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 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.
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.
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
2. MI-BCI training
NOTE: The rehabilitation robot for upper limb hand function based on motor imagery is selected in this study. The device comprises an electroencephalogram (EEG) cap (Figure 1A), a computer terminal (i.e., control interface; Figure 1B), an external manipulator (Figure 1E), and a 23 inch computer display screen (Figure 1C).
3. Clinical evaluation
4. fNIRS brain function assessment
For this study, place 10 sources and 12 detectors on the fNIRS test head caps to correspond to the eight regions of interest (ROIs) in this study, including the bilateral dorsolateral prefrontal cortex (DLPFC), the dorsolateral promoter cortex (PMC), the dorsolateral primary motor cortex (M1), and the dorsolateral primary sensory cortex (S1; Figure 2).
5. Post-treatment
6. Data processing and analysis
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/session/day) and brain function assessment and clinical function assessment were completed before and 10 days after treatment (Figure 5). The results of clinical evaluation before and after treatment were FMA-UE = 12/14 (before/after); WMFT (scores) = 33/34; WMFT (s) = 127.43/90.91; MMSE = 30/30; HAMA = 6/0; HAMD = 4/0 (Table 1).
The Stroop cognitive paradigm assessment results showed that the ACC of the congruence test and the incongruence test was the same in the pre-treatment while the RT of the incongruence test was longer than that of the congruence test (ACCCongruence = ACCIncongruence = 100%, RTCongruence = 856.6 ms, RTIncongruence = 880.7 ms). The ACC of the congruence test and the incongruence test was the same in the post-treatment and the RT of the incongruence test was also longer than that of the congruence test (ACCCongruence = ACCIncongruence = 100%, RTCongruence = 803.2 ms, RTIncongruence = 870.1 ms). It could be seen from the comparison before and after treatment that for the congruence test, the ACC remained unchanged and the RT became shorter after treatment (ACCPre = ACCPost = 100%, RTPre = 856.6 ms, RTPost = 803.2 ms). For the incongruence test, the ACC remained unchanged, and the RT was shorter after treatment (ACCPre = ACCPost = 100%, RTPre = 880.7 ms, RTPost = 870.1 ms; Table 2).
The results of the fNIRS evaluation showed that the beta value of R-M1 in the post-treatment was higher than that in the motor task paradigm of the pre-treatment (R-M1Pre = 0.016, R-M1Post = 0.044). The beta value of bilateral DLPFC in the post-treatment was higher than that in the congruence test of the pre-treatment (R-DLPFCPre = 0.009, R-DLPFCPost = 0.010; L-DLPFCPre = -0.062, L-DLPFCPost = 0.003). The beta value of all ROIs in the post-treatment was higher than that in the incongruence test of the pre-treatment (R-DLPFCPre = -0.032, R-DLPFCPost = 0.030; L-DLPFCPre = -0.007, L-DLPFCPost = 0.026; R-PMCPre = 0.014, R-PMCPost = 0.087; L-PMCPre = 0.030, L-PMCPost = 0.111; R-S1Pre = -0.035, R-S1Post = 0.081; L-S1Pre = 0.024, L-S1Post = 0.081; R-M1Pre = 0.000, R-M1Post = 0.025; L-M1Pre = 0.031, L-M1Post = 0.093). The rest of the brain regions and their data are shown in Figure 6 and Table 3, respectively.
Figure 1. Diagram of the motor imagery brain computer interface (MI-BCI) upper limb rehabilitation training system. (A) Patients wear MI-BCI EEG caps. (B) The patient side display provides motor imagery. (C) EEG display screen. (D) The MI-BCI system analyzes and interprets the EEG signal. (E) The robotic arm for motion performing and feedback. Patients wearing MI-BCI EEG caps perform motor imagery according to the motion images provided by the patient side display, and the MI-BCI system based on EEG analyzes and interprets the patient's EEG signal. The robotic arm provides corresponding feedback according to the patient's motion intention score. Please click here to view a larger version of this figure.
Figure 2. Regions of interest and the channel setting. In the protocol, eight regions of interest (ROIs) were selected, including the bilateral dorsolateral prefrontal cortex (DLPFC), the dorsolateral promoter cortex (PMC), the dorsolateral primary motor cortex (M1), and the dorsolateral primary sensory cortex (S1). Abbreviations: DLPFC = prefrontal cortex; PMC = premotor cortex; M1 = primary motor cortex; S1 = primary sensory cortex. Please click here to view a larger version of this figure.
Figure 3. The Motor task paradigm and the fNIRS design. The motor task paradigm lasted 190 s and included a resting state rest of 10 s and three blocks, each block includes 30 s task and 30 s rest. Each task consists of 15 trials, each trial includes 1 s gripping and 1 s opening of the grasp. Please click here to view a larger version of this figure.
Figure 4. The Stroop paradigm and the fNIRS design. The congruence test lasted 280 s and included a resting state rest of 10 s and three blocks, each block includes 60 s task and 30 s rest. Each task consists of 10 trials, each consisting of 2000 ms fixation and 4000 ms stimulus-response. The procedure of the incongruence test is the same as that of the congruence test. Abbreviations: = left; = right. Please click here to view a larger version of this figure.
Figure 5. MI-BCI training timeline. The protocol included 10 days of outpatient treatment (30 min/session/day) and brain function assessment and clinical function assessment were completed before and 10 days after treatment. Please click here to view a larger version of this figure.
Figure 6. ROIs activation in the stroke patient before and after treatment. The beta values are indicated by color. The color bar represents intensity of activation of each region, in which blue means less activation whereas red means more activation. The results of the fNIRS evaluation showed that the beta value of R-M1 in the post-treatment was higher than that in the motor task paradigm of the pre-treatment. The beta value of bilateral DLPFC in the post-treatment was higher than that in the congruence test of the pre-treatment. The beta value of all ROIs in the post-treatment was higher than that in the incongruence test of the pre-treatment. Abbreviations:L-DLPFC = left dorsolateral prefrontal cortex; R-DLPFC = right dorsolateral prefrontal cortex; L-PMC = left promoter cortex; R-PMC = right promoter cortex; L-M1 = left primary motor cortex; R-M1 = right primary motor cortex; L-S1 = left primary sensory cortex; R-S1 = right primary sensory cortex; L = left; R= right. Please click here to view a larger version of this figure.
Clinical function evaluation | Pre-treatment | Post-treatment |
FMA-UE (scores) | 12 | 14 |
WMFT (scores) | 33 | 34 |
WMFT(s) | 127.43 | 90.91 |
MMSE (scores) | 30 | 30 |
HAMA (scores) | 6 | 0 |
HAMD (scores) | 4 | 0 |
Table 1 Results of clinical function assessment before and after MI-BCI training. FMA-UE and WMFT were used to assess patients' motor function, MMSE was used to assess patients' cognitive function, and HAMA and HAMD were used to assess patients' emotional function. Abbreviations: FMA-UE = Fugl-Meyer assessment-upper extremity; WMFT = Wolf motor function test; MMSE = Mini-Mental State Examination; HAMA = Hamilton Anxiety Scale; HAMD = Hamilton Depression Scale.
Pre-treatment | Post-treatment | ||
Congruence test | ACC (%) | 100% | 100% |
RT (ms) | 856.6 | 803.2 | |
Incongruence test | ACC (%) | 100% | 100% |
RT (ms) | 880.7 | 870.1 |
Table 2 Results of congruence test and incongruence test based on Stroop cognitive paradigm. The Stroop cognitive paradigm assessment results showed that the ACC of the congruence test and the incongruence test were the same in the pre-treatment while the RT of the incongruence test was longer than that of the congruence test. The ACC of the congruence test and the incongruence test was the same in the post-treatment and the RT of the incongruence test was also longer than that of the congruence test. It could be seen from the comparison before and after treatment that for the congruence test, the ACC remained unchanged, and the RT became shorter after treatment. For the incongruence test, the ACC remained unchanged, and the RT was shorter after treatment. Abbreviations: ACC = accuracy; RT = reaction time.
Motor task paradigm | Congruence test trials | Incongruence test trials | ||||
Pre-treatment | Post-treatment | Pre-treatment | Post-treatment | Pre-treatment | Post-treatment | |
RDLPFC | 0.041 | 0.008 | 0.009 | 0.010 | -0.032 | 0.030 |
LDPFC | 0.022 | -0.032 | -0.062 | 0.003 | -0.007 | 0.026 |
RPMC | 0.054 | 0.045 | -0.006 | -0.036 | 0.014 | 0.087 |
LPMC | -0.009 | -0.059 | 0.034 | -0.011 | 0.030 | 0.111 |
RS1 | 0.053 | 0.004 | -0.021 | -0.051 | -0.035 | 0.081 |
LS1 | 0.048 | -0.038 | 0.026 | 0.001 | 0.024 | 0.081 |
RM1 | 0.016 | 0.044 | -0.025 | -0.047 | 0.000 | 0.025 |
LM1 | 0.026 | -0.009 | 0.036 | 0.036 | 0.031 | 0.093 |
Table 3 Changes of ROIs beta values in the stroke patient before and after treatment. The results of the fNIRS evaluation showed that the beta value of R-M1 in the post-treatment was higher than that in the motor task paradigm of the pre-treatment. The beta value of bilateral DLPFC in the post-treatment was higher than that in the congruence test of the pre-treatment. The beta value of all ROIs in the post-treatment was higher than that in the incongruence test of the pre-treatment. Abbreviations: L-DLPFC = left dorsolateral prefrontal cortex; R-DLPFC = right dorsolateral prefrontal cortex; L-PMC = left promoter cortex; R-PMC = right promoter cortex; L-M1 = left primary motor cortex; R-M1 = right primary motor cortex; L-S1 = left primary sensory cortex; R-S1 = right primary sensory cortex; L = left; R = right.
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 rehabilitation effects20. Therefore, it is of great significance to continuously develop new stroke rehabilitation techniques/strategies21. MI-BCI has good clinical application potential as a non-invasive means of rehabilitation and has been gradually promoted22. In this study, MI-BCI was adopted as an intervention method to collect EEG signals generated by brain motor imagery, analyze and decode the patient's intention to move the affected limb, convert them (the patient's intention) into action instructions to control external devices, and feed them back to the brain through audio-visual and tactile feedback, thus forming a central-peripheral-central closed-loop system23. This method is more in line with the rehabilitation characteristics of central nervous system diseases and theoretically is more conducive to promoting the functional remodeling of injured cerebral nerves24.
The following points must be noted and explained in the MI-BCI training. First, contraindications must be clear before treatment. In addition to the contraindications mentioned in the exclusion criteria in recruitment, the operator should ensure that there are no fresh wounds on the subject's head prior to treatment. Since the process of wearing the EEG cap requires the sponge to be filled with saline and placed in the slot, there is a risk of wound infection if the subject has head trauma. Second, for patients with severe upper limb spasms, it is necessary to clarify the degree of spasm and pain and to determine whether wearing the manipulator will increase the degree of pain. If the patient cannot tolerate it, the training should be terminated. For patients with shoulder subluxation, pillows should be placed on the elbow to avoid aggravating the degree of subluxation. Third, in the preparation stage of MI-BCI training, the correct wearing of the EEG cap is very important for decoding EEG data during training. The wearing of the EEG cap should strictly follow the international 10-20 system to ensure that the Cz site on the EEG cap corresponds to the Cz site on the top of the subject's head9,10,11. Recalibration is required if the EEG cap shifts during training. Fourth, the MI-BCI operation process has strict requirements regarding the environment. MI-BCI requires subjects to concentrate intently to complete active motor imagery, and a noisy environment will affect patients' concentration. Fifth, attention should be paid to the fatigued condition of patients in the training process. MI-BCI training requires the patient to constantly perform motor imagery; for patients in high-intensity, long-time, focused training who are prone to fatigue, sleepiness, and sedentary discomfort, the operator must pay attention to the patient's physical condition. If it is necessary, the patient can take a break. If the above conditions cannot be improved, training can be terminated.
In this study protocol, FMA-UE and WMFT scores of patients increased before and after the treatment, suggesting an improvement trend in the motor function performance of patients. Accordingly, eight ROIs were selected for fNIRS brain function assessment in this study, including bilateral DLPFC, PMC, M1, and S1. The results showed that M1 of the affected side was activated after MI-BCI intervention in the motor task monitored by synchronous fNIRS. At the same time, bilateral DLPFC were activated in the Stroop congruence test and the incongruence test, and M1 and S1 were activated in the Stroop incongruence test, suggesting that MI-BCI intervention might have positive effects on the motor and cognitive function of stroke patients. The above results can provide a reference for subsequent MI-BCI-related cerebral nerve remodeling mechanisms and be of significance for further research on MI-BCI-related mechanisms.
This protocol has some limitations. First, this study presented a treatment plan for MI-BCI in patients with moderate and severe upper limb dysfunction after stroke and described the efficacy of MI-BCI, 10 days after intervention through clinical function evaluation and brain function evaluation results. However, this study protocol included only one stroke patient. Therefore, further verification should be conducted with a larger sample size in the future. Second, this study intervened for only 10 sessions; the long-term efficacy of MI-BCI requires further improvement in future studies. Moreover, this study used only the MI-BCI paradigm, which does not apply to stroke patients with cognitive dysfunction. BCI under other paradigms should be explored in future clinical practice to meet the rehabilitation needs of patients with cognitive dysfunction.
The authors have nothing to disclose.
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).
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 |