This study was supported by the National Science Foundation of Guangdong Province (No.2023A1515010586), Guangzhou clinical characteristic technology construction project (2023C-TS19), Education Science Planning Project of Guangdong Province (No.2022GXJK299), the General Guidance Program of Guangzhou Municipal Health and Family Planning (20221A011109, 20231A011111), 2022 Guangzhou Higher Education Teaching Quality and Teaching Reform Project of Higher Education Teaching reform General project (No.2022JXGG088/02-408-2306040XM), 2022 Guangzhou Medical University Student Innovation Ability Improvement Plan project (No.PX-66221494/02-408-2304-19062XM), 2021 school-level education science planning project (2021: NO.45), 2023 First-class Undergraduate Major Construction Fund of high-level University (2022JXA009,&#160;2022JXD001, 2022JXD003)/(02-408-2304-06XM), Guangzhou Education Bureau university research project (No. 202235384), 2022 Undergraduate Teaching Quality and Teaching Reform Project of Guangzhou Medical University (2022 NO. 33), National Science Foundation of Guangdong Province (No. 2021A1515012197), and Guangzhou and University Foundation (No. 202102010100).

This project was approved by the Medical Ethics Association of the Fifth Affiliated Hospital of Guangzhou Medical University (approval No. KY01-2021-05-01) on August 19, 2021. The trial was registered in the Chinese Clinical Trials Registry (registration number: NO. ChiCTR2100050162) on August 19, 2021. All patients signed the informed consent form.
1. Recruitment
<ol>
	<li>Inclusion criteria
	<ol>
		<li>Recruit patients who meet the diagnostic criteria of stroke formulated ...

Restoring Post-Stroke Motor Function by Motor Imagery Brain-Computer Interface

<ol>
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K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Brain-computer+interface-based+robotic+end+effector+system+for+wrist+and+hand+rehabilitation:+results+of+a+three-armed+randomized+controlled+trial+for+chronic+stroke.">Brain-computer interface-based robotic end effector system for wrist and hand rehabilitation: results of a three-armed randomized controlled trial for chronic stroke.</a> Frontiers in Neuroengineering. 7, 30 (2014).</li><li>Nuwer, M. R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=IFCN+standards+for+digital+recording+of+clinical+EEG.+The+International+Federation+of+Clinical+Neurophysiology.">IFCN standards for digital recording of clinical EEG. The International Federation of Clinical Neurophysiology.</a> Electroencephalography and Clinical Neurophysiology. 52, 11-14 (1999).</li><li>Klem, G. H., L&#252;ders, H. O., Jasper, H. H., Elger, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+ten-twenty+electrode+system+of+the+International+Federation.+The+International+Federation+of+Clinical+Neurophysiology.">The ten-twenty electrode system of the International Federation. The International Federation of Clinical Neurophysiology.</a> Electroencephalography and Clinical Neurophysiology. 52, 3-6 (1999).</li><li>Uwe Herwig, ., Peyman Satrapi, ., Sch&#246;nfeldt-Lecuona, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Using+the+international+10-20+EEG+system+for+positioning+of+transcranial+magnetic+stimulation.">Using the international 10-20 EEG system for positioning of transcranial magnetic stimulation.</a> Brain Topography. , (2003).</li><li>Mane, R., Robinson, N., Vinod, A. P., Lee, S. W., Guan, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+Multi-view+CNN+with+Novel+Variance+Layer+for+Motor+Imagery+Brain+Computer+Interface.">A Multi-view CNN with Novel Variance Layer for Motor Imagery Brain Computer Interface.</a> Annual International Conference of the IEEE Engineering in Medicine and Biology Society. 2020, 2950-2953 (2020).</li><li>Sanford, J., Moreland, J., Swanson, L. R., Stratford, P. W., Gowland, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Reliability+of+the+Fugl-Meyer+assessment+for+testing+motor+performance+in+patients+following+stroke.">Reliability of the Fugl-Meyer assessment for testing motor performance in patients following stroke.</a> Physical Therapy. 73 (7), 447-454 (1993).</li><li>Martinez, C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+Reaching+Performance+Scale+for+2+Wolf+Motor+Function+Test+Items.">A Reaching Performance Scale for 2 Wolf Motor Function Test Items.</a> Archives of Physical Medicine and Rehabilitation. 101 (11), 2015-2026 (2020).</li><li>Dufouil, C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Population+norms+for+the+MMSE+in+the+very+old:+estimates+based+on+longitudinal+data.+Mini-Mental+State+Examination.">Population norms for the MMSE in the very old: estimates based on longitudinal data. Mini-Mental State Examination.</a> Neurology. 55 (11), 1609-1613 (2000).</li><li>Thompson, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Hamilton+Rating+Scale+for+Anxiety+(HAM-A).">Hamilton Rating Scale for Anxiety (HAM-A).</a> Occupational Medicine. 65 (7), 601 (2015).</li><li>Zimmerman, M., Martinez, J. H., Young, D., Chelminski, I., Dalrymple, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Severity+classification+on+the+Hamilton+Depression+Rating+Scale.">Severity classification on the Hamilton Depression Rating Scale.</a> Journal of Affective Disorders. 150 (2), 384-388 (2013).</li><li>Bai, X., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Different+Therapeutic+Effects+of+Transcranial+Direct+Current+Stimulation+on+Upper+and+Lower+Limb+Recovery+of+Stroke+Patients+with+Motor+Dysfunction:+A+Meta-Analysis.">Different Therapeutic Effects of Transcranial Direct Current Stimulation on Upper and Lower Limb Recovery of Stroke Patients with Motor Dysfunction: A Meta-Analysis.</a> Neural Plasticity. 2019, 1372138 (2019).</li><li>Dimyan, M. A., Cohen, L. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Neuroplasticity+in+the+context+of+motor+rehabilitation+after+stroke.">Neuroplasticity in the context of motor rehabilitation after stroke.</a> Nature Reviews Neurology. 7 (2), 76-85 (2011).</li><li>Bai, Z., Fong, K. N. K., Zhang, J. J., Chan, J., Ting, K. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Immediate+and+long-term+effects+of+BCI-based+rehabilitation+of+the+upper+extremity+after+stroke:+a+systematic+review+and+meta-analysis.">Immediate and long-term effects of BCI-based rehabilitation of the upper extremity after stroke: a systematic review and meta-analysis.</a> Journal of NeuroEngineering and Rehabilitation. 17 (1), 57 (2020).</li><li>Yang, W., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Effect+of+Brain-Computer+Interface+Training+on+Rehabilitation+of+Upper+Limb+Dysfunction+After+Stroke:+A+Meta-Analysis+of+Randomized+Controlled+Trials.">The Effect of Brain-Computer Interface Training on Rehabilitation of Upper Limb Dysfunction After Stroke: A Meta-Analysis of Randomized Controlled Trials.</a> Frontiers in Neuroscience. 15, 766879 (2021).</li><li>Pandian, S., Arya, K. N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Stroke-related+motor+outcome+measures:+do+they+quantify+the+neurophysiological+aspects+of+upper+extremity+recovery.">Stroke-related motor outcome measures: do they quantify the neurophysiological aspects of upper extremity recovery.</a> Journal of Bodywork and Movement Therapies. 18 (3), 412-423 (2014).</li><li>Potter, S. M., El Hady, A., Fetz, E. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Closed-loop+neuroscience+and+neuroengineering.">Closed-loop neuroscience and neuroengineering.</a> Frontiers in Neural Circuits. 8, 115 (2014).</li><li>Nowak, D. A., Grefkes, C., Ameli, M., Fink, G. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Interhemispheric+competition+after+stroke:+brain+stimulation+to+enhance+recovery+of+function+of+the+affected+hand.">Interhemispheric competition after stroke: brain stimulation to enhance recovery of function of the affected hand.</a> Neurorehabilitation and Neural Repair. 23 (7), 641-656 (2009).</li></ol>

The rehabilitation period for moderate and severe upper limb motor dysfunction after stroke is long and the recovery is difficult, which has always been the focus of clinical rehabilitation research18. Traditional upper limb rehabilitation training is mostly simple peripheral intervention or central intervention19. Meanwhile, due to the lack of active participation of patients with moderate and severe limb dysfunction, passive treatment is mainly used, with poor rehabilitat...

An erratum was issued for:&#160;<a href="https://www.jove.com/t/65405">Motor Imagery Brain-Computer Interface in Rehabilitation of Upper Limb Motor Dysfunction After Stroke</a>. The Authors section was updated from:
Yongchun Jiang1,2,3 
Junxiao Yin4 
Biyi Zhao1,3,5 
Yajie Zhang1,3 
Tingting Peng1,3 
Wanqi Zhuang1,3 
Siqing Wang1,3 
Siqi Huang1,3 
Meilian Zhong1,2,3 
Yanni Zhang1,3 
Guibing Tang1,3 
Bingchi Shen6 
Haining Ou1,3 
Yuxin Zheng2,3&#160; 
Qiang Lin2,3 
1Guangzhou Medical University 
2Department of Rehabilitation Medicine, The Seventh Affiliated Hospital of Sun Yat-sen University 
3Department of Rehabilitation Medicine, The Fifth Affiliated Hospital of Guangzhou Medical University 
4Clinical Medical College of Acupuncture and Rehabilitation, Guangzhou University of Traditional Chinese Medicine 
5School of Traditional Chinese Medicine, Jinan University 
6Department of Stomatology, Second Clinical Medical College, Dongguan Campus of Guangdong Medical University 
&#160;
to:
Yongchun Jiang1,2,3 
Junxiao Yin4 
Biyi Zhao1,3,5 
Yajie Zhang1,3 
Tingting Peng1,3 
Wanqi Zhuang1,3 
Siqing Wang1,3 
Siqi Huang1,3 
Meilian Zhong1,3 
Yanni Zhang1,3 
Guibing Tang1,3 
Bingchi Shen6 
Haining Ou1,3 
Yuxin Zheng2,3&#160; 
Qiang Lin2,3 
1Guangzhou Medical University 
2Department of Rehabilitation Medicine, The Seventh Affiliated Hospital of Sun Yat-sen University 
3Department of Rehabilitation Medicine, The Fifth Affiliated Hospital of Guangzhou Medical University 
4Clinical Medical College of Acupuncture and Rehabilitation, Guangzhou University of Traditional Chinese Medicine 
5School of Traditional Chinese Medicine, Jinan University 
6Department of Stomatology, Second Clinical Medical College, Dongguan Campus of Guangdong Medical University 
&#160;

An erratum was issued for:&#160;<a href="https://www.jove.com/t/65405">Motor Imagery Brain-Computer Interface in Rehabilitation of Upper Limb Motor Dysfunction After Stroke</a>. The Authors section was updated.

Erratum: Motor Imagery Brain-Computer Interface in Rehabilitation of Upper Limb Motor Dysfunction After Stroke

Nearly 85% of stroke patients have motor dysfunction1, especially due to the limited rehabilitation effect of patients with moderate and severe upper limb motor dysfunction, which seriously affects patients' ability to live independent daily lives and has been the focus and difficulty of research. Non-invasive brain-computer interface (BCI) is known as an emerging treatment for rehabilitation of motor dysfunction after stroke2. BCI is the direct conversion of the sensory perception, imagery, cognition, and thinking of users or subjects into actions, without reliance on peripheral nerves or muscles, to establish direct communication and control channels between the brain and external devices3. At present, the paradigms of BCI for clinical rehabilitation include motor imagery (MI), steady-state visual evoked potentials (SSVEP), and auditory evoked potentials (AEP) P3004, of which the most commonly used and convenient is motor imagery brain-computer interface (MI-BCI). MI is an intervention that uses visual/kinesthetic motor imagery to visualize the execution of motor tasks (such as hand, arm, or foot movements). On the one hand, previous studies have demonstrated that activation of the associated motor cortex during MI is similar to actual motor execution5. On the other hand, unlike other paradigms, MI can activate a specific area of activity through motor memory without any external stimulus to improve motor function; this is conducive to implementation in stroke patients, especially when combined with hearing dysfunction6.
Moreover, MI-BCI has been shown to have a positive effect on improving motor dysfunction in stroke patients. Cheng et al. reported that compared with simple soft robotic glove intervention, the soft robotic glove based on MI-BCI combined with tasks oriented to daily life activities showed more obvious functional improvement and more lasting kinesthetic experience in chronic stroke patients after 6 weeks of intervention. Furthermore, it was also able to elicit the perception of motor movements7. Additionally, Ang et al. included 21 chronic stroke patients with moderate to severe upper limb dysfunction for randomized intervention. The clinical function was evaluated before and after intervention by the Fugl-Meyer assessment of upper extremity (FMA-UE). The results showed that, compared with simple haptic knob (HK) robot intervention (HK group) and standard arm therapy intervention (SAT group), the motion gain effect of HK based on MI-BCI intervention (BCI-HK group) was significantly better than that of the other two groups8. However, the specific operation of MI-BCI still requires normative standards, and the mechanism of neural remodeling must be fully understood, which limits the clinical application and promotion of MI-BCI. Therefore, by showing the intervention process of MI-BCI in a 36-year-old male stroke patient with upper limb motor dysfunction, this study will summarize the functional outcome changes and brain function remodeling before and after the intervention to demonstrate the complete operation process of MI-BCI and provide ideas and references for clinical rehabilitation application and mechanism research.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>MI-BCI</td>
			<td>Rui Han, China</td>
			<td>RuiHan Bangde</td>
			<td>NA</td>
		</tr>
		<tr>
			<td>E-Prime&#160;</td>
			<td></td>
			<td>version 3.0</td>
			<td>behavioral research software.</td>
		</tr>
		<tr>
			<td>fNIRS</td>
			<td>Hui Chuang, China</td>
			<td>NirSmart-500</td>
			<td>NA</td>
		</tr>
		<tr>
			<td>NirSpark</td>
			<td></td>
			<td></td>
			<td>preprocess near-infrared data</td>
		</tr>
	</tbody>
</table>

motor imagery brain-computer interface in rehabilitation of upper limb motor dysfunction after stroke

The rehabilitation effect of patients with moderate or severe upper limb motor dysfunction after stroke is poor, which has been the focus of research owing to the difficulties encountered. Brain-computer interface (BCI) represents a hot frontier technology in brain neuroscience research. It refers to the direct conversion of the sensory perception, imagery, cognition, and thinking of users or subjects into actions, without reliance on peripheral nerves or muscles, to establish direct communication and control channels between the brain and external devices. Motor imagery brain-computer interface (MI-BCI) is the most common clinical application of rehabilitation as a non-invasive means of rehabilitation. Previous clinical studies have confirmed that MI-BCI positively improves motor dysfunction in patients after stroke. However, there is a lack of clinical operation demonstration. To that end, this study describes in detail the treatment of MI-BCI for patients with moderate and severe upper limb dysfunction after stroke and shows the intervention effect of MI-BCI through clinical function evaluation and brain function evaluation results, thereby providing ideas and references for clinical rehabilitation application and mechanism research.

Author Spotlight: Using Motor Imagery Brain-Computer Interface to Improve Motor and Cognitive Function in Stroke Patients

Motor Imagery Brain-Computer Interface in Rehabilitation of Upper Limb Motor Dysfunction After Stroke

This study focus on the clinical application of MI-BCI in stroke patients with moderate to severe upper limb motor dysfunction. And it provides ideas and references for the standardized clinical operation and mechanism research by demonstrating the operation process and intervention effect of MI-BCI. MI-BCI has present a positive effect on improving motor dysfunction in stroke patients.However, more clinical researches of this field will be done in the future to more appropriate treatment protocols for this different level of function in stroke patients. In this study, functional near-infrared spectroscopy, fNIRS, was used to monitor the concentration changes of hemoglobin and the oxygenating hemoglobin in the cerebral cortex in real time under different stimulation task. Thus providing imaging evidence for the clinical effect of MI-BCI.We present a protocol to use MI-BCI training on stroke patients for upper limb motor rehabilitation. The scores of Fugi-Meyer assessment of upper extremity and Wolf Motor Function Test was both improved after MI-BCI treatment. Meanwhile, the fNIRS assessment also showed more activation of dorsolateral prefrontal cortex, primary motor cortex, and primary sensory cortex.The findings suggest potential improvement in motor and cognitive function in stroke patients upon MI-BCI intervention. Original upper limb rehabilitation intervention methods, either peripheral intervention or central intervention. Whereas MI-BCI is based on the closed-loop principle of center, peripheral and center, or combined central model with peripheral motor feedback.The closed-loop principle is more fit for the characteristic of central nervous system disease.

The study presents the clinical function and remodeling of brain function before and after MI-BCI intervention in a 36-year-old male stroke patient. More than 4 months after cerebral hemorrhage, the imaging results showed chronic bleeding focus in the right frontal lobe and the right basal ganglia region-radiative crown region. The patient was diagnosed with left limb motor dysfunction during convalescence from a cerebral hemorrhage. Simple outpatient treatment of MI-BCI was performed in the hospital for 10 days (30 min/...

Watch this Scientific Journal Video about Motor Imagery Brain-Computer Interface in Rehabilitation of Upper Limb Motor Dysfunction After Stroke at JoVE.com

The purpose of this study is to provide an important reference for the standard clinical operation of motor imagery brain-computer interface (MI-BCI) for upper limb motor dysfunction after stroke.

The rehabilitation effect of patients with moderate or severe upper limb motor dysfunction after stroke is poor, which has been the focus of research ...

motor-imagery-brain-computer-interface-rehabilitation-upper-limb

Research

JoVE Journal

Neuroscience

Training and Clinical Evaluation of Motor Imagery Brain-Computer Interface

Begin by explaining the training purpose and method to the patient. Put the MIBCI EEG cap on the patient ensuring that the Cz point of the cap coincides with that of the patient's head. Confirm the position of the EEG cap by checking the intersection point of the ear bead line and the human median line passing through the nose and eyebrow center.Keep the ears exposed from the ear seam of the head cap and adjust the chinstrap to fix the head cap. Insert 24 electrodes dipped in normal saline into the groove of the EEG cap and clip two reference electrodes into the two ear lobes. Put the manipulator on the patient and adjust it to a comfortable training position to prevent upper limb forearm pain.Then open the training software MIBCI upper limb hand function rehabilitation robot. Click the user list and enter the patient information, including name, disease name, date of birth, date of illness, and location of the affected side. Adjust the stability of the EEG signal to no obvious clutter and click the resting EEG button.Let the patient complete the resting EEG acquisition process according to the voice and text prompts. Click the task setting button and according to the situation of the patient, set the initial training difficulty upward or downward from level nine. Also set the training duration to 30 minutes.Click the task EEG button to start the formal training. Ask the patient to follow the onscreen text that asks them to close their eyes and relax for five seconds. After five seconds, ask the patient to open their eyes and follow the onscreen commands.The screen on the patient's side displays the gripping or opening video to assist the patient to imagine the actions. Ask the patient to perform the motion imagination task for five seconds. After another four seconds, check the motor intention.If the intention is less than 60 points, the system determines that the patient cannot perform the movement. During the training, the MIBCI system will automatically adjust the task difficulty according to the patient's performance. For course movements, the task difficulty is simple, making it easier for the patient to complete.Conversely, for fine movements, the task becomes more difficult, making it challenging for the patient to complete. If the patient has pain or discomfort during the training, stop the training and record the reason for termination. During the training, observe the EEG waveform in real time.If there is a small range of EEG disturbances, check the corresponding electrode for dryness. Stop the training and EEG acquisition immediately and properly wet the electrode before continuing. If the EEG signal has an extensive range of disturbance, check whether the reference electrode has fallen off.Stop the training immediately and clamp the reference electrode at the ear lobe again. After the test, evaluate the motor function by Fugl-Meyer Assessment of Upper Extremity out of a total score of 66. Also, evaluate the Wolf Motor Function Test out of a total score of 85.Perform cognitive function assessment by mini mental state examination on stroke subjects and divide the score according to the educational level. Also, evaluate the emotional function on patients using Hamilton Anxiety Scale and calculate the scores during the assessment process. Then, evaluate the emotion function using the Hamilton Depression Scale.MIBCI intervention was performed on a 36-year-old male stroke patient diagnosed with left limb motor dysfunction. Brain function and clinical function assessment before and 10 days after treatment showed improvement in FMAUE and WMFT scores.

fNIRS Motor Task and Cognitive Assessment Before and After MI-BCI Treatment

Perform fNIRS Motor Task Assessment by selecting the motor test paradigm in the fNIRS system. Place the patient's upper limb on the test table and ask the patient to rest for 10 seconds before the experiment. Ask the patient to follow the exercise rhythm, to grasp the effect hand in three blocks during the experiment.Each block includes 30 seconds task and 30 seconds rest. Each task consists of 15 trials. Each trial includes one second gripping and one second opening of the grasp.During each rest, ask the patients to close their eyes and rest. After all three blocks are complete, end the task, save the data, and import it to the self-built database. To perform cognitive task assessment by Stroop task, run behavioral research software and choose the Cognitive Task paradigm.Select the patient treatment files and then select Congruence test. Ask the patient to place their healthy hand on the button of the keyboard. Then ask the patient to rest for 10 seconds before the trial starts.Perform three blocks of the congruence test. Each block includes 60 seconds task and 30 seconds rest. Each task consists of 10 trials, each consisting of 2, 000 millisecond fixation, and 4, 000 millisecond stimulus response.When the left symbol is displayed on the left of the field font, press the left arrow button on the keyboard as soon as possible. Similarly, press the right arrow button when the right symbol is displayed on the field font. Next, select the Incongruence test.When the right symbol is displayed on the left of the field font, ask the patient to ignore the character meaning, and press the left arrow button on the keyboard. Similarly, press right arrow button when left symbol is displayed on the screen. Complete the task, save the data, and export it to the self-created database.In a 36-year-old male stroke patient diagnosed with left limb motor dysfunction, fNIRS evaluation showed that for the motor task paradigm, the beta value of RM1 was higher after MIBCI treatment. Similarly, the beta value of bilateral DLPFC for the congruence test was higher for the post-treatment than that for the pre-treatment. Also, the beta value of all ROIs for the incongruence test was higher after treatment with MIBCI.The Stroop cognitive paradigm assessment results showed that for the congruence test, the accuracy rate remained unchanged and the response time became shorter after treatment. For the incongruence test, the accuracy rate remained unchanged, and the response time was shorter after treatment.

778 Views.  Guangzhou Medical University.  The purpose of this study is to provide an important reference for the standard clinical operation of motor imagery brain-computer interface (MI-BCI) for upper limb motor dysfunction after stroke.

Restoring Post-Stroke Motor Function by Motor Imagery Brain-Computer Interface

Summary