ibarra J C P, Siqueira A A G. Impedance control of rehabilitation robots for lower limbs, review. In: Proceedings of 2014 Joint Conference on Robotics: SBR-LARS Robotics Symposium and Robocontrol, Sao Carlos, 2014. 235--240&
[37]
Robertson G, Caldwell G, Hamill J, et al. Research Methods in Biomechanics. Champaign: Human Kinetics, 2013. 179--182.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Robertson G, Caldwell G, Hamill J, et al. Research Methods in Biomechanics. Champaign: Human Kinetics, 2013. 179--182&
[38]
Luca C J D. The use of surface electromyography in biomechanics. J Appl Biomech, 1997, 13: 135--163.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Luca C J D. The use of surface electromyography in biomechanics. J Appl Biomech, 1997, 13: 135--163&
[39]
Tong L N, Hou Z G, Peng L, et al. Multi-channel sEMG time series analysis based human motion recognition method. Act Autom Sin, 2014, 40: 810--821.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Tong L N, Hou Z G, Peng L, et al. Multi-channel sEMG time series analysis based human motion recognition method. Act Autom Sin, 2014, 40: 810--821&
[40]
Zhang F, Li P F, Hou Z G, et al. sEMG-based continuous estimation of joint angles of human legs by using BP neural network. Neurocomputing, 2012, 78: 139--148.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Zhang F, Li P F, Hou Z G, et al. sEMG-based continuous estimation of joint angles of human legs by using BP neural network. Neurocomputing, 2012, 78: 139--148&
[41]
Artemiadis P. EMG-based robot control interfaces: past, present and future. Adv Robot Autom, 2012, 1: 1--3.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Artemiadis P. EMG-based robot control interfaces: past, present and future. Adv Robot Autom, 2012, 1: 1--3&
[42]
Ding Q C, Xiong A B, Zhao X G, et al. A review on researches and applications of sEMG-based motion intent recognition methods. Act Autom Sin, 2016, 42: 13--25.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Ding Q C, Xiong A B, Zhao X G, et al. A review on researches and applications of sEMG-based motion intent recognition methods. Act Autom Sin, 2016, 42: 13--25&
[43]
Chu J U, Moon I, Lee Y J, et al. A supervised feature-projection-based real-time EMG pattern recognition for multifunction myoelectric hand control. IEEE/ASME Trans Mech 2007, 12: 282--290.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Chu J U, Moon I, Lee Y J, et al. A supervised feature-projection-based real-time EMG pattern recognition for multifunction myoelectric hand control. IEEE/ASME Trans Mech 2007, 12: 282--290&
[44]
Hashemi J, Morin E, Mousavi P, et al. Enhanced dynamic EMG-force estimation through calibration and PCI modeling. IEEE Trans Neural Syst Rehabil Eng, 2015, 23: 41--50.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Hashemi J, Morin E, Mousavi P, et al. Enhanced dynamic EMG-force estimation through calibration and PCI modeling. IEEE Trans Neural Syst Rehabil Eng, 2015, 23: 41--50&
[45]
Daley H, Englehart K, Hargrove L, et al. High density electromyography data of normally limbed and transradial amputee subjects for multifunction prosthetic control. J Electromyogr Kines, 2012, 22: 478--484.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Daley H, Englehart K, Hargrove L, et al. High density electromyography data of normally limbed and transradial amputee subjects for multifunction prosthetic control. J Electromyogr Kines, 2012, 22: 478--484&
[46]
Mulas M, Folgheraiter M, Gini G. An EMG-controlled exoskeleton for hand rehabilitation. In: Proceedings of the 9th International Conference on Rehabilitation Robotics, Chicago, 2015. 371--374.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Mulas M, Folgheraiter M, Gini G. An EMG-controlled exoskeleton for hand rehabilitation. In: Proceedings of the 9th International Conference on Rehabilitation Robotics, Chicago, 2015. 371--374&
[47]
Scheme E, Englehart K. Electromyogram pattern recognition for control of powered upper-limb prostheses: state of the art and challenges for clinical use. J Rehabil Res Dev, 2011, 48: 643--659.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Scheme E, Englehart K. Electromyogram pattern recognition for control of powered upper-limb prostheses: state of the art and challenges for clinical use. J Rehabil Res Dev, 2011, 48: 643--659&
[48]
Ngeo J G, Tamei T, Shibata T. Continuous and simultaneous estimation of finger kinematics using inputs from an EMG-to-muscle activation model. J Neuroeng Rehabil, 2014, 11: 1--14.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Ngeo J G, Tamei T, Shibata T. Continuous and simultaneous estimation of finger kinematics using inputs from an EMG-to-muscle activation model. J Neuroeng Rehabil, 2014, 11: 1--14&
[49]
Au S K, Herr H. Powered ankle-foot prosthesis. Robot Autom Mag, 2008, 15: 52--59.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Au S K, Herr H. Powered ankle-foot prosthesis. Robot Autom Mag, 2008, 15: 52--59&
[50]
Makowski N S, Knutson J S, Chae J, et al. Control of robotic assistance using poststroke residual voluntary effort. IEEE Trans Neural Syst Rehabil Eng, 2015, 23: 221--231.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Makowski N S, Knutson J S, Chae J, et al. Control of robotic assistance using poststroke residual voluntary effort. IEEE Trans Neural Syst Rehabil Eng, 2015, 23: 221--231&
[51]
Huang H, Zhou P, Li G, et al. Spatial filtering improves EMG classification accuracy following targeted muscle reinnervation. Ann Biomed Eng, 2009, 37: 1849--1857.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Huang H, Zhou P, Li G, et al. Spatial filtering improves EMG classification accuracy following targeted muscle reinnervation. Ann Biomed Eng, 2009, 37: 1849--1857&
[52]
Dosen S, Muceli S, Dideriksen J L, et al. Online tremor suppression using electromyography and low-level electrical stimulation. IEEE Trans Neural Syst Rehabil Eng, 2015, 23: 385--395.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Dosen S, Muceli S, Dideriksen J L, et al. Online tremor suppression using electromyography and low-level electrical stimulation. IEEE Trans Neural Syst Rehabil Eng, 2015, 23: 385--395&
[53]
Peng L, Hou Z G, Wang W Q. Synchronous active interaction control and its implementation for a rehabilitation robot. Act Autom Sin, 2015, 41: 1837--1846.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Peng L, Hou Z G, Wang W Q. Synchronous active interaction control and its implementation for a rehabilitation robot. Act Autom Sin, 2015, 41: 1837--1846&
[54]
Sun R, Song R, Tong K Y. Complexity analysis of EMG signals for patients after stroke during robot-aided rehabilitation training using fuzzy approximate entropy. IEEE Trans Neural Syst Rehabil Eng, 2014, 22: 1013--1019.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Sun R, Song R, Tong K Y. Complexity analysis of EMG signals for patients after stroke during robot-aided rehabilitation training using fuzzy approximate entropy. IEEE Trans Neural Syst Rehabil Eng, 2014, 22: 1013--1019&
[55]
Peng L, Hou Z G, Peng L, et al. Experimental study of robot-assisted exercise training for knee rehabilitation based on a practical EMG-driven model. In: Proceedings of the 6th IEEE International Conference on Biomedical Robotics and Biomechatronics, UTown, 2016. 810--814.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Peng L, Hou Z G, Peng L, et al. Experimental study of robot-assisted exercise training for knee rehabilitation based on a practical EMG-driven model. In: Proceedings of the 6th IEEE International Conference on Biomedical Robotics and Biomechatronics, UTown, 2016. 810--814&
[56]
Yin Y H, Fan Y J, Xu L D. EMG and EPP-integrated human-machine interface between the paralyzed and rehabilitation exoskeleton. IEEE Trans Inform Technol Biomed, 2012, 16: 542--549.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Yin Y H, Fan Y J, Xu L D. EMG and EPP-integrated human-machine interface between the paralyzed and rehabilitation exoskeleton. IEEE Trans Inform Technol Biomed, 2012, 16: 542--549&
[57]
Mulder T. Motor imagery and action observation: cognitive tools for rehabilitation. J Neural Transm, 2007, 114: 1265--1278.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Mulder T. Motor imagery and action observation: cognitive tools for rehabilitation. J Neural Transm, 2007, 114: 1265--1278&
[58]
Dijkerman H C, Ietswaart M, Johnston M, et al. Does motor imagery training improve hand function in chronic stroke patients? a pilot study. Clin Rehabil, 2004, 18: 538--549.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Dijkerman H C, Ietswaart M, Johnston M, et al. Does motor imagery training improve hand function in chronic stroke patients? a pilot study. Clin Rehabil, 2004, 18: 538--549&
[59]
Wang W, Collinger J L, Perez M A, et al. Neural interface technology for rehabilitation: exploiting and promoting neuroplasticity. Phys Med Rehabil Cli, 2010, 21: 157--178.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Wang W, Collinger J L, Perez M A, et al. Neural interface technology for rehabilitation: exploiting and promoting neuroplasticity. Phys Med Rehabil Cli, 2010, 21: 157--178&
[60]
Xu B, Peng S, Song A, et al. Robot-aided upper-limb rehabilitation based on motor imagery EEG. Int J Adv Robot Syst, 2011, 33: 307--313.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Xu B, Peng S, Song A, et al. Robot-aided upper-limb rehabilitation based on motor imagery EEG. Int J Adv Robot Syst, 2011, 33: 307--313&
[61]
Gomez-Rodriguez M, Grosse-Wentrup M, Hill J, et al. Towards brain-robot interfaces in stroke rehabilitation. In: Proceedings of 2011 IEEE International Conference on Rehabilitation Robotics, Zurich, 2011. 1--6.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Gomez-Rodriguez M, Grosse-Wentrup M, Hill J, et al. Towards brain-robot interfaces in stroke rehabilitation. In: Proceedings of 2011 IEEE International Conference on Rehabilitation Robotics, Zurich, 2011. 1--6&
[62]
Buch E, Weber C, Cohen L G, et al. Think to move: a neuromagnetic brain-computer interface (BCI) system for chronic stroke. Stroke, 2008, 39: 910--917.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Buch E, Weber C, Cohen L G, et al. Think to move: a neuromagnetic brain-computer interface (BCI) system for chronic stroke. Stroke, 2008, 39: 910--917&
[63]
Park W, Kwon G H, Kim D H, et al. Assessment of cognitive engagement in stroke patients from single-trial EEG during motor rehabilitation. IEEE Trans Neural Syst Rehabil Eng, 2015, 23: 351--362.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Park W, Kwon G H, Kim D H, et al. Assessment of cognitive engagement in stroke patients from single-trial EEG during motor rehabilitation. IEEE Trans Neural Syst Rehabil Eng, 2015, 23: 351--362&
[64]
Kalcher J, Flotzinger D, Neuper C, et al. Graz brain-computer enterface II-toward communication between humans and computers based on online classification of three different EEG patterns. Med Biol Eng Comput, 1996, 34: 382--388.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Kalcher J, Flotzinger D, Neuper C, et al. Graz brain-computer enterface II-toward communication between humans and computers based on online classification of three different EEG patterns. Med Biol Eng Comput, 1996, 34: 382--388&
[65]
Onose G, Grozea C, Anghelescu A, et al. On the feasibility of using motor imagery EEG-based brain-computer interface in chronic tetraplegics for assistive robotic arm control: a clinical test and long-term post-trial follow-up. Spinal Cord, 2012, 50: 599--608.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Onose G, Grozea C, Anghelescu A, et al. On the feasibility of using motor imagery EEG-based brain-computer interface in chronic tetraplegics for assistive robotic arm control: a clinical test and long-term post-trial follow-up. Spinal Cord, 2012, 50: 599--608&
[66]
Ma J, Zhang Y, Cichocki A, et al. A novel EOG/EEG hybrid human-machine interface adopting eye movements and ERPs: application to robot control. IEEE Trans Biomed Eng, 2015, 62: 876--889.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Ma J, Zhang Y, Cichocki A, et al. A novel EOG/EEG hybrid human-machine interface adopting eye movements and ERPs: application to robot control. IEEE Trans Biomed Eng, 2015, 62: 876--889&
[67]
Velliste M, Perel S, Spalding M C, et al. Cortical control of a prosthetic arm for self-feeding. Nature, 2008, 453: 1098--1101.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Velliste M, Perel S, Spalding M C, et al. Cortical control of a prosthetic arm for self-feeding. Nature, 2008, 453: 1098--1101&
[68]
Hochberg L R, Daniel B, Beata J, et al. Reach and grasp by people with tetraplegia using a neurally controlled robotic arm. Nature, 2011, 485: 372--375.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Hochberg L R, Daniel B, Beata J, et al. Reach and grasp by people with tetraplegia using a neurally controlled robotic arm. Nature, 2011, 485: 372--375&
[69]
Collinger J L, Wodlinger B, Downey J E, et al. High-performance neuroprosthetic control by an individual with tetraplegia. Lancet, 2013, 381: 557--564.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Collinger J L, Wodlinger B, Downey J E, et al. High-performance neuroprosthetic control by an individual with tetraplegia. Lancet, 2013, 381: 557--564&
[70]
Galan F, Nuttin M, Lew E, et al. A brain-actuated wheelchair: asynchronous and non-invasive brain-computer interfaces for continuous control of robots. Clin Neurophysiol, 2008, 119: 2159--2169.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Galan F, Nuttin M, Lew E, et al. A brain-actuated wheelchair: asynchronous and non-invasive brain-computer interfaces for continuous control of robots. Clin Neurophysiol, 2008, 119: 2159--2169&
[71]
Kam T E, Suk H I, Lee S W. Non-homogeneous spatial filter optimization for electroencephalogram (EEG)-based motor imagery classification. Neurocomputing, 2013, 108: 58--68.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Kam T E, Suk H I, Lee S W. Non-homogeneous spatial filter optimization for electroencephalogram (EEG)-based motor imagery classification. Neurocomputing, 2013, 108: 58--68&
[72]
Doud A J, Lucas J P, Pisansky M T, et al. Continuous three-dimensional control of a virtual helicopter using a motor imagery based brain-computer interface. Plos One, 2011, 6: 1--10.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Doud A J, Lucas J P, Pisansky M T, et al. Continuous three-dimensional control of a virtual helicopter using a motor imagery based brain-computer interface. Plos One, 2011, 6: 1--10&
[73]
Muller-Putz G R, Scherer R, Pfurtscheller G, et al. Temporal coding of brain patterns for direct limb control in humans. Front Neurosci, 2009, 4: 1--10.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Muller-Putz G R, Scherer R, Pfurtscheller G, et al. Temporal coding of brain patterns for direct limb control in humans. Front Neurosci, 2009, 4: 1--10&
[74]
Allison B Z, Jin J, Zhang Y, et al. A four-choice hybrid P300/SSVEP BCI for improved accuracy. Brain-Comput Interface, 2014, 1: 17--26.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Allison B Z, Jin J, Zhang Y, et al. A four-choice hybrid P300/SSVEP BCI for improved accuracy. Brain-Comput Interface, 2014, 1: 17--26&
[75]
Yin E, Zhou Z, Jiang J, et al. A speedy hybrid BCI spelling approach combining P300 and SSVEP. IEEE Trans Biomed Eng, 2013, 61: 473--483.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Yin E, Zhou Z, Jiang J, et al. A speedy hybrid BCI spelling approach combining P300 and SSVEP. IEEE Trans Biomed Eng, 2013, 61: 473--483&
[76]
Li Y, Pan J, Wang F, et al. A hybrid BCI system combining P300 and SSVEP and its application to wheelchair control. IEEE Trans Biomed Eng, 2013, 60: 3156--3166.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Li Y, Pan J, Wang F, et al. A hybrid BCI system combining P300 and SSVEP and its application to wheelchair control. IEEE Trans Biomed Eng, 2013, 60: 3156--3166&
[77]
Yin E, Zeyl T, Saab R, et al. A hybrid brain-computer interface based on the fusion of P300 and SSVEP scores. IEEE Trans Neural Syst Rehabil Eng, 2015, 23: 693--701.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Yin E, Zeyl T, Saab R, et al. A hybrid brain-computer interface based on the fusion of P300 and SSVEP scores. IEEE Trans Neural Syst Rehabil Eng, 2015, 23: 693--701&
[78]
Lew E, Chavarriaga R, Silvoni S, et al. Detection of self-paced reaching movement intention from EEG signals. Front Neuroeng, 2011, 5: 1--17.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Lew E, Chavarriaga R, Silvoni S, et al. Detection of self-paced reaching movement intention from EEG signals. Front Neuroeng, 2011, 5: 1--17&
[79]
Bradberry T J, Gentili R J, Contrerasvidal J L. Fast attainment of computer cursor control with noninvasively acquired brain signals. J Neural Eng, 2011, 8: 292--301.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Bradberry T J, Gentili R J, Contrerasvidal J L. Fast attainment of computer cursor control with noninvasively acquired brain signals. J Neural Eng, 2011, 8: 292--301&
[80]
Presacco A, Goodman R, Forrester L, et al. Neural decoding of treadmill walking from noninvasive electroencephalographic signals. J Neurophysiol, 2011, 106: 1875--1887.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Presacco A, Goodman R, Forrester L, et al. Neural decoding of treadmill walking from noninvasive electroencephalographic signals. J Neurophysiol, 2011, 106: 1875--1887&
[81]
Lv J, Li Y, Gu Z. Decoding hand movement velocity from electroencephalogram signals during a drawing task. Biomed Eng Online, 2010, 9: 1--21.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Lv J, Li Y, Gu Z. Decoding hand movement velocity from electroencephalogram signals during a drawing task. Biomed Eng Online, 2010, 9: 1--21&
[82]
Kim J H, Biessmann F, Lee S W. Decoding three-dimensional trajectory of executed and imagined arm movements from electroencephalogram signals. IEEE Trans Neural Syst Rehabil Eng, 2014, 23: 867--876.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Kim J H, Biessmann F, Lee S W. Decoding three-dimensional trajectory of executed and imagined arm movements from electroencephalogram signals. IEEE Trans Neural Syst Rehabil Eng, 2014, 23: 867--876&
[83]
Nakanishi Y, Yanagisawa T, Shin D, et al. Prediction of three-dimensional arm trajectories based on ECoG signals recorded from human sensorimotor cortex. Plos One, 2013, 8: 1--9.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Nakanishi Y, Yanagisawa T, Shin D, et al. Prediction of three-dimensional arm trajectories based on ECoG signals recorded from human sensorimotor cortex. Plos One, 2013, 8: 1--9&
[84]
Chen Y X. Design and control of FES and biosignal feedback based rehabilitation robot for lower limbs. Dissertation for Ph.D. Degree. Beijing: The University of Chinese Academy of Sciences, 2014.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Chen Y X. Design and control of FES and biosignal feedback based rehabilitation robot for lower limbs. Dissertation for Ph.D. Degree. Beijing: The University of Chinese Academy of Sciences, 2014&
[85]
Zhang X, Xu G, Xie J, et al. An EEG-driven lower limb rehabilitation training system for active and passive co-stimulation. In: Proceedings of the 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Milan, 2015. 4582--4585.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Zhang X, Xu G, Xie J, et al. An EEG-driven lower limb rehabilitation training system for active and passive co-stimulation. In: Proceedings of the 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Milan, 2015. 4582--4585&
[86]
Xiao Z G, Elnady A M, Webb J, et al. Towards a brain computer interface driven exoskeleton for upper extremity rehabilitation. In: Proceedings of the 5th IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics, S$\tilde{a}$o Paulo, 2014. 432--437.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Xiao Z G, Elnady A M, Webb J, et al. Towards a brain computer interface driven exoskeleton for upper extremity rehabilitation. In: Proceedings of the 5th IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics, S$\tilde{a}$o Paulo, 2014. 432--437&
[87]
Sarac M, Koyas E, Erdogan A, et al. Brain computer interface based robotic rehabilitation with online modification of task speed. In: Proceedings of the 2011 IEEE International Conference on Rehabilitation Robotics, Seattle, 2013. 1--7.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Sarac M, Koyas E, Erdogan A, et al. Brain computer interface based robotic rehabilitation with online modification of task speed. In: Proceedings of the 2011 IEEE International Conference on Rehabilitation Robotics, Seattle, 2013. 1--7&
[88]
Meng W, Liu Q, Zhou Z, et al. Recent development of mechanisms and control strategies for robot-assisted lower limb rehabilitation. Mechatronics, 2015, 31: 132--145.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Meng W, Liu Q, Zhou Z, et al. Recent development of mechanisms and control strategies for robot-assisted lower limb rehabilitation. Mechatronics, 2015, 31: 132--145&
[89]
Armstrong-helouvry B, Dupont P, Wit C C D. A survey of models, analysis tools and compensation methods for the control of machines with friction. Automatica, 1994, 30: 1083--1138.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Armstrong-helouvry B, Dupont P, Wit C C D. A survey of models, analysis tools and compensation methods for the control of machines with friction. Automatica, 1994, 30: 1083--1138&
[90]
Wang W Q, Hou Z G, Cheng L, et al. Toward patients motion intention recognition: dynamics modeling and identification of iLeg-an LLRR under motion constraints. IEEE Trans Syst Man Cybern Syst, 2016, 46: 980--992.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Wang W Q, Hou Z G, Cheng L, et al. Toward patients motion intention recognition: dynamics modeling and identification of iLeg-an LLRR under motion constraints. IEEE Trans Syst Man Cybern Syst, 2016, 46: 980--992&
[91]
Wang Q S, Li J T. Friction compensation in cable-conduit transmission system of hand rehabilitation robot. Robot, 2014, 36: 1--7.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Wang Q S, Li J T. Friction compensation in cable-conduit transmission system of hand rehabilitation robot. Robot, 2014, 36: 1--7&
[92]
Wang W Q, Hou Z G, Tong L N, et al. Dynamics modeling and identification of the human-robot interface based on a lower limb rehabilitation robot. In: Proceedings of the 2014 IEEE International Conference on Robotics and Automation, Hong Kong, 2014. 6012--6017.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Wang W Q, Hou Z G, Tong L N, et al. Dynamics modeling and identification of the human-robot interface based on a lower limb rehabilitation robot. In: Proceedings of the 2014 IEEE International Conference on Robotics and Automation, Hong Kong, 2014. 6012--6017&
[93]
Seul J, Hsia T C. Robust neural force control scheme under uncertainties in robot dynamics and unknown environment. IEEE Trans Ind Electron, 2000, 47: 403--412.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Seul J, Hsia T C. Robust neural force control scheme under uncertainties in robot dynamics and unknown environment. IEEE Trans Ind Electron, 2000, 47: 403--412&
[94]
Seul J, Hyun-Taek C, Hsia T C. Neural network control for position tracking of a two-axis inverted pendulum system: experimental studies. IEEE Trans Neural Netw, 2007, 18: 1042--1048.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Seul J, Hyun-Taek C, Hsia T C. Neural network control for position tracking of a two-axis inverted pendulum system: experimental studies. IEEE Trans Neural Netw, 2007, 18: 1042--1048&
[95]
Seul J, Hsia T C. Neural network impedance force control of robot manipulator. IEEE Trans Ind Electron, 1998, 45: 451--461.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Seul J, Hsia T C. Neural network impedance force control of robot manipulator. IEEE Trans Ind Electron, 1998, 45: 451--461&
[96]
Cheng L, Hou Z G, Tan M. Adaptive neural network tracking control for manipulators with uncertain kinematics, dynamics and actuator model. Automatic, 2009, 45: 2312--2318.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Cheng L, Hou Z G, Tan M. Adaptive neural network tracking control for manipulators with uncertain kinematics, dynamics and actuator model. Automatic, 2009, 45: 2312--2318&
[97]
Singh Y, Vinoth V, Kiran Y R, et al. Inverse dynamic sand control of a 3-DOF planar parallel (U-shaped 3-PPR) manipulator. Robot Comput Integr Manuf, 2015, 34: 164--179.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Singh Y, Vinoth V, Kiran Y R, et al. Inverse dynamic sand control of a 3-DOF planar parallel (U-shaped 3-PPR) manipulator. Robot Comput Integr Manuf, 2015, 34: 164--179&
[98]
Aguirre-Ollinger G, Colgate J E, Peshkin M A, et al. Inertia compensation control of a one-degree-of-freedom exoskeleton for lower-limb assistance: initial experiments. IEEE Trans Neural Syst Rehabil Eng, 2012, 20: 68--77.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Aguirre-Ollinger G, Colgate J E, Peshkin M A, et al. Inertia compensation control of a one-degree-of-freedom exoskeleton for lower-limb assistance: initial experiments. IEEE Trans Neural Syst Rehabil Eng, 2012, 20: 68--77&
[99]
Duschau-Wicke A, Von Zitzewitz J, Caprez A, et al. Path control: a method for patient-cooperative robot-aided gait rehabilitation. IEEE Trans Neural Syst Rehabil Eng, 2010, 18: 38--48.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Duschau-Wicke A, Von Zitzewitz J, Caprez A, et al. Path control: a method for patient-cooperative robot-aided gait rehabilitation. IEEE Trans Neural Syst Rehabil Eng, 2010, 18: 38--48&
[100]
Riener R, Nef T, Colombo G. Robot-aided neurorehabilitation of the upper extremities. Med Biol Eng Comput, 2005, 43: 2--10.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Riener R, Nef T, Colombo G. Robot-aided neurorehabilitation of the upper extremities. Med Biol Eng Comput, 2005, 43: 2--10&
[101]
Cai L L, Fong A J, Liang Y, et al. Assist-as-needed training paradigms for robotic rehabilitation of spinal cord injuries. In: Proceedings of the 2006 IEEE International Conference on Robotics and Automation, Orlando, 2006. 3504--3511.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Cai L L, Fong A J, Liang Y, et al. Assist-as-needed training paradigms for robotic rehabilitation of spinal cord injuries. In: Proceedings of the 2006 IEEE International Conference on Robotics and Automation, Orlando, 2006. 3504--3511&
[102]
Hu J, Hou Z G, Zhang F, et al. Training strategies for a lower limb rehabilitation robot based on impedance control. In: Proceedings of the 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, S$\tilde{a}$n Diego, 2012. 6032--6035.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Hu J, Hou Z G, Zhang F, et al. Training strategies for a lower limb rehabilitation robot based on impedance control. In: Proceedings of the 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, S$\tilde{a}$n Diego, 2012. 6032--6035&
[103]
He W, Ge S S, Li Y, et al. Neural network control of a rehabilitation robot by state and output feedback. J Intell Robot Syst, 2015, 80: 15--31.
Google Scholar
http://scholar.google.com/scholar_lookup?title=He W, Ge S S, Li Y, et al. Neural network control of a rehabilitation robot by state and output feedback. J Intell Robot Syst, 2015, 80: 15--31&
[104]
Napper S A, Seaman R L. Applications of robots in rehabilitation. Robot Auton Syst, 1989, 5: 227--239.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Napper S A, Seaman R L. Applications of robots in rehabilitation. Robot Auton Syst, 1989, 5: 227--239&
[105]
Hogan N. Impedance control: an approach to manipulation. J Dyn Syst Meas Control, 1985, 107: 1--24.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Hogan N. Impedance control: an approach to manipulation. J Dyn Syst Meas Control, 1985, 107: 1--24&
[106]
Jezernik S, Colombo G, Morari M. Automatic gait-pattern adaptation algorithms for rehabilitation with a 4-DOF robotic orthosis. IEEE Trans Robot Autom, 2004, 20: 574--582.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Jezernik S, Colombo G, Morari M. Automatic gait-pattern adaptation algorithms for rehabilitation with a 4-DOF robotic orthosis. IEEE Trans Robot Autom, 2004, 20: 574--582&
[107]
Tsoi Y, Xie S. Impedance control of ankle rehabilitation robot. In: Proceedings of the 2008 IEEE International Conference on Robotics and Biomimetics, Guilin, 2008. 840--845.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Tsoi Y, Xie S. Impedance control of ankle rehabilitation robot. In: Proceedings of the 2008 IEEE International Conference on Robotics and Biomimetics, Guilin, 2008. 840--845&
[108]
Wen Z, Qian J W, Shen L Y, et al. Trajectory adaption for impedance control based walking rehabilitation training robot. Robot, 2011, 33: 142--149.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Wen Z, Qian J W, Shen L Y, et al. Trajectory adaption for impedance control based walking rehabilitation training robot. Robot, 2011, 33: 142--149&
[109]
Riener R, Lunenburger L, Jezernik S, et al. Patient-cooperative strategies for robot-aided treadmill training: first experimental results. IEEE Trans Neural Syst Rehabil Eng, 2005, 13: 380--394.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Riener R, Lunenburger L, Jezernik S, et al. Patient-cooperative strategies for robot-aided treadmill training: first experimental results. IEEE Trans Neural Syst Rehabil Eng, 2005, 13: 380--394&
[110]
Ficuciello F, Villani L, Siciliano B. Variable impedance control of redundant manipulators for intuitive human-robot physical interaction. IEEE Trans Robot, 2015, 31: 850--863.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Ficuciello F, Villani L, Siciliano B. Variable impedance control of redundant manipulators for intuitive human-robot physical interaction. IEEE Trans Robot, 2015, 31: 850--863&
[111]
Ficuciello F, Romano A, Villani L, et al. Cartesian impedance control of redundant manipulators for human-robot co-manipulation. In: Proceedings of the 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, Chicago, 2014. 2020--2125.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Ficuciello F, Romano A, Villani L, et al. Cartesian impedance control of redundant manipulators for human-robot co-manipulation. In: Proceedings of the 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, Chicago, 2014. 2020--2125&
[112]
Kordasz M, Kuczkowski K, Sauer P. Study on possible control algorithms for lower limb rehabilitation system. In: Proceedings of 2011 IEEE International Conference on Rehabilitation Robotics, Zurich, 2011. 1--6.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Kordasz M, Kuczkowski K, Sauer P. Study on possible control algorithms for lower limb rehabilitation system. In: Proceedings of 2011 IEEE International Conference on Rehabilitation Robotics, Zurich, 2011. 1--6&
[113]
Tsoi Y H, Xie S Q. Design and control of a parallel robot for ankle rehabilitation. In: Proceedings of the 15th International Conference on Mechatronics and Machine Vision in Practice, Auckland, 2008. 515--520.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Tsoi Y H, Xie S Q. Design and control of a parallel robot for ankle rehabilitation. In: Proceedings of the 15th International Conference on Mechatronics and Machine Vision in Practice, Auckland, 2008. 515--520&
[114]
Yoon J, Ryu J, Lim K B. Reconfigurable ankle rehabilitation robot for various exercises. J Robot Syst, 2006, 22: 15--33.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Yoon J, Ryu J, Lim K B. Reconfigurable ankle rehabilitation robot for various exercises. J Robot Syst, 2006, 22: 15--33&
[115]
Mirzaei A, Ozgoli S. A new impedance control structure for leg rehabilitation robot. In: Proceedings of the 2nd International Conference on Control, Instrumentation and Automation, Shiraz, 2011. 952--956.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Mirzaei A, Ozgoli S. A new impedance control structure for leg rehabilitation robot. In: Proceedings of the 2nd International Conference on Control, Instrumentation and Automation, Shiraz, 2011. 952--956&
[116]
Lawson B E, Varol H A, Huff A, et al. Control of stair ascent and descent with a powered transfemoral prosthesis. IEEE Trans Neural Syst Rehabil Eng, 2013, 21: 466--473.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Lawson B E, Varol H A, Huff A, et al. Control of stair ascent and descent with a powered transfemoral prosthesis. IEEE Trans Neural Syst Rehabil Eng, 2013, 21: 466--473&
[117]
Gregg R D, Lenzi T, Hargrove L J, et al. Virtual constraint control of a powered prosthetic leg: from simulation to experiments with transfemoral amputees. IEEE Trans Robot, 2014, 30: 1455--1471.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Gregg R D, Lenzi T, Hargrove L J, et al. Virtual constraint control of a powered prosthetic leg: from simulation to experiments with transfemoral amputees. IEEE Trans Robot, 2014, 30: 1455--1471&
[118]
Lawson B E, Ruhe B, Shultz A, et al. A powered prosthetic intervention for bilateral transfemoral amputees. IEEE Trans Biomed Eng, 2015, 62: 1042--1050.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Lawson B E, Ruhe B, Shultz A, et al. A powered prosthetic intervention for bilateral transfemoral amputees. IEEE Trans Biomed Eng, 2015, 62: 1042--1050&
[119]
Akdougan E, Taçgin E, Adli M A. Knee rehabilitation using an intelligent robotic system. J Intell Manuf, 2009, 20: 195--202.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Akdougan E, Taçgin E, Adli M A. Knee rehabilitation using an intelligent robotic system. J Intell Manuf, 2009, 20: 195--202&
[120]
Mendoza M, Bonilla I, Gonzalez-Galvan E, et al. Impedance control in a wave-based teleoperator for rehabilitation motor therapies assisted by robots. Comput Meth Prog Bio, 2016, 123: 54--67.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Mendoza M, Bonilla I, Gonzalez-Galvan E, et al. Impedance control in a wave-based teleoperator for rehabilitation motor therapies assisted by robots. Comput Meth Prog Bio, 2016, 123: 54--67&
[121]
Liu M, Zhang F, Datseris P, et al. Improving finite state impedance control of active-transfemoral prosthesis using dempster-shafer based state transition rules. J Intell Robot Syst, 2014, 76: 461--474.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Liu M, Zhang F, Datseris P, et al. Improving finite state impedance control of active-transfemoral prosthesis using dempster-shafer based state transition rules. J Intell Robot Syst, 2014, 76: 461--474&
[122]
Huang H, Crouch D L, Liu M, et al. A cyber expert system for auto-tuning powered prosthesis impedance control parameters. Ann Biomed Eng, 2015: 1--12.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Huang H, Crouch D L, Liu M, et al. A cyber expert system for auto-tuning powered prosthesis impedance control parameters. Ann Biomed Eng, 2015: 1--12&
[123]
Wang D, Liu M, Zhang F, et al. Design of an expert system to automatically calibrate impedance control for powered knee prostheses. In: Proceedings of the 13th International Conference on Rehabilitation Robotics, Seattle, 2013. 1--5.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Wang D, Liu M, Zhang F, et al. Design of an expert system to automatically calibrate impedance control for powered knee prostheses. In: Proceedings of the 13th International Conference on Rehabilitation Robotics, Seattle, 2013. 1--5&
[124]
Ragnarsson K T. Functional electrical stimulation after spinal cord injury: current use, therapeutic effects and future directions. Spinal Cord, 2008, 46: 255--274.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Ragnarsson K T. Functional electrical stimulation after spinal cord injury: current use, therapeutic effects and future directions. Spinal Cord, 2008, 46: 255--274&
[125]
Martin R, Sadowsky C, Obst K, et al. Functional electrical stimulation in spinal cord injury: from theory to practice. Top Spinal Cord Injury Rehabil, 2011, 18: 28--33.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Martin R, Sadowsky C, Obst K, et al. Functional electrical stimulation in spinal cord injury: from theory to practice. Top Spinal Cord Injury Rehabil, 2011, 18: 28--33&
[126]
Glinsky J, Harvey L, Es P V. Efficacy of electrical stimulation to increase muscle strength in people with neurological conditions: a systematic review. Physiother Res Int, 2007, 12: 175--194.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Glinsky J, Harvey L, Es P V. Efficacy of electrical stimulation to increase muscle strength in people with neurological conditions: a systematic review. Physiother Res Int, 2007, 12: 175--194&
[127]
Qiu S, Yi W, Xu J, et al. Event-related beta EEG changes during active, passive movement and functional electrical stimulation of the lower limb. IEEE Trans Neural Syst Rehabil Eng, 2015, 24: 283--290.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Qiu S, Yi W, Xu J, et al. Event-related beta EEG changes during active, passive movement and functional electrical stimulation of the lower limb. IEEE Trans Neural Syst Rehabil Eng, 2015, 24: 283--290&
[128]
Jr G D, Dolbow D, Tsui B, et al. Functional electrical stimulation therapies after spinal cord injury. Neurorehabilitation, 2011, 28: 231--248.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Jr G D, Dolbow D, Tsui B, et al. Functional electrical stimulation therapies after spinal cord injury. Neurorehabilitation, 2011, 28: 231--248&
[129]
Ward N S, Brown M M, Thompson A J, et al. Neural correlates of motor recovery after stroke: a longitudinal fMRI study. Brain, 2003, 126: 2476--2496.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Ward N S, Brown M M, Thompson A J, et al. Neural correlates of motor recovery after stroke: a longitudinal fMRI study. Brain, 2003, 126: 2476--2496&
[130]
Rushton D N. Functional electrical stimulation and rehabilitation-an hypothesis. Med Eng Phys, 2003, 25: 75--78.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Rushton D N. Functional electrical stimulation and rehabilitation-an hypothesis. Med Eng Phys, 2003, 25: 75--78&
[131]
Freeman C T, Hughes A M, Burridge J H, et al. Iterative learning control of FES applied to the upper extremity for rehabilitation. Control Eng Pract, 2009, 17: 368--381.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Freeman C T, Hughes A M, Burridge J H, et al. Iterative learning control of FES applied to the upper extremity for rehabilitation. Control Eng Pract, 2009, 17: 368--381&
[132]
Qi H Z, Xu J P, Qiu S, et al. EEG analysis of changes in brain induced by leg related movement with FES. Nanotechnol Precis Eng, 2015, 5: 339--345.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Qi H Z, Xu J P, Qiu S, et al. EEG analysis of changes in brain induced by leg related movement with FES. Nanotechnol Precis Eng, 2015, 5: 339--345&
[133]
Hunt K J, Stone B, Negard N O, et al. Control strategies for integration of electric motor assist and functional electrical stimulation in paraplegic cycling: utility for exercise testing and mobile cycling. IEEE Trans Neural Syst Rehabil Eng, 2004, 12: 89--101.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Hunt K J, Stone B, Negard N O, et al. Control strategies for integration of electric motor assist and functional electrical stimulation in paraplegic cycling: utility for exercise testing and mobile cycling. IEEE Trans Neural Syst Rehabil Eng, 2004, 12: 89--101&
[134]
Bellman M J, Cheng T H, Downey R J, et al. Stationary cycling induced by switched functional electrical stimulation control. In: Proceedings of the 2014 American Control Conference, Oregon, 2014. 4802--4809.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Bellman M J, Cheng T H, Downey R J, et al. Stationary cycling induced by switched functional electrical stimulation control. In: Proceedings of the 2014 American Control Conference, Oregon, 2014. 4802--4809&
[135]
Metrailler P, Blanchard V, Perrin I, et al. Improvement of rehabilitation possibilities with the MotionMaker TM. In: Proceedings of the 1st IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics, Pisa, 2006. 359--364.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Metrailler P, Blanchard V, Perrin I, et al. Improvement of rehabilitation possibilities with the MotionMaker TM. In: Proceedings of the 1st IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics, Pisa, 2006. 359--364&
[136]
Farhoud A, Erfanian A. Fully automatic control of paraplegic FES pedaling using higher-order sliding mode and fuzzylogic control. IEEE Trans Neural Syst Rehabil Eng, 2014, 22: 533--542.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Farhoud A, Erfanian A. Fully automatic control of paraplegic FES pedaling using higher-order sliding mode and fuzzylogic control. IEEE Trans Neural Syst Rehabil Eng, 2014, 22: 533--542&
[137]
Alibeji N, Kirsch N, Farrokhi S, et al. Further fesults on predictor-based control of neuromuscular electrical stimulation. IEEE Trans Neural Syst Rehabil Eng, 2015, 23: 1095--1105.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Alibeji N, Kirsch N, Farrokhi S, et al. Further fesults on predictor-based control of neuromuscular electrical stimulation. IEEE Trans Neural Syst Rehabil Eng, 2015, 23: 1095--1105&
[138]
Sampson P, Freeman C, Coote S, et al. Using functional electrical stimulation mediated by iterative learning control and robotics to improve arm movement for people with multiple sclerosis. IEEE Trans Neural Syst Rehabil Eng, 2016, 24: 235--247.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Sampson P, Freeman C, Coote S, et al. Using functional electrical stimulation mediated by iterative learning control and robotics to improve arm movement for people with multiple sclerosis. IEEE Trans Neural Syst Rehabil Eng, 2016, 24: 235--247&
[139]
Meadmore K L, Hughes A M, Freeman C T, et al. Functional electrical stimulation mediated by iterative learning control and 3D robotics reduces motor impairment in chronic stroke. J Neuroeng Rehabil, 2012, 32: 1--11.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Meadmore K L, Hughes A M, Freeman C T, et al. Functional electrical stimulation mediated by iterative learning control and 3D robotics reduces motor impairment in chronic stroke. J Neuroeng Rehabil, 2012, 32: 1--11&
[140]
Oboe R, Pilastro D. Stability analysis of a non-linear adaptive impedance controller for rehabilitation purposes. In: Proceedings of 2015 IEEE International Conference on Mechatronics, Nagoya, 2015. 454--459.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Oboe R, Pilastro D. Stability analysis of a non-linear adaptive impedance controller for rehabilitation purposes. In: Proceedings of 2015 IEEE International Conference on Mechatronics, Nagoya, 2015. 454--459&
[141]
Zhang J J, Chien C C. Passivity and stability of human-robot interaction control for upper-limb rehabilitation robots. IEEE Trans Robot, 2015, 31: 233--245.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Zhang J J, Chien C C. Passivity and stability of human-robot interaction control for upper-limb rehabilitation robots. IEEE Trans Robot, 2015, 31: 233--245&
[142]
Zhang J J, Chien C C, Steven H. Stable human-robot interaction control for upper-limb rehabilitation robotics. In: Proceedings of the 2013 IEEE International Conference on Robotics and Automation, Karlsruhe, 2013. 2201--2206.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Zhang J J, Chien C C, Steven H. Stable human-robot interaction control for upper-limb rehabilitation robotics. In: Proceedings of the 2013 IEEE International Conference on Robotics and Automation, Karlsruhe, 2013. 2201--2206&
[143]
Yu H Y, Huang S N, Chen G, et al. Human-robot interaction control of rehabilitation robots with series elastic actuators. IEEE Trans Robot, 2015, 31: 1089--1100.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Yu H Y, Huang S N, Chen G, et al. Human-robot interaction control of rehabilitation robots with series elastic actuators. IEEE Trans Robot, 2015, 31: 1089--1100&
[144]
Chawda V, OMalley M K. Position synchronization inbilateral teleoperation under time-varying communication delays communication delays. IEEE/ASME Trans Mech, 2015, 20: 245--253.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Chawda V, OMalley M K. Position synchronization inbilateral teleoperation under time-varying communication delays communication delays. IEEE/ASME Trans Mech, 2015, 20: 245--253&
[145]
Li J, Tavakoli M, Mendez V, et al. Passivity and absolute stability analyses of trilateral haptic collaborative systems. J Intell Robot Syst, 2015, 78: 3--20.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Li J, Tavakoli M, Mendez V, et al. Passivity and absolute stability analyses of trilateral haptic collaborative systems. J Intell Robot Syst, 2015, 78: 3--20&
[146]
Oboe R, Pilastro D. Non-linear adaptive impedance controller for rehabilitation purposes. In: Proceedings of the 13th International Workshop on Advanced Motion Control, Yokohama, 2014. 272--277.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Oboe R, Pilastro D. Non-linear adaptive impedance controller for rehabilitation purposes. In: Proceedings of the 13th International Workshop on Advanced Motion Control, Yokohama, 2014. 272--277&
[147]
Kashiri N, Lee J, Tsagarakis N G, et al. Proxy-based position control of manipulators with passive compliant actuators: stability analysis and experiments. Robot Auton Syst, 2016, 75: 398--408.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Kashiri N, Lee J, Tsagarakis N G, et al. Proxy-based position control of manipulators with passive compliant actuators: stability analysis and experiments. Robot Auton Syst, 2016, 75: 398--408&
[148]
Santis A D, Siciliano B, Luca A D, et al. An atlas of physical human-robot interaction. Mech Mach Theory, 2008, 43: 253--270.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Santis A D, Siciliano B, Luca A D, et al. An atlas of physical human-robot interaction. Mech Mach Theory, 2008, 43: 253--270&
[149]
Xu W K, Cai C X, Zou Y. Adaptive motion control of arm rehabilitation robot based on impedance identification. Nonlinear Dynam, 2015, 79: 1099--1114.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Xu W K, Cai C X, Zou Y. Adaptive motion control of arm rehabilitation robot based on impedance identification. Nonlinear Dynam, 2015, 79: 1099--1114&
[150]
Jimenez-Fabian R, Verlinden O. Review of control algorithms for robotic ankle systems in lower-limb orthoses, prostheses, and exoskeletons. Med Eng Phys, 2012, 34: 397--408.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Jimenez-Fabian R, Verlinden O. Review of control algorithms for robotic ankle systems in lower-limb orthoses, prostheses, and exoskeletons. Med Eng Phys, 2012, 34: 397--408&
[151]
McCool P, Fraser G D, Chan A D C, et al. Identification of contaminant type in surface electromyography (EMG) signals. IEEE Trans Neural Syst Rehabil Eng, 2014, 22: 774--783.
Google Scholar
http://scholar.google.com/scholar_lookup?title=McCool P, Fraser G D, Chan A D C, et al. Identification of contaminant type in surface electromyography (EMG) signals. IEEE Trans Neural Syst Rehabil Eng, 2014, 22: 774--783&
[152]
Disselhorst-Klug C, Schmitz-Rode T, Rau G. Surface electromyography and muscle force: limits in sEMG-force relationship and new approaches for applications. Clin Biomech, 2009, 24: 225--235.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Disselhorst-Klug C, Schmitz-Rode T, Rau G. Surface electromyography and muscle force: limits in sEMG-force relationship and new approaches for applications. Clin Biomech, 2009, 24: 225--235&
[153]
Abser N, MacIsaac D, Fraser G, et al. CleanEMG: quantifying power line interference in surface EMG signals. In: Proceedings of the 34th Conference Canadian Medical and Biological Engineering Society and Festival of International Conferences on Caregiving, Disability, Aging and Technology, Toronto, 2011. 1--4.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Abser N, MacIsaac D, Fraser G, et al. CleanEMG: quantifying power line interference in surface EMG signals. In: Proceedings of the 34th Conference Canadian Medical and Biological Engineering Society and Festival of International Conferences on Caregiving, Disability, Aging and Technology, Toronto, 2011. 1--4&
[154]
Abser N, MacIsaac D, Chan A D C, et al. CleanEMG: comparing interpolation strategies for power line interference quantification in surface EMG signals. In: Proceedings of the 35th Conference Canadian Medical and Biological Engineering Society, Halifax, 2012.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Abser N, MacIsaac D, Chan A D C, et al. CleanEMG: comparing interpolation strategies for power line interference quantification in surface EMG signals. In: Proceedings of the 35th Conference Canadian Medical and Biological Engineering Society, Halifax, 2012&
[155]
Fraser G D, Chan A D C, Green J R, et al. Detection of ADC clipping, quantization noise, and amplifier saturation in surface electromyography. In: proceedings of IEEE International Symposium on Medical Measurements and Applications, Budapest, 2012. 162--166.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Fraser G D, Chan A D C, Green J R, et al. Detection of ADC clipping, quantization noise, and amplifier saturation in surface electromyography. In: proceedings of IEEE International Symposium on Medical Measurements and Applications, Budapest, 2012. 162--166&
[156]
Vodovnik L, Crochetiere W, Reswick J. Control of a skeletal joint by electrical stimulation of antagonists. Med Biol Eng, 1967, 5: 97--109.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Vodovnik L, Crochetiere W, Reswick J. Control of a skeletal joint by electrical stimulation of antagonists. Med Biol Eng, 1967, 5: 97--109&
[157]
Jezernik S, Wassink R G, Keller T. Sliding mode closed-loop control of FES controlling the shank movement. IEEE Trans Biomed Eng, 2004, 51: 263--272.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Jezernik S, Wassink R G, Keller T. Sliding mode closed-loop control of FES controlling the shank movement. IEEE Trans Biomed Eng, 2004, 51: 263--272&
[158]
Hunt K, Jaime R, Gollee H. Robust control of electrically-stimulated muscle using polynomial H-infinity design. Control Eng Pract, 2001, 9: 313--328.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Hunt K, Jaime R, Gollee H. Robust control of electrically-stimulated muscle using polynomial H-infinity design. Control Eng Pract, 2001, 9: 313--328&
[159]
Kroon J R D, Lee J H V D, IJzerman M J, et al. Therapeutic electrical stimulation to improve motor control and functional abilities of the upper extremity after stroke: a systematic review. Clin Rehabil, 2002, 16: 350--360.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Kroon J R D, Lee J H V D, IJzerman M J, et al. Therapeutic electrical stimulation to improve motor control and functional abilities of the upper extremity after stroke: a systematic review. Clin Rehabil, 2002, 16: 350--360&
[160]
Burridge J H, Ladouceur M. Clinical and therapeutic applications of neuromuscular stimulation: a review of current use and speculation into future developments. Neuromodulation, 2001, 4: 147--154.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Burridge J H, Ladouceur M. Clinical and therapeutic applications of neuromuscular stimulation: a review of current use and speculation into future developments. Neuromodulation, 2001, 4: 147--154&
[161]
Schmidt R A, Lee T D. Motor Learning in Motor Control and Learning: a Behavioral Emphasis. 3rd ed. Champaign: Human Kinetics, 1999. 261--285.
Google Scholar
http://scholar.google.com/scholar_lookup?title=Schmidt R A, Lee T D. Motor Learning in Motor Control and Learning: a Behavioral Emphasis. 3rd ed. Champaign: Human Kinetics, 1999. 261--285&