Predicting Functional Recovery in Chronic Stroke Rehabilitation Using Event-Related Desynchronization-Synchronization during Robot-Assisted Movement

Although rehabilitation robotics seems to be a promising therapy in the rehabilitation of the upper limb in stroke patients, consensus is still lacking on its additive effects. Therefore, there is a need for determining the possible success of robotic interventions on selected patients, which in turn determine the necessity for new investigating instruments supporting the treatment decision-making process and customization. The objective of the work presented in this preliminary study was to verify that fully robot assistance would not affect the physiological oscillatory cortical activity related to a functional movement in healthy subjects. Further, the clinical results following the robotic treatment of a chronic stroke patient, who positively reacted to the robotic intervention, were analyzed and discussed. First results show that there is no difference in EEG activation pattern between assisted and no-assisted movement in healthy subjects. Even more importantly, the patient's pretreatment EEG activation pattern in no-assisted movement was completely altered, while it recovered to a quasi-physiological one in robot-assisted movement. The functional improvement following treatment was large. Using pretreatment EEG recording during robot-assisted movement might be a valid approach to assess the potential ability of the patient for recovering.

[1]  Shunsuke Ohtahara,et al.  Topographic mapping of brain electrical activity, FH Duffy (Ed.). Butterworths, Boston · London · Durban · Singapore · Sydney · Toronto · Wellington (1986), 428 pp , 1987 .

[2]  N. Pedrocchi,et al.  Proprioceptivity and upper-extremity dynamics in robot-assisted reaching movement , 2012, 2012 4th IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob).

[3]  P. Dario,et al.  Design strategies to improve patient motivation during robot-aided rehabilitation , 2007, Journal of NeuroEngineering and Rehabilitation.

[4]  Robert Riener,et al.  Rehabilitation Robotics , 2013, Found. Trends Robotics.

[5]  R. C. Oldfield The assessment and analysis of handedness: the Edinburgh inventory. , 1971, Neuropsychologia.

[6]  Brain Aids to the Examination of the Peripheral Nervous System , 1987 .

[7]  Valentina Squeri,et al.  Desirable features of a “humanoid” robot-therapist , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[8]  Hermano I Krebs,et al.  Rehabilitation robotics: pilot trial of a spatial extension for MIT-Manus , 2004, Journal of NeuroEngineering and Rehabilitation.

[9]  Maarten J. IJzerman,et al.  Systematic review of the effect of robot-aided therapy on recovery of the hemiparetic arm after stroke. , 2006, Journal of rehabilitation research and development.

[10]  Rajesh Verma,et al.  Estimating the Minimal Clinically Important Difference of an Upper Extremity Recovery Measure in Subacute Stroke Patients , 2011, Topics in stroke rehabilitation.

[11]  DR McCluskey,et al.  Aids to the examination of the peripheral nervous system , 1989, Practical Neurology.

[12]  P. Manganotti,et al.  Electroencephalographic Changes of Brain Oscillatory Activity After Upper Limb Somatic Sensation Training in a Patient With Somatosensory Deficit After Stroke , 2015, Clinical EEG and neuroscience.

[13]  J. Artieda,et al.  Beta electroencephalograph changes during passive movements: sensory afferences contribute to beta event-related desynchronization in humans , 2002, Neuroscience Letters.

[14]  A. Fugl-Meyer,et al.  The post-stroke hemiplegic patient. 1. a method for evaluation of physical performance. , 1975, Scandinavian journal of rehabilitation medicine.

[15]  T. Sejnowski,et al.  Removing electroencephalographic artifacts by blind source separation. , 2000, Psychophysiology.

[16]  F. Perrin,et al.  Spherical splines for scalp potential and current density mapping. , 1989, Electroencephalography and clinical neurophysiology.

[17]  Paolo Gallina,et al.  Upper limb rehabilitation robotics after stroke: a perspective from the University of Padua, Italy. , 2009, Journal of rehabilitation medicine.

[18]  G. R. Muller,et al.  Event-related beta EEG changes during wrist movements induced by functional electrical stimulation of forearm muscles in man , 2003, Neuroscience Letters.

[19]  S. Masiero,et al.  Upper-limb robot-assisted therapy in rehabilitation of acute stroke patients: focused review and results of new randomized controlled trial. , 2011, Journal of rehabilitation research and development.

[20]  Timothy D. Lee,et al.  Motor Control and Learning: A Behavioral Emphasis , 1982 .

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

[22]  Gert Kwakkel,et al.  Invited commentary on comparison of robotics, functional electrical stimulation, and motor learning methods for treatment of persistent upper extremity dysfunction after stroke: a randomized controlled trial. , 2015, Archives of physical medicine and rehabilitation.

[23]  G. Pfurtscheller,et al.  Event-related cortical desynchronization detected by power measurements of scalp EEG. , 1977, Electroencephalography and clinical neurophysiology.

[24]  D.J. Reinkensmeyer,et al.  Optimizing Compliant, Model-Based Robotic Assistance to Promote Neurorehabilitation , 2008, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[25]  M. Cagy,et al.  Electrophysiological analysis of the perception of passive movement , 2011, Neuroscience Letters.

[26]  Matteo Malosio,et al.  Normative Data for an Instrumental Assessment of the Upper-Limb Functionality , 2015, BioMed research international.

[27]  N. Schweighofer,et al.  Task-Oriented Rehabilitation Robotics , 2012, American journal of physical medicine & rehabilitation.

[28]  Nicola Smania,et al.  Time–Frequency Modulation of ERD and EEG Coherence in Robot-Assisted Hand Performance , 2014, Brain Topography.

[29]  Nicola Smania,et al.  Modulation of event-related desynchronization in robot-assisted hand performance: brain oscillatory changes in active, passive and imagined movements , 2013, Journal of NeuroEngineering and Rehabilitation.

[30]  H I Krebs,et al.  Rehabilitation robotics. , 2013, Handbook of clinical neurology.