Posts Tagged Post-stroke rehabilitation

[BOOK] Converging Clinical and Engineering Research on Neurorehabilitation III – Proceedings – SpringerLink

Proceedings of the 4th International Conference on NeuroRehabilitation (ICNR2018), October 16-20, 2018, Pisa, Italy


The book reports on advanced topics in the areas of neurorehabilitation research and practice. It focuses on new methods for interfacing the human nervous system with electronic and mechatronic systems to restore or compensate impaired neural functions. Importantly, the book merges different perspectives, such as the clinical, neurophysiological, and bioengineering ones, to promote, feed and encourage collaborations between clinicians, neuroscientists and engineers.  Based on the 2018 International Conference on Neurorehabilitation (ICNR 2018) held on October 16-20, 2018, in Pisa, Italy,, this book covers various aspects of neurorehabilitation research and practice, including new insights into biomechanics, brain physiology, neuroplasticity, and brain damages and diseases, as well as innovative methods and technologies for studying and/or recovering brain function, from data mining to interface technologies and neuroprosthetics. In this way, it offers a concise, yet comprehensive reference guide to neurosurgeons, rehabilitation physicians, neurologists, and bioengineers. Moreover, by highlighting current challenges in understanding brain diseases as well as in the available technologies and their implementation, the book is also expected to foster new collaborations between the different groups, thus stimulating new ideas and research directions.

Table of contents (233 papers)

Visit Site —> Converging Clinical and Engineering Research on Neurorehabilitation III | SpringerLink


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[Case Report] Biomechanical Assessment of Fugl-Meyer Score: The Case of One Post Stroke Patient Who has Undergone the Rehabilitation using Hand Exoskeleton Controlled by Brain-Computer Interface


Objective: The study is double aimed: 1) to propose a version of common protocol for an assessment of upper limb motor impairment with the use of biomechanical characteristics of Fugl-Meyer items and 2) to apply this protocol to assess an efficacy of rehabilitation using hand exoskeleton controlled by brain-computer interface during the late stage of post stroke recovery in patient with mild paresis.

Methods: One patient, 62 years old man, 10 months after ischemic stroke was recruited in the rehabilitation procedure. The patient was instructed to perform one of three tasks: to relax and to imagine kinesthetically slow extension of either paretic (left) or intact (right) hand fingers. The recorded electroencephalography was analyzed and exoskeleton extended the patient’s fingers if brain-computer interface classifier recognized the imagery of their extension. The patient performed 10 daily procedures, each including three 10-minute long sessions. 14 items of Fugl-Meyer scale, describing flexor synergy (domain II), extensor synergy (domain III), movement combining synergies (domain IV) and movement out of synergy (domain V) were evaluated by standard Fugl-Meyer scores. In addition to Fugl-Meyer assessment biomechanical analysis of each item was performed. The items were recorded by electromagnetic tracking system for both paretic and intact arms. All seven degrees of freedom in each
arm were taken into account. Two types of biomechanical parameters were analyzed: 1) coordination between angular velocities and 2) maximal angular velocities corresponding to seven degrees of freedom of the arm.

Results: Fugl-Meyer assessment revealed motor improvements for two items only, whereas biomechanical analysis for all 14 items considered.

Conclusion: The use of Fugl-Meyer scale completed by biomechanical parameters of its’ items can be a version of common protocol for assessment of upper limb motor impairment, useful for obtaining a comparable data in different clinical studies.

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[ARTICLE] Motor Imagery based Brain-Computer Interfaces: An Emerging Technology to Rehabilitate Motor Deficits


  • BCIs permit to reintegrate the sensory-motor loop by accessing to brain information.
  • Motor imagery based BCIs seem to be an effective system for an early rehabilitation.
  • This technology does not need remaining motor activity and promotes neuroplasticity.
  • BCI for rehabilitation tends towards implantable devices plus stimulation systems.


When the sensory-motor integration system is malfunctioning provokes a wide variety of neurological disorders, which in many cases cannot be treated with conventional medication, or via existing therapeutic technology. A brain-computer interface (BCI) is a tool that permits to reintegrate the sensory-motor loop, accessing directly to brain information. A potential, promising and quite investigated application of BCI has been in the motor rehabilitation field. It is well-known that motor deficits are the major disability wherewith the worldwide population lives. Therefore, this paper aims to specify the foundation of motor rehabilitation BCIs, as well as to review the recent research conducted so far (specifically, from 2007 to date), in order to evaluate the suitability and reliability of this technology. Although BCI for post-stroke rehabilitation is still in its infancy, the tendency is towards the development of implantable devices that encompass a BCI module plus a stimulation system.

Source: Motor Imagery based Brain-Computer Interfaces: An Emerging Technology to Rehabilitate Motor Deficits

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