Effects of Robot-Aided Rehabilitation on the Ankle Joint Properties and Balance Function in Stroke Survivors: A Randomized Controlled Trial

A compact motorized end-effector for ankle rehabilitation training

This paper introduces a compact end-effector ankle rehabilitation robot (CEARR) system for addressing ankle range of motion (ROM) rehabilitation. The CEARR features a bilaterally symmetrical rehabilitation structure, with each side possessing three degrees of freedom (DOF) driven by three independently designed actuators. The working intervals of each actuator are separated by a series connection, ensuring they operate without interference to accommodate the dorsiflexion/plantarflexion (DO/PL), inversion/eversion (IN/EV), and adduction/abduction (AD/AB) DOF requirements for comprehensive ankle rehabilitation. In addition, we integrated an actuator and foldable brackets to accommodate patients in varied postures. We decoded the motor intention based on the surface electromyography (sEMG) and torque signals generated by the subjects' ankle joints in voluntary rehabilitation. Besides, we designed a real-time voluntary-triggered control (VTC) strategy to enhance the rehabilitation effect, in which the root mean square (RMS) of sEMG was utilized to trigger and adjust the CEARR rehabilitation velocity support. We verified the consistency of voluntary movement with CEARR rehabilitation support output for four healthy subjects on a nonlinear sEMG signal with anR 2 metric of approximately 0.67. We tested the consistency of triggering velocity trends with a linear torque signal for one healthy individual with anR 2 metric of approximately 0.99.

CAMBA framework: Unveiling the brain asymmetry alterations and longitudinal changes after stroke using resting-state EEG

Hemispheric asymmetry or lateralization is a fundamental principle of brain organization. However, it is poorly understood to what extent the brain asymmetries across different levels of functional organizations are evident in health or altered in brain diseases. Here, we propose a framework that integrates three degrees of brain interactions (isolated nodes, node-node, and edge-edge) into a unified analysis pipeline to capture the sliding window-based asymmetry dynamics at both the node and hemisphere levels. We apply this framework to resting-state EEG in healthy and stroke populations and investigate the stroke-induced abnormal alterations in brain asymmetries and longitudinal asymmetry changes during poststroke rehabilitation. We observe that the mean asymmetry in patients was abnormally enhanced across different frequency bands and levels of brain interactions, with these abnormal patterns strongly associated with the side of the stroke lesion. Compared to healthy controls, patients displayed significant alterations in asymmetry fluctuations, disrupting and reconfiguring the balance of inter-hemispheric integration and segregation. Additionally, analyses reveal that specific abnormal asymmetry metrics in patients tend to move towards those observed in healthy controls after short-term brain-computer interface rehabilitation. Furthermore, preliminary evidence suggests that baseline clinical and asymmetry features can predict poststroke improvements in the Fugl-Meyer assessment of the lower extremity (mean absolute error of about 2). Overall, these findings advance our understanding of hemispheric asymmetry. Our framework offers new insights into the mechanisms underlying brain alterations and recovery after a brain lesion, may help identify prognostic biomarkers, and can be easily extended to different functional modalities.

The Effect of Robot-Assisted Training on Arm Function, Walking, Balance, and Activities of Daily Living After Stroke: A Systematic Review and Meta-Analysis

This meta-analysis aimed to compare the effects of robot-assisted training (RAT) with those of conventional therapy (CT), considering the potential sources of heterogeneity in the previous studies. We searched three international electronic databases (MEDLINE, Embase, and the Cochrane Library) to identify relevant studies. Risk of bias assessment was performed using the Cochrane's Risk of Bias 1.0 tool. The certainty of the evidence was evaluated using the Grading of Recommendations, Assessment, Development, and Evaluations method. The meta-analyses for each outcome of the respective domains were performed using 24 randomized controlled trials (RCTs) on robot-assisted arm training (RAAT) for arm function, 7 RCTs on RAAT for activities of daily living (ADL), 12 RCTs on robot-assisted gait training (RAGT) for balance, 6 RCTs on RAGT for walking, and 7 RCTs on RAGT for ADL. The random-effects model for the meta-analysis revealed that RAAT has significant superiority over CT in improving arm function, and ADL. We also showed that RAGT has significant superiority over CT in improving balance. Our study provides high-level evidence for the superiority of RAT over CT in terms of functional recovery after stroke. Therefore, physicians should consider RAT as a therapeutic option for facilitating functional recovery after stroke.

Falls caused by balance disorders in the elderly with multiple systems involved: Pathogenic mechanisms and treatment strategies

Falls are the main contributor to both fatal and nonfatal injuries in elderly individuals as well as significant sources of morbidity and mortality, which are mostly induced by impaired balance control. The ability to keep balance is a remarkably complex process that allows for rapid and precise changes to prevent falls with multiple systems involved, such as musculoskeletal system, the central nervous system and sensory system. However, the exact pathogenesis of falls caused by balance disorders in the elderly has eluded researchers to date. In consideration of aging phenomenon aggravation and fall risks in the elderly, there is an urgent need to explore the pathogenesis and treatments of falls caused by balance disorders in the elderly. The present review discusses the epidemiology of falls in the elderly, potential pathogenic mechanisms underlying multiple systems involved in falls caused by balance disorders, including musculoskeletal system, the central nervous system and sensory system. Meanwhile, some common treatment strategies, such as physical exercise, new equipment based on artificial intelligence, pharmacologic treatments and fall prevention education are also reviewed. To fully understand the pathogenesis and treatment of falls caused by balance disorders, a need remains for future large-scale multi-center randomized controlled trials and in-depth mechanism studies.

Ankle rehabilitation robot training for stroke patients with foot drop: Optimizing intensity and frequency

BACKGROUND

Robotic solutions for ankle joint physical therapy have extensively been researched. The optimal frequency and intensity of training for patients when using the ankle robot is not known which can affect rehabilitation outcome.

OBJECTIVE

To explore the optimal ankle robot training protocol on foot drop in stroke subjects.

METHODS

Subjects were randomly divided into four groups, with 9 in each group. The subjects received different intensities (low or high intensity) with frequencies (1 session/day or 2 sessions/day) of robot combination training. Each session lasted 20 minutes and all subjects were trained 5 days a week for 3 weeks.

RESULTS

After 3 weeks of treatment, all groups showed an improvement in passive and active ankle dorsiflexion range of motion (PROM and AROM) and Fugl-Meyer Assessment for lower extremity (FMA-LE) compared to pre-treatment. When training at the same level of intensity, patients who received 2 sessions/day of training had better improvement in ankle dorsiflexion PROM than those who received 1 session/day. In terms of the improvement in dorsiflexion AROM and FMA-LE, patients who received 2 sessions/day with high intensity training improved better than other protocols.

CONCLUSION

High frequency and high intensity robot training can be more effective in improving ankle dysfunction.

Effect of early integrated robot-assisted gait training on motor and balance in patients with acute ischemic stroke: a single-blinded randomized controlled trial

Background:

Gait disruption is a common poststroke problem. Robot-assisted gait training (RAGT) might improve motor function, balance, and activities of daily living.

Objective:

We compared the clinical effectiveness of early integrated RAGT using the Walkbot robotic gym with an intensity-matched enhanced lower limb therapy (ELLT) program and with conventional rehabilitation therapy (CRT) in patients with acute ischemic stroke.

Methods:

A total of 192 patients with acute ischemic stroke were randomly assigned (1:1:1) to receive RAGT, ELLT, or CRT. All three groups received 45 min of training daily, 3 days a week, for 4 weeks consecutively. Before and after the 4-week treatment, the patients were assessed based on a 6-minute walking test (6MWT), functional ambulation classification (FAC), timed up and go (TUG) test, dual-task walking (DTW) test, Tinetti’s test, Barthel’s index (BI), stroke-specific quality of life (SS-QOL) scale, and gait analysis parameters.

Results:

After the 4-week intervention, the results of the 6MWT, FAC, TUG, DTW, Tinetti’s test, BI, SS-QOL, and gait in the three groups significantly improved. Compared with ELLT and CRT groups, participants in the RAGT group had a better performance in 6MWT (199.11 ± 60.72 versus 182.47 ± 59.72 versus 173.69 ± 40.58, p = 0.035), FAC (4.10 ± 0.91 versus 3.69 ± 0.88 versus 3.58 ± 0.81, p = 0.044), DTW (10.29 ± 2.38 versus 12.92 ± 2.64 versus 13.89 ± 2.62, p = 0.031), SS-QOL (184.46 ± 20.53 versus 165.39 ± 20.49 versus 150.72 ± 20.59, p = 0.012), velocity (0.66 ± 0.22 versus 0.55 ± 0.23 versus 0.51 ± 0.20, p = 0.008), cycle duration (1.38 ± 0.40 versus 1.50 ± 0.38 versus 1.61 ± 0.30, p = 0.040), and swing phase symmetry ratio (SPSR, 1.10 ± 0.33 versus 1.21 ± 0.22 versus 1.48 ± 0.25, p = 0.021). The TUG, Tinetti’s test, BI, and RMT results were similar, however.

Conclusion:

In the acute stroke phase, early integrated RAGT showed greater performance in gait rehabilitation than CRT and ELLT.

Registration:

ChiCTR1900026225

EEG Microstate-Specific Functional Connectivity and Stroke-Related Alterations in Brain Dynamics

The brain, as a complex dynamically distributed information processing system, involves the coordination of large-scale brain networks such as neural synchronization and fast brain state transitions, even at rest. However, the neural mechanisms underlying brain states and the impact of dysfunction following brain injury on brain dynamics remain poorly understood. To this end, we proposed a microstate-based method to explore the functional connectivity pattern associated with each microstate class. We capitalized on microstate features from eyes-closed resting-state EEG data to investigate whether microstate dynamics differ between subacute stroke patients (N = 31) and healthy populations (N = 23) and further examined the correlations between microstate features and behaviors. An important finding in this study was that each microstate class was associated with a distinct functional connectivity pattern, and it was highly consistent across different groups (including an independent dataset). Although the connectivity patterns were diminished in stroke patients, the skeleton of the patterns was retained to some extent. Nevertheless, stroke patients showed significant differences in most parameters of microstates A, B, and C compared to healthy controls. Notably, microstate C exhibited an opposite pattern of differences to microstates A and B. On the other hand, there were no significant differences in all microstate parameters for patients with left-sided vs. right-sided stroke, as well as patients before vs. after lower limb training. Moreover, support vector machine (SVM) models were developed using only microstate features and achieved moderate discrimination between patients and controls. Furthermore, significant negative correlations were observed between the microstate-wise functional connectivity and lower limb motor scores. Overall, these results suggest that the changes in microstate dynamics for stroke patients appear to be state-selective, compensatory, and related to brain dysfunction after stroke and subsequent functional reconfiguration. These findings offer new insights into understanding the neural mechanisms of microstates, uncovering stroke-related alterations in brain dynamics, and exploring new treatments for stroke patients.