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Patients with chronic hemiplegic stroke undergo traditional physiotherapy (TPT) to improve walking ability, activity of daily living (ADL), balance, and pulmonary endurance. To mitigate these disabilities, we technologically advanced a convolutional neural network (CNN)-based rehabilitation application (CRA) that provides no physical therapy stress or contact to the therapist and offers sufficient repetition. The CRA evaluates patients’ balance, walking ability, ADL, and cardiopulmonary function like a suitable beneficial intervention, such as TPT. We compared the effects of CRA and TPT on the Berg Balance Scale (BBS), Rating of Perceived Exertion Scale, 6-min walking test, Functional Ambulation Category (FAC), and modified Barthel Index (MBI) in patients with stroke. A sample of 30 participants with hemiplegic stroke was randomized into either the CRA or TPT intervention group. CRA and TPT were managed for the participants, with each intervention session lasting 30 min and allocated three per week for five weeks. Analysis of variance was accomplished, and the level of significance was set at $p<$ 0.05. The ANOVA showed that CRA showed effects on the 6-min walking test result, BBS score, and MBI compared with TPT. Our novel results suggest that CRA can expand pulmonary endurance, balance, and ADL more effectively than TPT in patients with stroke.

Robot-assisted gait rehabilitation technology mitigates gait dysfunction caused by neurological conditions by focusing on functional impairments and activity limitations. However, it often neglects integrative robotic designs that address the international classification of functioning (ICF) domains, including impairments, activity limitations, and social community participation. To develop optimal social integration wearable gait-assisting robots for individuals with neurological gait dysfunction through a comprehensive robot design survey, a survey, including 192 participants with gait dysfunction across all age groups, was conducted to identify important demographic and clinical outcome variables and related robotic design features. Data were analyzed using qualitative, correlation, and ${\chi }^2$ analyses at $P<0.05$. This survey data identified important relationships between functional ambulation classification and awareness of robot ($r={0.391}^{\ast \ast },P=0.000$), Timed Up and Go (TUG) and robot satisfaction $(r={0.605}^{\ast \ast },P=0.002)$, gross motor function classification scale (GMFCS) levels and reason for using robots $(r={-0.351}^{\ast },P=0.018)$ and social participation, considering personal and environmental contextual factors. The correlation between lower TUG scores and higher robot satisfaction suggests that users with mobility challenges benefit more from the wearable gait assisting robot (“MIRACLE”), leading us to refine the interface and control mechanisms to further optimize ease of use and stability for individuals with slower walking speeds or greater balance impairments. This, in turn, results in more tailored assistance and improved user interaction with the robotic device. The survey data can contribute to designing effective, socially integrated robotic systems that will enhance mobility, independence, and social integration for pediatric and adult populations with gait dysfunction. By highlighting these connections in the abstract, we aim to provide a clearer picture of how the study’s results contribute to meaningful improvements in the design and function of the MIRACLE robots, aligning with the ultimate goal of enhancing mobility and user satisfaction.

This systematic review aims to investigate the efficacy of mirror therapy on the motor and sensory functions of the upper extremities in stroke patients. Literature from PubMed, Embase, CINAHL, and Web of Science databases was searched since their inception until March 8, 2023. Taking CINAHL as an example, the search strategy was formulated, and similar strategies were used for other databases. Four reviewers screened the literature according to the PICO principle, excluding literature related to patients with other neurological disorders, non-English literature, literature without full-text availability, study protocols, dissertations, conference abstracts, and reviews. Finally, 10 papers were selected from 1289 papers. Four researchers independently extracted data, determined the level of evidence using PEDro, and assessed the risk of bias in the literature based on the Cochrane Collaboration’s recommendations. The data synthesis indicates that mirror therapy significantly improves upper-extremity motor function, especially gross motor function, and enhances touch and temperature sensory functions by promoting the ability to distinguish different tactile stimuli. However, some studies have shown that mirror therapy does not significantly improve upper-extremity function in stroke patients. The operations of mirror therapy vary from motor-based to task-based, which may contribute to the variation in outcomes among studies. In conclusion, mirror therapy improves the upper-extremity motor function and has the potential to enhance the sensory function in stroke patients, yet more high-quality studies are still needed to provide evidence support.

The development of efficient stroke-detection methods is of significant importance in today's society due to the effects and impact of stroke on health and economy worldwide. This study focuses on Human Activity Recognition (HAR), which is a key component in developing an early stroke-diagnosis tool. An overview of the proposed global approach able to discriminate normal resting from stroke-related paralysis is detailed. The main contributions include an extension of the Genetic Fuzzy Finite State Machine (GFFSM) method and a new hybrid feature selection (FS) algorithm involving Principal Component Analysis (PCA) and a voting scheme putting the cross-validation results together. Experimental results show that the proposed approach is a well-performing HAR tool that can be successfully embedded in devices.

Motor rehabilitation based on the association of electroencephalographic (EEG) activity and proprioceptive feedback has been demonstrated as a feasible therapy for patients with paralysis. To promote long-lasting motor recovery, these interventions have to be carried out across several weeks or even months. The success of these therapies partly relies on the performance of the system decoding movement intentions, which normally has to be recalibrated to deal with the nonstationarities of the cortical activity. Minimizing the recalibration times is important to reduce the setup preparation and maximize the effective therapy time. To date, a systematic analysis of the effect of recalibration strategies in EEG-driven interfaces for motor rehabilitation has not yet been performed. Data from patients with stroke (4 patients, 8 sessions) and spinal cord injury (SCI) (4 patients, 5 sessions) undergoing two different paradigms (self-paced and cue-guided, respectively) are used to study the performance of the EEG-based classification of motor intentions. Four calibration schemes are compared, considering different combinations of training datasets from previous and/or the validated session. The results show significant differences in classifier performances in terms of the true and false positives (TPs) and (FPs). Combining training data from previous sessions with data from the validation session provides the best compromise between the amount of data needed for calibration and the classifier performance. With this scheme, the average true (false) positive rates obtained are 85.3% (17.3%) and 72.9% (30.3%) for the self-paced and the cue-guided protocols, respectively. These results suggest that the use of optimal recalibration schemes for EEG-based classifiers of motor intentions leads to enhanced performances of these technologies, while not requiring long calibration phases prior to starting the intervention.

Stroke, if not lethal, is a primary cause of disability. Early assessment of markers of recovery can allow personalized interventions; however, it is difficult to deliver indexes in the acute phase able to predict recovery. In this perspective, evaluation of electrical brain activity may provide useful information. A machine learning approach was explored here to predict post-stroke recovery relying on multi-channel electroencephalographic (EEG) recordings of few minutes performed at rest. A data-driven model, based on partial least square (PLS) regression, was trained on 19-channel EEG recordings performed within 10 days after mono-hemispheric stroke in 101 patients. The band-wise (delta: 1–4Hz, theta: 4–7Hz, alpha: 8–14Hz and beta: 15–30Hz) EEG effective powers were used as features to predict the recovery at 6 months (based on clinical status evaluated through the NIH Stroke Scale, NIHSS) in an optimized and cross-validated framework. In order to exploit the multimodal contribution to prognosis, the EEG-based prediction of recovery was combined with NIHSS scores in the acute phase and both were fed to a nonlinear support vector regressor (SVR). The prediction performance of EEG was at least as good as that of the acute clinical status scores. A posteriori evaluation of the features exploited by the analysis highlighted a lower delta and higher alpha activity in patients showing a positive outcome, independently of the affected hemisphere. The multimodal approach showed better prediction capabilities compared to the acute NIHSS scores alone ($r=0.53$ versus $r=0.41$, AUC = 0.80 versus AUC = 0.70, $p<0.05$). The multimodal and multivariate model can be used in acute phase to infer recovery relying on standard EEG recordings of few minutes performed at rest together with clinical assessment, to be exploited for early and personalized therapies. The easiness of performing EEG may allow such an approach to become a standard-of-care and, thanks to the increasing number of labeled samples, further improving the model predictive power.

Spasticity is a common post-stroke syndrome that imposes significant adverse impacts on patients and caregivers. This study aims to improve the efficiency of botulinum toxin (BoNT) in managing spasticity, by utilizing a three-dimensional innervation zone imaging (3DIZI) technique based on high-density surface electromyography (HD-sEMG) recordings. Stroke subjects were randomly assigned to two groups: the control group ($n=6$) which received standard ultrasound-guided injections, and the experimental group ($n=6$) which received 3DIZI-guided injections. The amount of BoNT given was consistent for all subjects. The Modified Ashworth Scale (MAS), compound muscle action potential (CMAP) and muscle activation volume (MAV) from bilateral biceps brachii muscles were obtained at the baseline, 3 weeks, and 3 months after injection. Intra-group and inter-group comparisons of MAS, CMAP amplitude and MAV were performed. An overall improvement in MAS of spastic elbow flexors was observed during the 3-week visit ($p<0.01$), yet no statistically significant difference found with intra-group or inter-group analysis. Compared to the baseline, a significant reduction of CMAP amplitude and MAV were observed in the spastic biceps muscles of both groups at 3-week post-injection, and returned to approximate baseline value at 12-week post injection. A significantly higher reduction was found in CMAP amplitude ($34.71\pm 5.42$% versus $20.92\pm 6.73$%, $p<0.01$) and MAV ($71.51\pm 8.20$% versus $44.33\pm 21.81$%, $p<0.05$) in the experimental group compared to the control group. The study has demonstrated preliminary evidence that precisely directing BoNT to the innervation zones (IZs) localized by 3DIZI leads to a significantly higher treatment efficiency improvement in spasticity management. Results have also shown the feasibility of developing a personalized BoNT injection technique for the optimization of clinical treatment for post-stroke spasticity using proposed 3DIZI technique.

The motor imagery brain–computer interface (MI-BCI) system is currently one of the most advanced rehabilitation technologies, and it can be used to restore the motor function of stroke patients. The deep learning algorithms in the MI-BCI system require lots of training samples, but the electroencephalogram (EEG) data of stroke patients is quite scarce. Therefore, the expansion of EEG data has become an important part of stroke clinical rehabilitation research. In this paper, a deep convolution generative adversarial network (DCGAN) model is proposed to generate artificial EEG data and further expand the scale of the stroke dataset. First, multichannel one-dimensional EEG data is converted into a two-dimensional EEG spectrogram using EEG2Image based on the modified S-transform. Then, DCGAN is used to artificially generate EEG data based on MI. Finally, the validity of the generated artificial EEG data is proved. This paper preliminarily indicates that generating artificial stroke data is a promising strategy, which contributes to the further development of stroke clinical rehabilitation.

Stroke patients are prone to fatigue during the EEG acquisition procedure, and experiments have high requirements on cognition and physical limitations of subjects. Therefore, how to learn effective feature representation is very important. Deep learning networks have been widely used in motor imagery (MI) based brain-computer interface (BCI). This paper proposes a contrast predictive coding (CPC) framework based on the modified s-transform (MST) to generate MST-CPC feature representations. MST is used to acquire the temporal-frequency feature to improve the decoding performance for MI task recognition. EEG2Image is used to convert multi-channel one-dimensional EEG into two-dimensional EEG topography. High-level feature representations are generated by CPC which consists of an encoder and autoregressive model. Finally, the effectiveness of generated features is verified by the k-means clustering algorithm. It can be found that our model generates features with high efficiency and a good clustering effect. After classification performance evaluation, the average classification accuracy of MI tasks is 89% based on 40 subjects. The proposed method can obtain effective feature representations and improve the performance of MI-BCI systems. By comparing several self-supervised methods on the public dataset, it can be concluded that the MST-CPC model has the highest average accuracy. This is a breakthrough in the combination of self-supervised learning and image processing of EEG signals. It is helpful to provide effective rehabilitation training for stroke patients to promote motor function recovery.

Stroke, an abrupt cerebrovascular ailment resulting in brain tissue damage, has prompted the adoption of motor imagery (MI)-based brain–computer interface (BCI) systems in stroke rehabilitation. However, analyzing electroencephalogram (EEG) signals from stroke patients poses challenges. To address the issues of low accuracy and efficiency in EEG classification, particularly involving MI, the study proposes a residual graph convolutional network (M-ResGCN) framework based on the modified S-transform (MST), and introduces the self-attention mechanism into residual graph convolutional network (ResGCN). This study uses MST to extract EEG time-frequency domain features, derives spatial EEG features by calculating the absolute Pearson correlation coefficient (aPcc) between channels, and devises a method to construct the adjacency matrix of the brain network using aPcc to measure the strength of the connection between channels. Experimental results involving 16 stroke patients and 16 healthy subjects demonstrate significant improvements in classification quality and robustness across tests and subjects. The highest classification accuracy reached 94.91% and a Kappa coefficient of 0.8918. The average accuracy and F1 scores from 10 times 10-fold cross-validation are 94.38% and 94.36%, respectively. By validating the feasibility and applicability of brain networks constructed using the aPcc in EEG signal analysis and feature encoding, it was established that the aPcc effectively reflects overall brain activity. The proposed method presents a novel approach to exploring channel relationships in MI-EEG and improving classification performance. It holds promise for real-time applications in MI-based BCI systems.

Synchronization between cerebral and peripheral circulation at the pre-stroke stage is discussed in newborn rats using a model of stress-induced hemorrhagic stroke. It is considered how the degree of coherence between the rhythmic components of the blood flow velocity is varied under normal and pathological conditions. It is shown that the degree of entrainment changes significantly after severe stress, provoking the transformation of normal vascular dynamics into pathological ones. Strong increase in the coherence measure is revealed, characterizing the entrainment in the dynamics of blood flow in the microvascular network surrounding the sagittal sinus and in the vein of the neck. Such changes can be considered as a precursor of the latent stage of stroke development in risk groups.

The effects of long-term oral administration of Choto-san (Diao-Teng-San in Chinese) extract on the occurrence of stroke and life span were investigated in stroke-prone spontaneously hypertensive rats (SHR-SPs). Twenty-four rats were ramdomized into three groups. From 8 weeks of age, 0.1% and 0.3% Choto-san groups were given water containing 0.1% (150 mg/kg/day) and 0.3% (450 mg/kg/day) Choto-san extract, respectively. A control group was given only water. The mean survival times of the control group, 0.1% and 0.3% Choto-san groups were 122.1, 159.8 and 176.8 days, respectively. The percent survivals of both the 0.1% and 0.3% Choto-san groups were significantly enhanced compared to the control (Kaplan-Meier analysis followed by log-rank test; 0.1% Choto-san: p < 0.05; 0.3% Choto-san: p < 0.05). Furthermore, the cumulative percent occurrence of neurological and behavioral signs accompanying stroke in the 0.3% Choto-san group was significantly inhibited compared to the control (p < 0.05). These results suggested that Choto-san prevents the occurrence of stroke and prolongs the life span of SHR-SPs.

Chungpyesagan-tang is one of the most well-known traditional herbal formulations frequently used for treatment of acute stroke in Korea. Therefore, this study aims to assess the clinical safety and efficacy of Chungpyesagan-tang on acute ischemic stroke. We recruited acute cerebral infarction subjects within 1 week after onset time. Then, we prescribed Chungpyesagan-tang to an Oriental medical treatment group (OM-group) for 2 weeks and enrolled a Western medical treatment group (WM-group) which received only Western biomedical care as a control. In this study, the OM-group was composed of 75 subjects. However, 14 of them dropped out, as two had progressive stroke while 12 complained of diarrhea. Thus, 61 cases were included in the analysis and compared to the 76 cases of the WM-group. The improvement of OM-group was better than that of the WM-group according to the National Institute of Health Stroke Scale (NIHSS), but not by the Modified Barthel Index (MBI). There were no definite abnormalities on laboratory safety assessment. Therefore, we suggest that Chungpyesagan-tang may have therapeutic effects, acting to reduce the severity of stroke and improving functional recovery without definite hepatic or renal toxicity when given for the first 2 weeks after a stroke.

Spasticity is a frequently observed motor impairment that develops after stroke. The objective of this study was to evaluate the efficacy of electroacupuncture (EA) and moxibustion (Mox) on spasticity due to stroke. The subjects consisted of 35 stroke patients with elbow spasticity whose mean duration of stroke was 2.97 months. Fifteen patients were randomized to the EA group, ten to Mox, and ten to control. Every other day, 30 minutes of electrical stimulation with a frequency of 50 Hz was given through four needles on the Ch'ü-Ch'ih-San-Li (LI-11-LI-10) and Wai-Kuan-Ho-Ku (TB-5-LI-4) points of the paretic side. Direct Mox was applied to Ch'ü-Ch'ih (LI-11), San-Li (LI-10), Wai-Kuan (TB-5) and Ho-Ku (LI-4) points three times a day every other day. The control group was given only the routine acupuncture therapy for stroke and range of motion (ROM) exercise, which were also applied to the EA and Mox groups. The efficacy of treatment was measured before, immediately, 1 hour, 3 hours, 1 day, 5 days, 10 days and 15 days after the start of treatment using a modified Ashworth scale (MAS). In the EA group, spasticity was significantly reduced immediately, 1 hour and 3 hours after treatment (p < 0.05). Reductions were significant on the 5th day and thereafter (p < 0.05). In the Mox group, there was no significant change in the MAS scores after the first treatment. In the Mox and control group, there was no significant change in MAS scores. This study suggests that EA can temporarily reduce spasticity due to stroke, and if applied repeatedly it can maintain reduced spasticity.

This is the first study that focuses on the effects of intradermal acupuncture on insomnia after stroke. We enrolled hospitalized stroke patients with insomnia and assigned them into a real intradermal acupuncture group (RA group) or a sham acupuncture group (SA group) by randomization. The RA group received intradermal acupuncture on Shen-Men (He-7) and Nei-Kuan (EH-6) for 2 days, and the SA group received sham acupuncture on the same points. The effectiveness was measured by the Morning Questionnaire (MQ), Insomnia Severity Index (ISI), and Athens Insomnia Scale (AIS). These scales were examined by an independent, blinded neurologist before, and 1 and 2 days after treatment, repeatedly. Thirty subjects (15 in the RA group and 15 in the SA group) were included in the final analysis. The RA group showed more improvement on insomnia than the SA group. Repeated measures analysis detected that there were significant between-subjects effects in the MQ, the ISI and the AIS. In conclusion, we suggest that intradermal acupuncture on Shen-Men and Nei-Kuan is a useful treatment for post stroke-onset insomnia.

Hypertension is one of the modifiable risk factors for stroke. Lowering blood pressure is helpful for primary and secondary prevention of stroke. This study is aimed to assess the efficacy of Chunghyul-dan on stroke patients with stage 1 hypertension using 24 hours ambulatory blood pressure monitoring (24ABPM). Forty hospitalized stroke patients with stage 1 hypertension were included in the study and they were randomly assigned into two groups: group A was treated with Chunghyul-dan 1200 mg once a day for 2 weeks, while group B was not. Twelve subjects were dropped out because of unexpected early discharge or data errors, thus the remaining 28 subjects were included in the final analysis (15 in group A and 13 in group B). Blood pressure was monitored every 30 minutes for 24 hours at baseline and 2 weeks after medication. Blood pressure, pulse rate, trough/peak ratio (TPR) [the value calculated by dividing the blood pressure change at trough (22 to 24 hours after drug intake) by the change at peak (2 adjacent hours with a maximal blood pressure reduction between the second and eighth hour after drug intake)] and smoothness index (SI) (the value calculated as the ratio between the average of the 24 hours, treatment-induced blood pressure changes and its standard deviation) were compared to assess the efficacy of Chunghyul-dan. To assess the safety of Chunghyul-dan, any adverse effects during medication period were monitored. There was no significant difference in the baseline assessment between the two groups. Systolic blood pressure was lower in group A than in group B (141.37 ± 8.96 mmHg versus 132.28 ± 9.46 mmHg, P = 0.03), while diastolic blood pressure and pulse rate had no significant difference between the two groups. Systolic TPR and SI was 0.87 and 1.04 in group A, respectively. This suggests that Chunghyul-dan have anti-hypertensive effect on stroke patients with stage 1 hypertension.

This study was conducted to test the effectiveness of moxibustion therapy for patients with post-stroke urinary symptoms using International Prostate Symptom Score (IPSS). Stroke patients with urinary symptoms were enrolled and assigned into the moxibustion group (MO group) and the control group by stratified randomization. The MO group received moxibustion treatment on Zhong-Ji (CV-3), Guan-Yuan (CV-4) and Qi-Hai (CV-6) for 10 days, and the control group did not receive it. The effectiveness of urinary symptoms and activities of daily living were measured by IPSS and Barthel Index (BI), respectively. These scales were examined by an independent blinded neurologist before treatment, and 10 days after therapy. Thirty nine subjects (20 in the MO group and 19 in the control group) were included in the final analysis. The MO group showed more improvement on urinary symptoms than the control group. In conclusion, we suggest that moxibustion on Zhong-Ji (CV-3), Guan-Yuan (CV-4) and Qi-Hai (CV-6) is effective to post-stroke urinary symptoms.

The disturbance of balance function is one of main etiology resulting in falling down in stroke patients. A number of studies report that acupuncture may improve the motor function of stroke patients. Therefore, the aim of the present study was to investigate the effect of acupuncture on balance function. We designed a single-blinded, controlled, randomized study. A total of 30 stroke patients were randomized into experimental and control groups. Experimental groups received acupuncture treatment accompanied by the manual twisting of needles and obtaining of qi (the subjects experienced sensations of soreness, numbness, swelling and heaviness, while the acupuncturist experienced a sensation of needle resistance), whereas the control group did not receive manual twisting of needles and without obtaining of qi. All of the subjects were first-time stroke patients; infarction location was limited to either the left or right hemisphere, and all subjects were able to walk for at least 6 meters. Acupuncture stimulation (AS) was applied to Baihui (GV 20) acupoint as well as to 4 spirit acupoints (1.5 cun anterior, posterior, left and right laterals from Baihui acupoint, respectively) for 20 min. Balance function outcome measures were: (1) the displacement area of the patient's center of gravity; (2) the time taken for a patient to stand vertically from a seated position; (3) the time taken for a patient to walk a distance of 6 meters; (4) muscle strength of both lower extremities. Results indicated that the displacement area from the center of gravity decreased in the experimental group, but not in the control group. There was greater reduction in the displacement area in the experimental group than in the control group. Following AS, the time taken to reach a standing position from a seated position, as well as the time taken to walk 6 meters was decreased equally in both the experimental and control groups. The muscle strength of the hip flexor and knee extensor were increased in the paralyzed and non-paralyzed sides of patients in the experimental group, but not in the control group. The results of the present study suggest that acupuncture stimulation may induce an immediate effect that improves balance function in stroke patients.

This study is a double-blind randomized controlled trial on the effect of intradermal acupuncture on insomnia after stroke. Hospitalized stroke patients with insomnia were enrolled in the study and were randomly assigned to either a real intradermal acupuncture group (RA group) or a sham acupuncture group (SA group). The RA group received intradermal acupuncture on Shen-Men (He-7) and Nei-Kuan (EH-6) for three days, and the SA group received sham acupuncture on the same points. The effect of acupuncture on insomnia was measured using Insomnia Severity Index (ISI) and Athens Insomnia Scale (AIS) at baseline and three days after treatment. To assess the effect of acupuncture on the autonomic nervous function, the subjects' blood pressure and heart rate variability were monitored. Fifty-two subjects (27 in the RA group and 25 in the SA group) were included in the final analysis. The insomnia-related scales ISI and AIS showed greater improvement of insomnia in the RA group than in the SA group. Moreover, there is a greater reduction of the number of non-dippers and a greater decrease of the LF/HF ratio (heart rate variability) in the RA group than in the SA group. These results indicate that sympathetic hyperactivities were stabilized in the RA group. It can thus be concluded that intradermal acupuncture on Shen-Men and Nei-Kuan is a useful therapeutic method for post stroke-onset insomnia as it reduces sympathetic hyperactivities.

As practice in folk medicine, Graptopetalum paraguayense E. Walther possesses several biological/pharmacological activities including hepatoprotective, anti-oxidant, and anti-inflammatory. We investigated the neuroprotective potential of Graptopetalum paraguayense E. Walther leaf extracts on inflammation-mediated ischemic brain injury. Water (GWE), 50% alcohol (GE50) extracts of Graptopetalum paraguayense E. Walther, and extracts obtained from further extraction of GE50 with ethyl acetate (GEE) were used. Oral administration of GEE, but not GWE or GE50, for 2 weeks protected animals against cerebral ischemia/reperfusion brain injury. The neuroprotective effect of GEE was accompanied by reductions in brain infarction, neurological deficits, caspase-3 activity, malondialdehyde content, microglia activation, and inducible nitric oxide synthase (iNOS) expression. Since microglia-mediated inflammation plays critical roles in ischemic brain injury, anti-inflammatory potential of Graptopetalum paraguayense E. Walther leaf extracts was further investigated on lipopolysaccharide (LPS)/interferon-γ (IFN-γ-activated BV-2 microglial cells. GEE decreased H₂O₂- and LPS/IFN-γ-induced free radical generation and LPS/IFN-γ-induced iNOS expression. Mechanistic study revealed that the neuroactive effects of GEE were markedly associated with anti-oxidative potential, activation of serine/threonine and tyrosine phosphatases, and down-regulation of extracellular signal-regulated kinase, c-Jun N-terminal kinase, p38, Akt, Src, Janus kinase-1, Tyk2, signal transducer and activator of transcription-1, and NF-κB and might be attributed to the presence of polyphenolic compounds such as gallic acid, genistin, daidzin, and quercetin. Together, our findings point out its potential therapeutic strategies that target microglia activation, oxidative stress, and iNOS expression to reduce ischemic brain injury and suggest that Graptopetalum paraguayense E. Walther leaf extracts represent a valuable source for the development of neuroprotective agents.