What EXACTLY will it take to get from 'improve' to 100% recover? When the hell will you take on the big challenges in stroke? When you are the 1 in 4 per WHO that has a stroke it will be too late!
Effects of exoskeleton rehabilitation robot training on neuroplasticity and lower limb motor function in patients with stroke
BMC Neurology volume 25, Article number: 193 (2025)
Abstract
Background
Lower limb exoskeleton rehabilitation robot is a new technology to improve the lower limb motor function of stroke patients. Recovery of motor function after stroke is closely related to neuroplasticity in the motor cortex and associated motor areas. However, few studies investigate how rehabilitation robots affect the neuroplasticity of stroke patients.This study sought to determine the effects of lower limb exoskeleton robot walking training on neuroplasticity and lower limb motor function in patients with stroke.
Methods
A total of 25 (50.26 ± 11.42 years, 68.0% male) patients(age 18–75 years, onset between 2 weeks and 6 months) with a stable condition after having a stroke were randomized into a treatment (n = 13) and control group (n = 12). Bilateral Exoskeletal Assistive Robot H1 (BEAR-H1) walking training was provided to the treatment group, whereas conventional walking training was provided to the control group. Both groups completed two training sessions per day for 30 min each and were trained 5 days a week for 4 weeks. Transcranial magnetic stimulation, Fugl–Meyer Assessment lower extremity, Functional Ambulation Category 6-min walking distance test, intelligent gait analysis, and surface electromyography of the lower limbs were performed before and 4 weeks after treatment.
Results
Both groups showed obvious improvements in all evaluation indicators (p < 0.05). Compared with the control group, the treatment group exhibited a decreased resting motor threshold and increased motor-evoked potential amplitude and recruitment curve slope (p < 0.05). The treatment group performed better than the control group (p < 0.05) in the 6-min walk test and knee flexion co-contraction ratio (CR). Correlation analysis showed that resting motor threshold, motor-evoked potential amplitude, and the recruitment curve slope were significantly correlated with the 6-min walk test, CR on ankle dorsiflexion, the root mean square of the tibialis anterior, biceps femoris, and medial gastrocnemius (p < 0.05).
Conclusion
Walking training using the bilateral exoskeletal assistive robot H1 improved cerebral cortical excitability in patients with stroke, which facilitated changes in neuroplasticity and enhanced lower limb motor function.
Registration
Chinese Clinical Trail Registry: ChiCTR1900028262. Registered Date: December 16,2019. Registration-URL: http://www.chictr.org.cn
Introduction
Stroke is one of the most common cerebrovascular diseases worldwide. Unfortunately, approximately 63% of stroke survivors suffer from lower limb motor dysfunction, [1] including gait dysfunction and decreased joint stability, muscle strength, and muscle endurance. Functional recovery of lower limb function, particularly walking ability, is fundamental to the daily activities of patients with stroke. Regaining walking ability is an important objective of post-stroke rehabilitation, considering that restrictions in walking function severely affect patient’s daily life and mental state, and increase the burden on their families. Impaired walking function can improve early after the onset of stroke, usually within the first 3–6 months [2].
Recovery of motor function after stroke is closely associated with neuroplasticity in the motor cortex and associated motor areas [3] Neuroimaging studies have already demonstrated that motor recovery after a stroke is usually associated with cortical reorganization and motor network connectivity [4, 5] Recovery of lower limb motor function depends on the reorganization of brain function and activation of cortical excitability in damaged brain areas [6] Interestingly, one study showed that lower limb movement or walking training can promote neuroplastic changes in the brain [7].
Conventional training methods for lower limb motor function, such as stepping and walking training, have been proven to be effective in restoring the walking ability of patients with stroke [8] However, considering that conventional training involves segmented training of a single muscle group or a single joint, coordinating active and antagonistic muscle movements through this training approach becomes difficult. To address this, robotic lower limb rehabilitation using exoskeletons or training pedals, for example, achieves symmetrical training of both lower extremities. Previous studies have shown that symmetrical walking training is positively correlated with walking stability among patients [9] Repetitive exercises for specific tasks are an effective approach for improving neuroplasticity, which may be related to an increase in the efficiency of cortical recombination or synaptic transmission. Moreover, some studies have shown that substantial benefits can only be achieved after engaging in an appropriate amount of repetitive walking training [10, 11] Lower limb rehabilitation robots allow patients to engage in high-intensity repetitive training while maintaining a steady standing position. French et al.,[12] who conducted a meta-analysis on repetitive training to improve limb movement disorders in patients with stroke, pointed out that repetitive training helps improve the body’s motor function, expands the innervation area of the trained site in the cerebral cortex, and improves the transmission efficiency of neural circuits [13] Lower limb rehabilitation robots can help patients engage in active training. Active movement patterns can stimulate the affected limb and cause expansion of the cortical areas. Lower limb rehabilitation exoskeleton robots imitate the gait cycle and provide ground walking training for patients in a real environment [14] This approach is based on resistance training patterns and provides assistance according to the patient’s gait phase [15] Jaeger et al.,[16] who used a magnetic resonance-compatible stepping robot and concluded that patients under active training stimulation exhibited significantly increased cortical signals. However, because most current studies have focused on the effects of rehabilitation exoskeleton robot training on improving limb motor function, little attention has been paid to determining the effects of such training on changes in neuroplasticity.
Transcranial magnetic stimulation (TMS) provides valuable information for predicting motor recovery in patients with stroke. It can explore the mechanisms of neural recovery by measuring the activation of the primary motor cortex (M1). The parameters provided by TMS can be used to identify motor cortical reorganization after a stroke, such as the resting motor threshold (rMT) and motor-evoked potential (MEP), which have been used to explain changes in corticospinal excitability after a stroke [17] One study showed that restoration of motor function is associated with improved corticospinal conduction and that MEP is a good indicator of functional recovery in patients with stroke [18] Studies on MEP and hand function of patients with chronic stroke found that shorter MEP latency, shorter central motor conduction time (CMCT), higher motor-evoked potential amplitude (pMEPamp), and diminished rMT were positively correlated with motor function recovery [19] TMS is an ideal tool for investigating cortical excitability in patients with stroke and may support the diagnosis and evaluation of clinical conditions [20] Therefore, this study used TMS to measure cortical plasticity in patients with hemiplegia. In addition, the main neural structures involved in this study include Primary motor cortex (M1), Corticospinal tract, Cerebral motor network, Peripheral nervous system components.
This study investigated the effects of bilateral exoskeletal assistive robot H1 (BEAR-H1) training and its impact on neuroplasticity in patients with stroke with hemiplegia using TMS analysis. Simultaneously, we used surface electromyography (sEMG) analysis, intelligent wearable gait analysis, the Functional Ambulation Category (FAC) scale, and the Fugl–Meyer Assessment (FMA) scale to explore the relationship between improvement in lower limb motor function and changes in neuroplasticity. The findings of this study provide a theoretical basis for the clinical application of lower limb rehabilitation robots.
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