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

Published: September 01, 2023

doi:

Summary

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.

Abstract

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.

Introduction

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.

Protocol

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 Inclusion criteria Recruit patients who meet the diagnostic criteria of stroke formulated …

Representative Results

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/…

Discussion

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…

Divulgations

The authors have nothing to disclose.

Acknowledgements

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, 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).

Materials

MI-BCI	Rui Han, China	RuiHan Bangde	NA
E-Prime		version 3.0	behavioral research software.
fNIRS	Hui Chuang, China	NirSmart-500	NA
NirSpark			preprocess near-infrared data

References

Dawson, J., et al. Vagus nerve stimulation paired with rehabilitation for upper limb motor function after ischaemic stroke (VNS-REHAB): a randomised, blinded, pivotal, device trial. Lancet. 397 (10284), 1545-1553 (2021).
Lin, Q., et al. The Frequency Effect of the Motor Imagery Brain Computer Interface Training on Cortical Response in Healthy Subjects: A Randomized Clinical Trial of Functional Near-Infrared Spectroscopy Study. Frontiers in Neuroscience. 16, 810553 (2022).
Carino-Escobar, R. I., et al. Longitudinal Analysis of Stroke Patients’ Brain Rhythms during an Intervention with a Brain-Computer Interface. Neural Plasticity. 2019, 7084618 (2019).
Mane, R., Chouhan, T., Guan, C. BCI for stroke rehabilitation: motor and beyond. Journal of Neural Engineering. 17 (4), 041001 (2020).
Khan, M. A., Das, R., Iversen, H. K., Puthusserypady, S. Review on motor imagery based BCI systems for upper limb post-stroke neurorehabilitation: From designing to application. Computers In Biology And Medicine. 123, 103843 (2020).
Hendricks, H. T., van Limbeek, J., Geurts, A. C., Zwarts, M. J. Motor recovery after stroke: a systematic review of the literature. Archives of Physical Medicine and Rehabilitation. 83 (11), 1629-1637 (2002).
Cheng, N., et al. Brain-Computer Interface-Based Soft Robotic Glove Rehabilitation for Stroke. IEEE Transactions on Biomedical Engineering. 67 (12), 3339-3351 (2020).
Ang, K. K., et al. Brain-computer interface-based robotic end effector system for wrist and hand rehabilitation: results of a three-armed randomized controlled trial for chronic stroke. Frontiers in Neuroengineering. 7, 30 (2014).
Nuwer, M. R., et al. IFCN standards for digital recording of clinical EEG. The International Federation of Clinical Neurophysiology. Electroencephalography and Clinical Neurophysiology. 52, 11-14 (1999).
Klem, G. H., Lüders, H. O., Jasper, H. H., Elger, C. The ten-twenty electrode system of the International Federation. The International Federation of Clinical Neurophysiology. Electroencephalography and Clinical Neurophysiology. 52, 3-6 (1999).
Uwe Herwig, ., Peyman Satrapi, ., Schönfeldt-Lecuona, C. Using the international 10-20 EEG system for positioning of transcranial magnetic stimulation. Brain Topography. , (2003).
Mane, R., Robinson, N., Vinod, A. P., Lee, S. W., Guan, C. A Multi-view CNN with Novel Variance Layer for Motor Imagery Brain Computer Interface. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. 2020, 2950-2953 (2020).
Sanford, J., Moreland, J., Swanson, L. R., Stratford, P. W., Gowland, C. Reliability of the Fugl-Meyer assessment for testing motor performance in patients following stroke. Physical Therapy. 73 (7), 447-454 (1993).
Martinez, C., et al. A Reaching Performance Scale for 2 Wolf Motor Function Test Items. Archives of Physical Medicine and Rehabilitation. 101 (11), 2015-2026 (2020).
Dufouil, C., et al. Population norms for the MMSE in the very old: estimates based on longitudinal data. Mini-Mental State Examination. Neurology. 55 (11), 1609-1613 (2000).
Thompson, E. Hamilton Rating Scale for Anxiety (HAM-A). Occupational Medicine. 65 (7), 601 (2015).
Zimmerman, M., Martinez, J. H., Young, D., Chelminski, I., Dalrymple, K. Severity classification on the Hamilton Depression Rating Scale. Journal of Affective Disorders. 150 (2), 384-388 (2013).
Bai, X., et al. Different Therapeutic Effects of Transcranial Direct Current Stimulation on Upper and Lower Limb Recovery of Stroke Patients with Motor Dysfunction: A Meta-Analysis. Neural Plasticity. 2019, 1372138 (2019).
Dimyan, M. A., Cohen, L. G. Neuroplasticity in the context of motor rehabilitation after stroke. Nature Reviews Neurology. 7 (2), 76-85 (2011).
Bai, Z., Fong, K. N. K., Zhang, J. J., Chan, J., Ting, K. H. Immediate and long-term effects of BCI-based rehabilitation of the upper extremity after stroke: a systematic review and meta-analysis. Journal of NeuroEngineering and Rehabilitation. 17 (1), 57 (2020).
Yang, W., et al. The Effect of Brain-Computer Interface Training on Rehabilitation of Upper Limb Dysfunction After Stroke: A Meta-Analysis of Randomized Controlled Trials. Frontiers in Neuroscience. 15, 766879 (2021).
Pandian, S., Arya, K. N. Stroke-related motor outcome measures: do they quantify the neurophysiological aspects of upper extremity recovery. Journal of Bodywork and Movement Therapies. 18 (3), 412-423 (2014).
Potter, S. M., El Hady, A., Fetz, E. E. Closed-loop neuroscience and neuroengineering. Frontiers in Neural Circuits. 8, 115 (2014).
Nowak, D. A., Grefkes, C., Ameli, M., Fink, G. R. Interhemispheric competition after stroke: brain stimulation to enhance recovery of function of the affected hand. Neurorehabilitation and Neural Repair. 23 (7), 641-656 (2009).