Brain–computer interface treatment for gait rehabilitation in stroke patients

Stroke is a leading cause of mortality and long-term disability globally, often resulting in lower limb functional deficits, which significantly impact patients’ quality of life. Despite extensive therapy efforts, many stroke survivors experience permanent impairments, including compromised gait ability. Various rehabilitation methods have been developed to address gait recovery, with recent studies focusing on interventions such as electromechanical-assisted training and functional electrical stimulation (FES).

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A 2018 study by Mehrholz et al. conducted a network meta-analysis to evaluate the effectiveness of different interventions for gait rehabilitation post-stroke. The study found that end-effector-assisted training (EGAIT_EE) significantly improved walking speed compared to conventional walking rehabilitation. Additionally, passive therapies like FES have shown promise in reducing muscle spasms and aiding in motor recovery.

BCI Integration Revolutionizes Rehabilitation Therapy for Enhanced Motor Recovery

Recent advancements in rehabilitation therapy involve the integration of Brain-Computer Interfaces (BCIs) to enhance motor imagery (MI) and provide closed-loop feedback. MI-based BCIs offer a novel approach to rehabilitation by enabling patients to engage in mental tasks associated with movement, thus facilitating neural reorganization and motor recovery. Studies have demonstrated the efficacy of combining BCI technology with FES feedback, suggesting that real-time sensory feedback based on patients’ movement intention may lead to better rehabilitation outcomes, including improvements in walking speed.

This clinical trial aims to investigate the effectiveness of combining BCI technology with MI and FES feedback for lower limb motor recovery in stroke patients. By exploring the relationship between this novel rehabilitation method and therapy outcomes, including changes in walking speed, the study seeks to provide insights into optimizing stroke rehabilitation strategies. Comparisons will be made with traditional therapies such as EGAIT_EE, highlighting the potential benefits of integrating BCI technology into rehabilitation programs.

Austrian Study Shows Promising Results for BCI-Enhanced Stroke Therapy

The study, approved by Ethikkommission des Landes Oberösterreich and Bundesamt für Sicherheit im Gesundheitswesen in Austria, involved stroke patients undergoing Brain-Computer Interface (BCI)-supported Motor Imagery (MI) training. Participants provided consent and underwent assessments pre and post-intervention. Inclusion criteria involved neurological stability and ability to follow instructions. Exclusion criteria included medical conditions affecting participation. 22 patients, predominantly in the chronic phase, remained after withdrawals. Functional baseline remained stable pre-intervention. Personal data and functional assessments, including gait speed via 10 Meter Walking Test (10MWT), Timed Up and Go (TUG), Berg Balance Scale (BBS), and Functional Ambulation Classification (FAC), were recorded. The study aimed to evaluate improvements in gait, balance, range of motion, motor function, and cognition.

The study employed various assessment scales and tests to evaluate the effects of Brain-Computer Interface (BCI) therapy on motor and cognitive functions in patients with neurological conditions. Spasticity was assessed using the Modified Ashworth Scale (MAS), with specific scales for ankle (MASAnkle) and knee (MASKnee) spasticity. Range of motion (ROM) for ankle and knee movements was analyzed using a digital goniometer. Muscle strength of the ankle and knee was measured with the Manual Muscle Test (MMT), and motor impairment was evaluated using the Fugl Meyer Assessment (FMA) for upper and lower extremities. The Barthel Index (BI) was utilized to assess daily living activities.

Cognitive function was evaluated using the Stroop Color-Word Test (SCWT) and the Montreal Cognitive Assessment (MOCA). EEG caps with electrodes were used for brain signal detection, and Functional Electrical Stimulation (FES) was applied to induce movement. Participants were instructed to imagine movements during Motor Imagery (MI) tasks, with EEG signals processed using common spatial patterns (CSP) and linear discriminant analysis (LDA) for classification. Offline classification accuracy was estimated through 10-fold cross-validation.

Statistical analysis involved paired sample t-tests or Wilcoxon signed rank tests for comparing assessment outcomes within the same group of patients, with p-values corrected using False Discovery Rate (FDR) for multiple comparisons. Functional improvements were analyzed at different time points post-therapy: immediately after therapy (Post1), one month (Post2), and six months (Post3).

“Promising Results: BCI Therapy Improves Gait and Motor Function in Stroke Patients

The study involved obtaining written informed consent from participants for potential publication of identifiable images or data. Twenty-seven patients were initially assessed, with two excluded due to stroke location not meeting criteria. The remaining twenty-five were assigned to the BCI intervention group, but three dropped out, two due to transportation issues and one due to loss of interest. Consequently, twenty-two patients completed BCI sessions, whose results were analyzed further.

The study evaluated various tests for gait function and balance, including the 10 Meter Walk Test (10MWT) and Timed Up and Go (TUG) test. Significant improvements were observed in both 10MWT parameters (Self-Selected Velocity and Fast Velocity), with reduced test times and increased speeds post-therapy. TUG test results also showed significant improvements in both test time and speed.

Functional Ambulation Classification (FAC) scores improved for two patients. However, the Berg Balance Test (BBS) indicated minimal improvement due to ceiling effects. Active range of motion (ROM) improvements were significant for ankle and knee flexion and ankle dorsiflexion, both in active and passive movements. Spasticity in the ankle decreased significantly post-therapy, as measured by the Modified Ashworth Scale (MAS). Manual Muscle Tests (MMT) showed significant improvements in ankle flexion, ankle dorsiflexion, and knee extension, with slight improvements in knee flexion.

The study evaluated the effectiveness of a therapy program for stroke patients focusing on motor function, cognitive abilities, and daily living activities. Motor function of upper and lower extremities was assessed using the Fugl-Meyer Assessment (FMA). Although there were improvements in FMA scores, they were not statistically significant. However, daily living activities assessed by the Barthel Index showed a significant improvement. Cognitive abilities were evaluated using the Montreal Cognitive Assessment and the Stroop Color Word test, with mixed results.

BCI Therapy Exhibits Long-term Upper Limb and Gait Improvements in Stroke Patients

Long-term effects were analyzed, showing significant improvement in upper limb functionality and comfortable gait speed six months after therapy. The therapy involved a Brain-Computer Interface (BCI) system, which showed positive results in motor imagery accuracy and gait speed improvement. Comparisons with other rehabilitation techniques, such as electromechanical gait devices and functional electrical stimulation, were made, indicating comparable improvements in gait speed.

BCI Therapy Discussion Highlights Assessment Sensitivity and Future Research Needs

Discussion points included the sensitivity of assessment scales, particularly the FMA-LE, in detecting changes in gait ability and the limitations of the study, including the lack of a control group and the chronic stage of stroke patients.

Despite limitations, the therapy showed no adverse events, was conducted ethically, and obtained patients’ consent. Further research with larger sample sizes and control groups could provide more insights into the effectiveness of the therapy.

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