Clinical usefulness of brain-computer interface-controlled functional electrical stimulation for improving brain activity in children with spastic cerebral palsy: a pilot randomized controlled trial

Development and evaluation of a BCI-neurofeedback system with real-time EEG detection and electrical stimulation assistance during motor attempt for neurorehabilitation of children with cerebral palsy

In the realm of motor rehabilitation, Brain-Computer Interface Neurofeedback Training (BCI-NFT) emerges as a promising strategy. This aims to utilize an individual's brain activity to stimulate or assist movement, thereby strengthening sensorimotor pathways and promoting motor recovery. Employing various methodologies, BCI-NFT has been shown to be effective for enhancing motor function primarily of the upper limb in stroke, with very few studies reported in cerebral palsy (CP). Our main objective was to develop an electroencephalography (EEG)-based BCI-NFT system, employing an associative learning paradigm, to improve selective control of ankle dorsiflexion in CP and potentially other neurological populations. First, in a cohort of eight healthy volunteers, we successfully implemented a BCI-NFT system based on detection of slow movement-related cortical potentials (MRCP) from EEG generated by attempted dorsiflexion to simultaneously activate Neuromuscular Electrical Stimulation which assisted movement and served to enhance sensory feedback to the sensorimotor cortex. Participants also viewed a computer display that provided real-time visual feedback of ankle range of motion with an individualized target region displayed to encourage maximal effort. After evaluating several potential strategies, we employed a Long short-term memory (LSTM) neural network, a deep learning algorithm, to detect the motor intent prior to movement onset. We then evaluated the system in a 10-session ankle dorsiflexion training protocol on a child with CP. By employing transfer learning across sessions, we could significantly reduce the number of calibration trials from 50 to 20 without compromising detection accuracy, which was 80.8% on average. The participant was able to complete the required calibration trials and the 100 training trials per session for all 10 sessions and post-training demonstrated increased ankle dorsiflexion velocity, walking speed and step length. Based on exceptional system performance, feasibility and preliminary effectiveness in a child with CP, we are now pursuing a clinical trial in a larger cohort of children with CP.

Effects of motor imagery based brain-computer interface on upper limb function and attention in stroke patients with hemiplegia: a randomized controlled trial

BACKGROUND

Seeking positive and comprehensive rehabilitation methods after stroke is an urgent problem to be solved, which is very important to improve the dysfunction of stroke. The aim of this study was to investigate the effects of motor imagery-based brain-computer interface training (MI-BCI) on upper limb function and attention in stroke patients with hemiplegia.

METHODS

Sixty stroke patients with impairment of upper extremity function and decreased attention were randomly assigned to the control group (CR group) or the experimental group (BCI group) in a 1:1 ratio. Patients in the CR group received conventional rehabilitation. Patients in the BCI group received 20 min of MI-BCI training five times a week for 3 weeks (15 sessions) in addition to conventional rehabilitation. The primary outcome measures were the changes in Fugl-Meyer Motor Function Assessment of Upper Extremities (FMA-UE) and Attention Network Test (ANT) from baseline to 3 weeks.

RESULTS

About 93% of the patients completed the allocated training. Compared with the CR group, among those in the BCI group, FMA-UE was increased by 8.0 points (95%CI, 5.0 to 10.0; P < 0.001). Alert network response time (32.4ms; 95%CI, 58.4 to 85.6; P < 0.001), orienting network response (5.6ms; 95%CI, 29.8 to 55.8; P = 0.010), and corrects number (8.0; 95%CI, 17.0 to 28.0; P < 0.001) also increased in the BCI group compared with the CR group. Additionally, the executive control network response time (- 105.9ms; 95%CI, - 68.3 to - 23.6; P = 0.002), the total average response time (- 244.8ms; 95%CI, - 155.8 to - 66.2; P = 0.002), and total time (- 122.0ms; 95%CI, - 80.0 to - 35.0; P = 0.001) were reduced in the BCI group compared with the CR group.

CONCLUSION

MI-BCI combined with conventional rehabilitation training could better enhance upper limb motor function and attention in stroke patients. This training method may be feasible and suitable for individuals with stroke.

TRIAL REGISTRATION

This study was registered in the Chinese Clinical Trial Registry with Portal Number ChiCTR2100050430(27/08/2021).

Neural Bypasses: Literature Review and Future Directions in Developing Artificial Neural Connections

Reported neuro-modulation schemes in the literature are typically classified as closed-loop or open-loop. A novel group of recently developed neuro-modulation devices may be better described as a neural bypass, which attempts to transmit neural data from one location of the nervous system to another. The most common form of neural bypasses in the literature utilize EEG recordings of cortical information paired with functional electrical stimulation for effector muscle output, most commonly for assistive applications and rehabilitation in spinal cord injury or stroke. Other neural bypass locations that have also been described, or may soon be in development, include cortical-spinal bypasses, cortical-cortical bypasses, autonomic bypasses, peripheral-central bypasses, and inter-subject bypasses. The most common recording devices include EEG, ECoG, and microelectrode arrays, while stimulation devices include both invasive and noninvasive electrodes. Several devices are in development to improve the temporal and spatial resolution and biocompatibility for neuronal recording and stimulation. A major barrier to entry includes neuroplasticity and current decoding mechanisms that regularly require retraining. Neural bypasses are a unique class of neuro-modulation. Continued advancement of neural recording and stimulating devices with high spatial and temporal resolution, combined with decoding mechanisms uninhibited by neuroplasticity, can expand the therapeutic capability of neural bypassing. Overall, neural bypasses are a promising modality to improve the treatment of common neurologic disorders, including stroke, spinal cord injury, peripheral nerve injury, brain injury and more.

[Current approaches to the use of robotic devices in rehabilitation complex of children with cerebral palsy]

Cerebral palsy is a neurological disease that is associated with multiple motor impairments and dysfunctions in children. The effective recovery of motor activity in both the upper and lower limbs is an important condition for the patient's social independence throughout his life. Robotic systems are new devices which are becoming increasingly popular as a part of the treatment of cerebral palsy. They have become a good addition to comprehensive rehabilitation therapy, including conducted at the sanatorium-resort stage. Further research is needed to clarify and prove the extent to which these devices help in treatment of children with cerebral palsy.

The influential factors and non-pharmacological interventions of cognitive impairment in children with ischemic stroke

Background

The prevalence of pediatric ischemic stroke rose by 35% between 1990 and 2013. Affected patients can experience the gradual onset of cognitive impairment in the form of impaired language, memory, intelligence, attention, and processing speed, which affect 20-50% of these patients. Only few evidence-based treatments are available due to significant heterogeneity in age, pathological characteristics, and the combined epilepsy status of the affected children.

Methods

We searched the literature published by Web of Science, Scopus, and PubMed, which researched non-pharmacological rehabilitation interventions for cognitive impairment following pediatric ischemic stroke. The search period is from the establishment of the database to January 2022.

Results

The incidence of such impairment is influenced by patient age, pathological characteristics, combined epilepsy status, and environmental factors. Non-pharmacological treatments for cognitive impairment that have been explored to date mainly include exercise training, psychological intervention, neuromodulation strategies, computer-assisted cognitive training, brain-computer interfaces (BCI), virtual reality, music therapy, and acupuncture. In childhood stroke, the only interventions that can be retrieved are psychological intervention and neuromodulation strategies.

Conclusion

However, evidence regarding the efficacy of these interventions is relatively weak. In future studies, the active application of a variety of interventions to improve pediatric cognitive function will be necessary, and neuroimaging and electrophysiological measurement techniques will be of great value in this context. Larger multi-center prospective longitudinal studies are also required to offer more accurate evidence-based guidance for the treatment of patients with pediatric stroke.

Changes in EEG patterns in the α-frequency band following BCI-based therapy in children with cerebral palsy

It was demonstrated previously that neurorehabilitation with the BCI-controlled robotic device Exohand-2 combined with conventional therapeutic modalities resulted in significant motor improvement in children with cerebral palsy. However, EEG records were not analyzed in the previous study. The aim of this paper was to describe the reactivity patterns of the EEG α-rhythm during a series of 10 BCI-based neurorehabilitation sessions. The study was carried out in 32 boys and girls aged 10 to 18 years with right- or left-side hemiparesis. EEG was recorded from 21 electrodes at rest and during kinesthetic imagery of finger extension. During the first session, patterns of α-rhythm reactivity during motor imagery differed between patients with left- and right-side hemiparesis. The differences were statistically significant at Р2 during left hand movement rehearsal (F1, 30 = 5.10; p < 0.05). During the final session, the pattern of α-rhythm reactivity was different: synchronization was taken over by desynchronization at some electrode sites, suggesting increased activity of the neocortex. The most conspicuous EEG changes were observed in children with left-side hemiparesis (F20, 300 = 1.84; p < 0.05). By the end of the rehabilitation course, the differences between patients with left-and right-side hemiparesis became much less pronounced. Rearrangements in the EEG patterns in the α-frequency band can be regarded as signs of beneficial reorganization of neural circuits responsible for planning and executing complex hand movements.

State-of-the-art non-invasive brain–computer interface for neural rehabilitation: A review

Brain–computer interface (BCI) is a novel communication method between brain and machine. It enables signals from the human brain to influence or control external devices. Currently, much research interest is focused on the BCI-based neural rehabilitation of patients with motor and cognitive diseases. Over the decades, BCI has become an alternative treatment for motor and cognitive rehabilitation. Previous studies demonstrated the usefulness of BCI intervention in restoring motor function and recovery of the damaged brain. Electroencephalogram (EEG)-based BCI intervention could cast light on the mechanisms underlying neuroplasticity during upper limb recovery by providing feedback to the damaged brain. BCI could act as a useful tool to aid patients with daily communication and basic movement in severe motor loss cases like amyotrophic lateral sclerosis (ALS). Furthermore, recent findings have reported the therapeutic efficacy of BCI in people suffering from other diseases with different levels of motor impairment such as spastic cerebral palsy, neuropathic pain, etc. Besides motor functional recovery, BCI also plays its role in improving the behavior of patients with cognitive diseases like attention-deficit/hyperactivity disorder (ADHD). The BCI-based neurofeedback training is focused on either reducing the ratio of theta and beta rhythm, or enabling the patients to regulate their own slow cortical potentials, and both have made progress in increasing attention and alertness. With summary of several clinical studies with strong evidence, we present cutting edge results from the clinical application of BCI in motor and cognitive diseases, including stroke, spinal cord injury, ALS, and ADHD.

Evaluating If Children Can Use Simple Brain Computer Interfaces

Background: The options for severely disabled children with intact cognition to interact with their environment are extremely limited. A brain computer interface (BCI) has the potential to allow such persons to gain meaningful function, communication, and independence. While the pediatric population might benefit most from BCI technology, research to date has been predominantly in adults. Methods: In this prospective, cross-over study, we quantified the ability of healthy school-aged children to perform simple tasks using a basic, commercially available, EEG-based BCI. Typically developing children aged 6-18 years were recruited from the community. BCI training consisted of a brief set-up and EEG recording while performing specific tasks using an inexpensive, commercially available BCI system (EMOTIV EPOC). Two tasks were trained (driving a remote-control car and moving a computer cursor) each using two strategies (sensorimotor and visual imagery). Primary outcome was the kappa coefficient between requested and achieved performance. Effects of task, strategy, age, and learning were also explored. Results: Twenty-six of thirty children completed the study (mean age 13.2 ± 3.6 years, 27% female). Tolerability was excellent with >90% reporting the experience as neutral or pleasant. Older children achieved performance comparable to adult studies, but younger age was associated with lesser though still good performance. The car task demonstrated higher performance compared to the cursor task (p = 0.027). Thought strategy was also associated with performance with visual imagery strategies outperforming sensorimotor approaches (p = 0.031). Conclusion: Children can quickly achieve control and execute multiple tasks using simple EEG-based BCI systems. Performance depends on strategy, task and age. Such success in the developing brain mandates exploration of such practical systems in severely disabled children.

Therapeutic Effect Evaluation of Neuromuscular Electrical Stimulation With or Without Strengthening Exercise on Spastic Cerebral Palsy

The aims of this study were to investigate the effect of neuromuscular electrical stimulation (NMES) combined with strengthening exercise on movement in children with spastic cerebral palsy (CP). One hundred children with spastic CP were randomly divided into a treatment group (NMES and strengthening exercise, n = 50) and a control group (only NMES, n = 50). We compared the Comprehensive Spasticity Scale (CSS) score, Gross Motor Function Measure (GMFM) score, and walking speed before treatment and 6 weeks and 3 months after treatment between the 2 groups. There was no difference in CSS score between the treatment and control groups before the therapy (12.0 ± 3.4 vs 12.3 ± 3.6), which decreased much more in the treatment group after 6 weeks (7.6 ± 3.0 vs 9.5 ± 2.8) and 3 months (7.4 ± 2.4 vs 9.4 ± 2.6) with significant differences ( P < .05). No difference in GMFM score was observed between the treatment and control groups before the therapy (44.5 ± 13.2 vs 44.0 ± 12.6), which increased much more in the treatment group after 6 weeks (70.6 ± 15.2 vs 56.7 ± 14.3) and 3 months (71.0 ± 16.4 vs 58.0 ± 15.6) with significant differences ( P < .05). The walking speed improved over time, which was the same before the treatment (0.43 ± 0.13 m/s vs 0.45 ± 0.14 m/s), and was significantly greater in the treatment group than that in the control group (6 weeks: 0.69 ± 0.15 m/s vs 0.56 ± 0.12 m/s, P < .05; 3 months: 0.72 ± 0.17 m/s vs 0.57 ± 0.18 m/s, P < .05). NMES combined with strengthening exercise was more effective than NMES alone in the recovery of spastic CP.

Brain-Computer Interface for Clinical Purposes: Cognitive Assessment and Rehabilitation

Alongside the best-known applications of brain-computer interface (BCI) technology for restoring communication abilities and controlling external devices, we present the state of the art of BCI use for cognitive assessment and training purposes. We first describe some preliminary attempts to develop verbal-motor free BCI-based tests for evaluating specific or multiple cognitive domains in patients with Amyotrophic Lateral Sclerosis, disorders of consciousness, and other neurological diseases. Then we present the more heterogeneous and advanced field of BCI-based cognitive training, which has its roots in the context of neurofeedback therapy and addresses patients with neurological developmental disorders (autism spectrum disorder and attention-deficit/hyperactivity disorder), stroke patients, and elderly subjects. We discuss some advantages of BCI for both assessment and training purposes, the former concerning the possibility of longitudinally and reliably evaluating cognitive functions in patients with severe motor disabilities, the latter regarding the possibility of enhancing patients' motivation and engagement for improving neural plasticity. Finally, we discuss some present and future challenges in the BCI use for the described purposes.