Development of efficient brain computer interface (BCI) system for stroke rehabilitation

This is an extended abstract describing the doctoral research on mentioned topic which is only to discuss the research in Ph.D symposium at INMIC 2014 conference. Proposed research and material presented in this extended abstract was also presented in the doctoral consortium at IMTIC 2013 at MUET, Pakistan and WEC 2013 conference at NUST Islamabad, Pakistan. This article is not intended to be published as conference paper in the conference proceedings.

[1]  S. Adamovich,et al.  Analysis of a commercial EEG device for the control of a robot arm , 2010, Proceedings of the 2010 IEEE 36th Annual Northeast Bioengineering Conference (NEBEC).

[2]  Abbas Erfanian,et al.  An online EEG-based brain-computer interface for controlling hand grasp using an adaptive probabilistic neural network. , 2010, Medical engineering & physics.

[3]  Dario Farina,et al.  Detection of movement-related cortical potentials based on subject-independent training , 2013, Medical & Biological Engineering & Computing.

[4]  Dandan Huang,et al.  Towards a user-friendly brain–computer interface: Initial tests in ALS and PLS patients , 2010, Clinical Neurophysiology.

[5]  Bo Yu,et al.  Memory efficient on-line streaming for multichannel spike train analysis , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[6]  Ali Bahramisharif,et al.  Brain-computer interfacing using modulations of alpha activity induced by covert shifts of attention , 2011, Journal of NeuroEngineering and Rehabilitation.

[7]  A. K. Platonov,et al.  Principles of neurorehabilitation based on the brain-computer interface and biologically adequate control of the exoskeleton , 2013, Human Physiology.

[8]  Fan Zhou,et al.  Field-programmable gate array implementation of a probabilistic neural network for motor cortical decoding in rats , 2010, Journal of Neuroscience Methods.

[9]  Hubert Cecotti,et al.  A Self-Paced and Calibration-Less SSVEP-Based Brain–Computer Interface Speller , 2010, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[10]  J. Zygierewicz,et al.  Asynchronous BCI Based on Motor Imagery With Automated Calibration and Neurofeedback Training , 2012, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[11]  Bo Yu,et al.  Real-time neuronal networks reconstruction using hierarchical systolic arrays , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[12]  B. Hameed,et al.  Stroke in Pakistan. , 2008, JPMA. The Journal of the Pakistan Medical Association.

[13]  Guest Editorial: From neuroscience to neuro-rehabilitation: transferring basic neuroscientific principles from laboratory to bedside , 2013, Journal of NeuroEngineering and Rehabilitation.

[14]  S. A. Bamford,et al.  A VLSI Field-Programmable Mixed-Signal Array to Perform Neural Signal Processing and Neural Modeling in a Prosthetic System , 2012, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[15]  M. Bergamasco,et al.  A New Gaze-BCI-Driven Control of an Upper Limb Exoskeleton for Rehabilitation in Real-World Tasks , 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[16]  Eric Leuthardt,et al.  An EEG-based brain computer interface for rehabilitation and restoration of hand control following stroke using ipsilateral cortical physiology , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[17]  An H. Do,et al.  Brain-Computer Interface Controlled Functional Electrical Stimulation System for Ankle Movement , 2011, Journal of NeuroEngineering and Rehabilitation.

[18]  P. F. M. J. Verschure,et al.  Using a Hybrid Brain Computer Interface and Virtual Reality System to Monitor and Promote Cortical Reorganization through Motor Activity and Motor Imagery Training , 2013, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[19]  E. E. Fetz,et al.  Interfacing With the Computational Brain , 2011, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[20]  Girijesh Prasad,et al.  Sensorimotor learning with stereo auditory feedback for a brain–computer interface , 2012, Medical & Biological Engineering & Computing.

[21]  Michelle J. Johnson,et al.  Advances in upper limb stroke rehabilitation: a technology push , 2011, Medical & Biological Engineering & Computing.

[22]  From neuroscience to neurorehabilitation : transferring basic neuroscientific principles from laboratory to bedside , 2013 .

[23]  Michael J. Black,et al.  Point-and-Click Cursor Control With an Intracortical Neural Interface System by Humans With Tetraplegia , 2011, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[24]  G. Pfurtscheller,et al.  An SSVEP BCI to Control a Hand Orthosis for Persons With Tetraplegia , 2011, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[25]  Pooja Gupta,et al.  Development of an FPGA-based real-time P300 speller , 2012, 22nd International Conference on Field Programmable Logic and Applications (FPL).

[26]  Javier Minguez,et al.  A Telepresence Mobile Robot Controlled With a Noninvasive Brain–Computer Interface , 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[27]  Philip Grewe,et al.  Learning real-life cognitive abilities in a novel 360°-virtual reality supermarket: a neuropsychological study of healthy participants and patients with epilepsy , 2013, Journal of NeuroEngineering and Rehabilitation.

[28]  Jaeseung Jeong,et al.  Toward Brain-Actuated Humanoid Robots: Asynchronous Direct Control Using an EEG-Based BCI , 2012, IEEE Transactions on Robotics.

[29]  Cuntai Guan Brain-computer interface for stroke rehabilitation with clinical studies , 2013, 2013 International Winter Workshop on Brain-Computer Interface (BCI).

[30]  Pablo F. Diez,et al.  Asynchronous BCI control using high-frequency SSVEP , 2011, Journal of NeuroEngineering and Rehabilitation.

[31]  Ivan Volosyak,et al.  Optimal visual stimuli on LCD screens for SSVEP based brain-computer interfaces , 2009, 2009 4th International IEEE/EMBS Conference on Neural Engineering.

[32]  O. Bai,et al.  Electroencephalography (EEG)-Based Brain–Computer Interface (BCI): A 2-D Virtual Wheelchair Control Based on Event-Related Desynchronization/Synchronization and State Control , 2012, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[33]  Chang-Hwan Im,et al.  Development of an SSVEP-based BCI spelling system adopting a QWERTY-style LED keyboard , 2012, Journal of Neuroscience Methods.

[34]  A. Akce,et al.  A Brain–Machine Interface to Navigate a Mobile Robot in a Planar Workspace: Enabling Humans to Fly Simulated Aircraft With EEG , 2013, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[35]  Ning Jiang,et al.  Peripheral Electrical Stimulation Triggered by Self-Paced Detection of Motor Intention Enhances Motor Evoked Potentials , 2012, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[36]  Po-Lei Lee,et al.  Development of a Low-Cost FPGA-Based SSVEP BCI Multimedia Control System , 2010, IEEE Transactions on Biomedical Circuits and Systems.