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.

Determining optimal mobile neurofeedback methods for motor neurorehabilitation in children and adults with non-progressive neurological disorders: a scoping review

Background

Brain–computer interfaces (BCI), initially designed to bypass the peripheral motor system to externally control movement using brain signals, are additionally being utilized for motor rehabilitation in stroke and other neurological disorders. Also called neurofeedback training, multiple approaches have been developed to link motor-related cortical signals to assistive robotic or electrical stimulation devices during active motor training with variable, but mostly positive, functional outcomes reported. Our specific research question for this scoping review was: for persons with non-progressive neurological injuries who have the potential to improve voluntary motor control, which mobile BCI-based neurofeedback methods demonstrate or are associated with improved motor outcomes for Neurorehabilitation applications?

Methods

We searched PubMed, Web of Science, and Scopus databases with all steps from study selection to data extraction performed independently by at least 2 individuals. Search terms included: brain machine or computer interfaces, neurofeedback and motor; however, only studies requiring a motor attempt, versus motor imagery, were retained. Data extraction included participant characteristics, study design details and motor outcomes.

Results

From 5109 papers, 139 full texts were reviewed with 23 unique studies identified. All utilized EEG and, except for one, were on the stroke population. The most commonly reported functional outcomes were the Fugl-Meyer Assessment (FMA; n = 13) and the Action Research Arm Test (ARAT; n = 6) which were then utilized to assess effectiveness, evaluate design features, and correlate with training doses. Statistically and functionally significant pre-to post training changes were seen in FMA, but not ARAT. Results did not differ between robotic and electrical stimulation feedback paradigms. Notably, FMA outcomes were positively correlated with training dose.

Conclusion

This review on BCI-based neurofeedback training confirms previous findings of effectiveness in improving motor outcomes with some evidence of enhanced neuroplasticity in adults with stroke. Associative learning paradigms have emerged more recently which may be particularly feasible and effective methods for Neurorehabilitation. More clinical trials in pediatric and adult neurorehabilitation to refine methods and doses and to compare to other evidence-based training strategies are warranted.

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.

[New perspectives of motor rehabilitation of patients after focal brain lesions]

Rehabilitation of patients after focal brain lesions is one of the topical issues of modern medicine. Motor disorders are known to develop in more than 80% of survivors of stroke and traumatic brain injury and be one of the main causes of disability, which necessitates an active search for new effective techniques for correction of motor disorders. Modern rehabilitation includes both traditional techniques for recovery of patients with motor deficit (exercise therapy and physiotherapy) and botulinum therapy, kinesiotherapy, mechanotherapy, etc., which have been developed in recent years. Robotic technologies have been developed, improved, and implemented. Currently, due to progress in computerization, virtual reality-based rehabilitation of patients is of particular interest. The article reviews the key studies in this field. We describe various visualization methods and means of immersion in a virtual environment for recovery of upper and lower extremity function in patients with focal brain lesions. The study provides an assessment of the effectiveness and safety of various virtual reality-based rehabilitation programs in patients with motor disorders after stroke and traumatic brain injury.