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Clinical Trials/NCT02325947
NCT02325947CompletedNot Applicable

A Multicentre Randomized Single Blind Placebo Controlled Study to Assess Efficacy of Hand Exoskeleton Controlled by Motor Imagery Based BCI for Post Stroke Patients Movement Rehabilitation

Russian Academy of Medical Sciences2 sites in 1 country75 target enrollmentStarted: January 2015Last updated:
Conditions
Interventions

Trial Snapshot

Phase
Not Applicable
Status
Completed
Enrollment
75
Locations
2
Primary Endpoint
Change from Baseline in hand paresis level and hand muscle spasticity

Study Overview

Brief Summary

The purpose of this study is to assess the efficacy of non-invasive BCI-exoskeleton technology based on EEG patterns recognition matching to motor imagery in post-stroke patients with hand paresis.

Detailed Description

The BCI training is based on EEG activity patterns recording during hand motor imagery. A subject sit comfortably 1m from a computer screen which presents visual instructions during the session. The robotic exoskeleton is fixed to the paretic hand. Subject visually fixate on a circle presented in the center of the screen and receive instructions from three surrounding rhomboidal arrows. Subject is given three commands instructing them to relax or imagine slow hand opening movement with the right or left hand. The "Relax" command means that the subject have to sit still and look at the center of the screen. Commands are presented randomly, each of 10 sec duration.

A visual cue provides the subject with feedback regarding the mental task recognition: the central circle turned green if the classifier recognizes the task in agreement with the given command, or remains white if the signal is not recognized. In addition to visual feedback the subject is provided with kinesthetic feedback: the exoskeleton is opening the hand when the classifier recognizes the imagery of paretic hand movement.

The EEG is registered with 30 electrodes distributed over the head in accordance with the standard international 10-20 system. EEG signals are filtered from 5-30Hz. A Bayesian approach for EEG pattern classifying is used in the system. The activity sources most relevant for BCI functioning will be identified using an independent component analysis (ICA). Classification accuracy will by measured with Cohen's kappa (Kohavi and Provost, 1998). The procedure may consist from up to three sessions, the duration of 1 session is 10 min, there are 5 min time brake between session and total duration of procedure is up to 45 min. The number of procedures - at least 10. The maximal interval between procedures is 3 days.

Study Design

Study Type
Interventional
Allocation
Randomized
Intervention Model
Parallel
Primary Purpose
Health Services Research
Masking
Single (Participant)

Eligibility Criteria

Ages
18 Years to 80 Years (Adult, Older Adult)
Sex
All
Accepts Healthy Volunteers
No

Inclusion Criteria

  • Signed informed consent
  • Medical history of primary acute cerebrovascular event (ischemic or hemorrhagic stroke) at least 4 weeks before screening
  • focal stroke located in a hemisphere
  • post stroke hand paresis (mild to plegia according to Medical Research Council (MRC) Scale for Muscle Strength)

Exclusion Criteria

  • Montreal Cognitive Assessment (MoCA) scale < 22
  • Left handedness
  • Sensory aphasia
  • Severe impairment of vision
  • Modified Ashworth Scale (MAS) ≥ 4

Arms & Interventions

Study group

Experimental

Hand exoskeleton, brain-computer interface (BCI) 10 sessions of 45-minutes

Intervention: hand exoskeleton, brain-computer interface (BCI), (Device)

Placebo group

Sham Comparator

Hand exoskeleton, sham BCI 10 sessions of 45-minutes (BCI imitation)

Intervention: hand exoskeleton, sham BCI (Device)

Outcomes

Primary Outcomes

Change from Baseline in hand paresis level and hand muscle spasticity

Time Frame: Week 2

ARAT; Fugl-Meyer, Modified Ashworth scale

Secondary Outcomes

  • Long-term changes from Baseline in hand paresis level and hand muscle spasticity(week 4, week 12, week 24)

Investigators

Sponsor Class
Other
Responsible Party
Principal Investigator
Principal Investigator

Roman Lyukmanov

Research scientist

Russian Academy of Medical Sciences

Study Sites (2)

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