scholarly journals Motor Imagery-Based Brain-Computer Interface Combined with Multimodal Feedback to Promote Upper Limb Motor Function after Stroke: A Preliminary Study

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yi-Qian Hu ◽  
Tian-Hao Gao ◽  
Jie Li ◽  
Jia-Chao Tao ◽  
Yu-Long Bai ◽  
...  
Keyword(s):  
Motor Function ◽  
Motor Imagery ◽  
Upper Limb ◽  
Brain Computer Interface ◽  
Chronic Stroke ◽  
Computer Interface ◽  
Stroke Patients ◽  
Multimodal Feedback ◽  
Before And After ◽  
Extensor Carpi Radialis

Background. Recently, the brain-computer interface (BCI) has seen rapid development, which may promote the recovery of motor function in chronic stroke patients. Methods. Twelve stroke patients with severe upper limb and hand motor impairment were enrolled and randomly assigned into two groups: motor imagery (MI)-based BCI training with multimodal feedback (BCI group, n = 7) and classical motor imagery training (control group, n = 5). Motor function and electrophysiology were evaluated before and after the intervention. The Fugl-Meyer assessment-upper extremity (FMA-UE) is the primary outcome measure. Secondary outcome measures include an increase in wrist active extension or surface electromyography (the amplitude and cocontraction of extensor carpi radialis during movement), the action research arm test (ARAT), the motor status scale (MSS), and Barthel index (BI). Time-frequency analysis and power spectral analysis were used to reflect the electroencephalogram (EEG) change before and after the intervention. Results. Compared with the baseline, the FMA-UE score increased significantly in the BCI group ( p  = 0.006). MSS scores improved significantly in both groups, while ARAT did not improve significantly. In addition, before the intervention, all patients could not actively extend their wrists or just had muscle contractions. After the intervention, four patients regained the ability to extend their paretic wrists (two in each group). The amplitude and area under the curve of extensor carpi radialis improved to some extent, but there was no statistical significance between the groups. Conclusion. MI-based BCI combined with sensory and visual feedback might improve severe upper limb and hand impairment in chronic stroke patients, showing the potential for application in rehabilitation medicine.

scholarly journals 2190 Longitudinal changes in EEG power envelope connectivity are proportional to motor recovery in chronic stroke patients

2018 ◽  
Vol 2 (S1) ◽  
pp. 17-17
Author(s):  
Joseph B. Humphries ◽  
David T. Bundy ◽  
Eric C. Leuthardt ◽  
Thy N. Huskey
Keyword(s):  
Motor Cortex ◽  
Motor Imagery ◽  
Stroke Rehabilitation ◽  
Brain Computer Interface ◽  
Chronic Stroke ◽  
Motor Recovery ◽  
Stroke Recovery ◽  
Computer Interface ◽  
Beta Band ◽  
Stroke Patients

OBJECTIVES/SPECIFIC AIMS: The objective of this study is to determine the degree to which the use of a contralesionally-controlled brain-computer interface for stroke rehabilitation drives change in interhemispheric motor cortical activity. METHODS/STUDY POPULATION: Ten chronic stroke patients were trained in the use of a brain-computer interface device for stroke recovery. Patients perform motor imagery to control the opening and closing of a motorized hand orthosis. This device was sent home with patients for 12 weeks, and patients were asked to use the device 1 hour per day, 5 days per week. The Action Research Arm Test (ARAT) was performed at 2-week intervals to assess motor function improvement. Before the active motor imagery task, patients were asked to quietly rest for 90 seconds before the task to calibrate recording equipment. EEG signals were acquired from 2 electrodes—one each centered over left and right primary motor cortex. Signals were preprocessed with a 60 Hz notch filter for environmental noise and referenced to the common average. Power envelopes for 1 Hz frequency bands (1–30 Hz) were calculated through Gabor wavelet convolution. Correlations between electrodes were then calculated for each frequency envelope on the first and last 5 runs, thus generating one correlation value per subject, per run. The chosen runs approximately correspond to the first and last week of device usage. These correlations were Fisher Z-transformed for comparison. The first and last 5 run correlations were averaged separately to estimate baseline and final correlation values. A difference was then calculated between these averages to determine correlation change for each frequency. The relationship between beta-band correlation changes (13–30 Hz) and the change in ARAT score was determined by calculating a Pearson correlation. RESULTS/ANTICIPATED RESULTS: Beta-band inter-electrode correlations tended to decrease more in patients achieving greater motor recovery (Pearson’s r=−0.68, p=0.031). A similar but less dramatic effect was observed with alpha-band (8–12 Hz) correlation changes (Pearson’s r=−0.42, p=0.22). DISCUSSION/SIGNIFICANCE OF IMPACT: The negative correlation between inter-electrode power envelope correlations in the beta frequency band and motor recovery indicates that activity in the motor cortex on each hemisphere may become more independent during recovery. The role of the unaffected hemisphere in stroke recovery is currently under debate; there is conflicting evidence regarding whether it supports or inhibits the lesioned hemisphere. These findings may support the notion of interhemispheric inhibition, as we observe less in common between activity in the 2 hemispheres in patients successfully achieving recovery. Future neuroimaging studies with greater spatial resolution than available with EEG will shed further light on changes in interhemispheric communication that occur during stroke rehabilitation.

scholarly journals Brain Functional Changes in Stroke Following Rehabilitation Using Brain-Computer Interface-Assisted Motor Imagery With and Without tDCS: A Pilot Study

2021 ◽  
Vol 15 ◽  
Author(s):  
Mengjiao Hu ◽  
Hsiao-Ju Cheng ◽  
Fang Ji ◽  
Joanna Su Xian Chong ◽  
Zhongkang Lu ◽  
...  
Keyword(s):  
Motor Function ◽  
Motor Imagery ◽  
Brain Computer Interface ◽  
Low Frequency ◽  
Computer Interface ◽  
Stroke Patients ◽  
Post Intervention ◽  
Functional Changes ◽  
Post Stroke ◽  
Assessment Scores

Brain-computer interface-assisted motor imagery (MI-BCI) or transcranial direct current stimulation (tDCS) has been proven effective in post-stroke motor function enhancement, yet whether the combination of MI-BCI and tDCS may further benefit the rehabilitation of motor functions remains unknown. This study investigated brain functional activity and connectivity changes after a 2 week MI-BCI and tDCS combined intervention in 19 chronic subcortical stroke patients. Patients were randomized into MI-BCI with tDCS group and MI-BCI only group who underwent 10 sessions of 20 min real or sham tDCS followed by 1 h MI-BCI training with robotic feedback. We derived amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), and functional connectivity (FC) from resting-state functional magnetic resonance imaging (fMRI) data pre- and post-intervention. At baseline, stroke patients had lower ALFF in the ipsilesional somatomotor network (SMN), lower ReHo in the contralesional insula, and higher ALFF/Reho in the bilateral posterior default mode network (DMN) compared to age-matched healthy controls. After the intervention, the MI-BCI only group showed increased ALFF in contralesional SMN and decreased ALFF/Reho in the posterior DMN. In contrast, no post-intervention changes were detected in the MI-BCI + tDCS group. Furthermore, higher increases in ALFF/ReHo/FC measures were related to better motor function recovery (measured by the Fugl-Meyer Assessment scores) in the MI-BCI group while the opposite association was detected in the MI-BCI + tDCS group. Taken together, our findings suggest that brain functional re-normalization and network-specific compensation were found in the MI-BCI only group but not in the MI-BCI + tDCS group although both groups gained significant motor function improvement post-intervention with no group difference. MI-BCI and tDCS may exert differential or even opposing impact on brain functional reorganization during post-stroke motor rehabilitation; therefore, the integration of the two strategies requires further refinement to improve efficacy and effectiveness.

scholarly journals Brain-computer-interface technology with multisensory feedback for controlled ideomotor training in the rehabilitation of stroke patients

2019 ◽  
pp. 27-32
Author(s):  
Yu.V. Bushkova ◽  
G.E. Ivanova ◽  
L.V. Stakhovskaya ◽  
A.A. Frolov
Keyword(s):  
Motor Imagery ◽  
Upper Limb ◽  
Brain Computer Interface ◽  
Motor Recovery ◽  
Computer Interface ◽  
Robotic Hand ◽  
Stroke Patients ◽  
Factors Affecting ◽  
The Difference ◽  
Recovery Dynamics

Motor recovery of the upper limb is a priority in the neurorehabilitation of stroke patients. Advances in the brain-computer interface (BCI) technology have significantly improved the quality of rehabilitation. The aim of this study was to explore the factors affecting the recovery of the upper limb in stroke patients undergoing BCI-based rehabilitation with the robotic hand. The study recruited 24 patients (14 men and 10 women) aged 51 to 62 years with a solitary supratentorial stroke lesion. The lesion was left-hemispheric in 11 (45.6%) patients and right-hemispheric in 13 (54.4%) patients. Time elapsed from stroke was 4.0 months (3.0; 12.0). The median MoCa score was 25.0 (23.0; 27.0). The rehabilitation course consisted of 9.5 sessions (8.0; 10.0). We established a significant moderate correlation between motor imagery performance (the MIQ-RS score) and the efficacy of patient-BCI interaction. Patients with high MIQ-RS scores (47.5 (32.0; 54.0) achieved a better control of the BCI-driven hand exoskeleton (63.0 (54.0; 67.0), R = 0.67; p < 0.05). Recovery dynamics were more pronounced in patients with high MIQ-RS scores: the median score on the Fugl-Meyer Assessment scale was 14 (8.0; 16.0) points vs 10 (6.0; 13.0) points in patients with low MIQ-RS scores. However, the difference was not significant. Thus, we established a correlation between a patient’s ability for motor imagery (MIQ-RS) and the efficacy of patient-BCI interaction. A larger patient sample might be necessary to assess the effect of these factors on motor recovery dynamics.

A Brain-Computer Interface For Motor Rehabilitation Of Chronic Stroke Patients

2018 ◽  
Vol 99 (10) ◽  
pp. e36
Author(s):  
Christoph Guger ◽  
Brendan Allison ◽  
Slav H. Dimov ◽  
Edlinger Guenter ◽  
Fan Cao
Keyword(s):  
Brain Computer Interface ◽  
Chronic Stroke ◽  
Computer Interface ◽  
Motor Rehabilitation ◽  
Stroke Patients

Training and assessment of upper limb motor function with a robotic exoskeleton in chronic stroke patients

2014 ◽  
Vol 40 ◽  
pp. S27-S28 ◽  
Author(s):  
C. Chisari ◽  
A. Frisoli ◽  
E. Sotgiu ◽  
C. Procopio ◽  
F. Bertolucci ◽  
...  
Keyword(s):  
Motor Function ◽  
Upper Limb ◽  
Chronic Stroke ◽  
Stroke Patients ◽  
Robotic Exoskeleton

scholarly journals Facilitating motor imagery-based brain–computer interface for stroke patients using passive movement

2016 ◽  
Vol 28 (11) ◽  
pp. 3259-3272 ◽  
Author(s):  
Mahnaz Arvaneh ◽  
Cuntai Guan ◽  
Kai Keng Ang ◽  
Tomas E. Ward ◽  
Karen S. G. Chua ◽  
...  
Keyword(s):  
Motor Imagery ◽  
Brain Computer Interface ◽  
Passive Movement ◽  
Computer Interface ◽  
Stroke Patients
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