Brain-Computer Interface and Functional Electrical Stimulation for Neurorehabilitation of Hand in Sub-acute Tetraplegic Patients - Functional and Neurological Outcomes

The aim of this paper is to compare neurological and functional outcomes between two groups of subacute hospitalised patients with incomplete tetraplegia receiving two experimental therapies. Seven patients received 20 sessions of Brain Computer Interface (BCI) controlled Functional Electrical Stimulation (FES) while five patients received 20 sessions of passive FES. The treatment assessment measures were EEG during movement attempt, Somatosensory evoked potential (SSEP) of the ulnar and median nerve and the range of movement of both wrists. Patients in both groups initially had intense cortical activity during a movement attempt, which was wide-spread, not restricted to the sensory-motor cortex. Following the treatment, cortical activity restored towards the activity in able-bodied people in BCI-FES group only. SSEP also returned in 3 patients in BCI-FES group while in FES group no changes were noticed. The range of movement improved in both groups and results are inconclusive due to the small number of participants. This study confirms the feasibility of prolonged BCI-FES therapy in a hospital setting. The results indicate better neurological recovery in BCI-FES group. Larger and longer studies are required to assess the potential advantage of BCI-FES on functional recovery.

[1]  Nicole Krämer,et al.  Time Domain Parameters as a feature for EEG-based Brain-Computer Interfaces , 2009, Neural Networks.

[2]  Mark E. Dohring,et al.  Feasibility of a New Application of Noninvasive Brain Computer Interface (BCI): A Case Study of Training for Recovery of Volitional Motor Control After Stroke , 2009, Journal of neurologic physical therapy : JNPT.

[3]  R. Chabot,et al.  SOMATOSENSORY EVOKED POTENTIALS , 1990, International anesthesiology clinics.

[4]  J B Green,et al.  Cortical sensorimotor reorganization after spinal cord injury , 1998, Neurology.

[5]  S. Holm A Simple Sequentially Rejective Multiple Test Procedure , 1979 .

[6]  R. Rupp Challenges in clinical applications of brain computer interfaces in individuals with spinal cord injury , 2014, Front. Neuroeng..

[7]  Milos R Popovic,et al.  Short‐Term Neuroplastic Effects of Brain‐Controlled and Muscle‐Controlled Electrical Stimulation , 2015, Neuromodulation : journal of the International Neuromodulation Society.

[8]  S. Lalwani,et al.  Spinal cord injury. , 2011, Journal of neurosurgery. Spine.

[9]  Yi Wu,et al.  Neurophysiological substrates of stroke patients with motor imagery-based brain-computer interface training , 2014, The International journal of neuroscience.

[10]  Erkki Oja,et al.  Independent component analysis: algorithms and applications , 2000, Neural Networks.

[11]  Aleksandra Vuckovic,et al.  Dynamic Oscillatory Signatures of Central Neuropathic Pain in Spinal Cord Injury , 2014, The journal of pain : official journal of the American Pain Society.

[12]  Carmen Vidaurre,et al.  BioSig: The Free and Open Source Software Library for Biomedical Signal Processing , 2011, Comput. Intell. Neurosci..

[13]  Vivek Prabhakaran,et al.  Case report: post-stroke interventional BCI rehabilitation in an individual with preexisting sensorineural disability , 2014, Front. Neuroeng..

[14]  Aleksandra Vučković,et al.  Hybrid Brain-Computer Interface and Functional Electrical Stimulation for Sensorimotor Training in Participants With Tetraplegia: A Proof-of-Concept Study , 2015, Journal of neurologic physical therapy : JNPT.

[15]  S. C. Gandevia,et al.  Neuropathic pain and primary somatosensory cortex reorganization following spinal cord injury , 2009, PAIN®.

[16]  Taehoon Kim,et al.  Effects of Action Observational Training Plus Brain-Computer Interface-Based Functional Electrical Stimulation on Paretic Arm Motor Recovery in Patient with Stroke: A Randomized Controlled Trial. , 2016, Occupational therapy international.

[17]  Valer Jurcak,et al.  10/20, 10/10, and 10/5 systems revisited: Their validity as relative head-surface-based positioning systems , 2007, NeuroImage.

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

[19]  W. Donovan,et al.  International Standards For Neurological Classification Of Spinal Cord Injury , 2003, The journal of spinal cord medicine.

[20]  Fei Meng,et al.  A Minimal Set of Electrodes for Motor Imagery BCI to Control an Assistive Device in Chronic Stroke Subjects: A Multi-Session Study , 2011, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[21]  Suk-Tak Chan,et al.  BCI-FES training system design and implementation for rehabilitation of stroke patients , 2008, 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence).

[22]  G. Pfurtscheller,et al.  ‘Thought’ – control of functional electrical stimulation to restore hand grasp in a patient with tetraplegia , 2003, Neuroscience Letters.

[23]  Aleksandra Vuckovic,et al.  Feasibility of using time-domain parameters as online therapeutic BCI features , 2014 .

[24]  Hiroshi Shibasaki,et al.  Somatosensory evoked potentials Diagnostic criteria and abnormalities in cerebral lesions , 1977, Journal of the Neurological Sciences.

[25]  A Curt,et al.  Electrophysiological recordings in patients with spinal cord injury: significance for predicting outcome , 1999, Spinal Cord.

[26]  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.

[27]  Akio Kimura,et al.  Efficacy of brain-computer interface-driven neuromuscular electrical stimulation for chronic paresis after stroke. , 2014, Journal of rehabilitation medicine.

[28]  B. Conway,et al.  The mechanism of neurofeedback training for treatment of central neuropathic pain in paraplegia: a pilot study , 2015, BMC Neurology.

[29]  Keinosuke Fukunaga,et al.  Introduction to Statistical Pattern Recognition , 1972 .

[30]  Cuntai Guan,et al.  EEG controlled neuromuscular electrical stimulation of the upper limb for stroke patients , 2011 .