A full upper limb robotic exoskeleton for reaching and grasping rehabilitation triggered by MI-BCI

In this paper we propose a full upper limb exoskeleton for motor rehabilitation of reaching, grasping and releasing in post-stroke patients. The presented system takes into account the hand pre-shaping for object affordability and it is driven by patient's intentional control through a self-paced asynchronous Motor Imagery based Brain Computer Interface (MI-BCI). The developed antropomorphic eight DoFs exoskeleton (two DoFs for the hand, two for the wrist and four for the arm) allows full support of the manipulation activity at the level of single upper limb joint. In this study, we show the feasibility of the proposed system through experimental rehabilitation sessions conducted with three chronic post-stroke patients. Results show the potential of the proposed system for being introduced in a rehabilitation protocol.

[1]  N. Hogan.  An organizing principle for a class of voluntary movements , 1984, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[2]  F. L. D. Silva,et al.  Event-related EEG/MEG synchronization and desynchronization: basic principles , 1999, Clinical Neurophysiology.

[3]  Takashi Maeno,et al.  Multi-fingered exoskeleton haptic device using passive force feedback for dexterous teleoperation , 2002, IEEE/RSJ International Conference on Intelligent Robots and Systems.

[4]  Arnaud Delorme,et al.  EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis , 2004, Journal of Neuroscience Methods.

[5]  R. Riener,et al.  ARMin - design of a novel arm rehabilitation robot , 2005, 9th International Conference on Rehabilitation Robotics, 2005. ICORR 2005..

[6]  Antonio Frisoli,et al.  A new force-feedback arm exoskeleton for haptic interaction in virtual environments , 2005, First Joint Eurohaptics Conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems. World Haptics Conference.

[7]  D.J. Reinkensmeyer,et al.  Automating Arm Movement Training Following Severe Stroke: Functional Exercises With Quantitative Feedback in a Gravity-Reduced Environment , 2006, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[8]  H.I. Krebs,et al.  Design and Characterization of Hand Module for Whole-Arm Rehabilitation Following Stroke , 2007, IEEE/ASME Transactions on Mechatronics.

[9]  M. Bergamasco,et al.  Arm rehabilitation with a robotic exoskeleleton in Virtual Reality , 2007, 2007 IEEE 10th International Conference on Rehabilitation Robotics.

[10]  J. Wolpaw,et al.  Brain–computer interfaces in neurological rehabilitation , 2008, The Lancet Neurology.

[11]  Christa Neuper,et al.  Rehabilitation with Brain-Computer Interface Systems , 2008, Computer.

[12]  Cuntai Guan,et al.  A clinical study of motor imagery-based brain-computer interface for upper limb robotic rehabilitation , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[13]  Hyung-Soon Park,et al.  Developing a whole-arm exoskeleton robot with hand opening and closing mechanism for upper limb stroke rehabilitation , 2009, 2009 IEEE International Conference on Rehabilitation Robotics.

[14]  Massimo Bergamasco,et al.  Mechanical design of a novel Hand Exoskeleton for accurate force displaying , 2009, 2009 IEEE International Conference on Robotics and Automation.

[15]  Antonio Frisoli,et al.  A force-feedback exoskeleton for upper-limb rehabilitation in virtual reality , 2009 .

[16]  Cuntai Guan,et al.  Clinical study of neurorehabilitation in stroke using EEG-based motor imagery brain-computer interface with robotic feedback , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.

[17]  Nikolaos G. Tsagarakis,et al.  A multi-DOF robotic exoskeleton interface for hand motion assistance , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[18]  Antonio Frisoli,et al.  Preliminary results of BRAVO project: Brain computer interfaces for Robotic enhanced Action in Visuo-motOr tasks , 2011, 2011 IEEE International Conference on Rehabilitation Robotics.

[19]  Arnaud Delorme,et al.  Single-Trial Normalization for Event-Related Spectral Decomposition Reduces Sensitivity to Noisy Trials , 2011, Front. Psychology.

[20]  M. Bergamasco,et al.  Positive effects of robotic exoskeleton training of upper limb reaching movements after stroke , 2012, Journal of NeuroEngineering and Rehabilitation.

[21]  M. Bergamasco,et al.  A comparison of algorithms for motor imagery for BCI under different sensory feedback conditions , 2012, 2012 4th IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob).

[22]  Antonio Frisoli,et al.  An emg-based robotic hand exoskeleton for bilateral training of grasp , 2013, 2013 World Haptics Conference (WHC).

[23]  L. Cohen,et al.  Brain–machine interface in chronic stroke rehabilitation: A controlled study , 2013, Annals of neurology.

[24]  Antonio Frisoli,et al.  A new bounded jerk on-line trajectory planning for mimicking human movements in robot-aided neurorehabilitation , 2013, Robotics Auton. Syst..

[25]  Vincenzo Parenti Castelli,et al.  Design of a New Hand Exoskeleton for Rehabilitation of Post- Stroke Patients , 2013 .

[26]  Brittany M. Young,et al.  Changes in functional connectivity correlate with behavioral gains in stroke patients after therapy using a brain-computer interface device , 2014, Front. Neuroeng..

[27]  Antonio Frisoli,et al.  A neuromusculoskeletal model of the human upper limb for a myoelectric exoskeleton control using a reduced number of muscles , 2015, 2015 IEEE World Haptics Conference (WHC).

[28]  A. Kottink,et al.  The Effect of Arm Support Combined With Rehabilitation Games on Upper-Extremity Function in Subacute Stroke , 2015, Neurorehabilitation and neural repair.

[29]  Antonio Frisoli,et al.  An EMG-Controlled Robotic Hand Exoskeleton for Bilateral Rehabilitation , 2015, IEEE Transactions on Haptics.