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.

Development of a Two-Finger Haptic Robotic Hand with Novel Stiffness Detection and Impedance Control.

Haptic hands and grippers, designed to enable skillful object manipulation, are pivotal for high-precision interaction with environments. These technologies are particularly vital in fields such as minimally invasive surgery, where they enhance surgical accuracy and tactile feedback: in the development of advanced prosthetic limbs, offering users improved functionality and a more natural sense of touch, and within industrial automation and manufacturing, they contribute to more efficient, safe, and flexible production processes. This paper presents the development of a two-finger robotic hand that employs simple yet precise strategies to manipulate objects without damaging or dropping them. Our innovative approach fused force-sensitive resistor (FSR) sensors with the average current of servomotors to enhance both the speed and accuracy of grasping. Therefore, we aim to create a grasping mechanism that is more dexterous than grippers and less complex than robotic hands. To achieve this goal, we designed a two-finger robotic hand with two degrees of freedom on each finger; an FSR was integrated into each fingertip to enable object categorization and the detection of the initial contact. Subsequently, servomotor currents were monitored continuously to implement impedance control and maintain the grasp of objects in a wide range of stiffness. The proposed hand categorized objects' stiffness upon initial contact and exerted accurate force by fusing FSR and the motor currents. An experimental test was conducted using a Yale-CMU-Berkeley (YCB) object set consisted of a foam ball, an empty soda can, an apple, a glass cup, a plastic cup, and a small milk packet. The robotic hand successfully picked up these objects from a table and sat them down without inflicting any damage or dropping them midway. Our results represent a significant step forward in developing haptic robotic hands with advanced object perception and manipulation capabilities.

Enhancing Wearable Gait Monitoring Systems: Identifying Optimal Kinematic Inputs in Typical Adolescents.

Machine learning-based gait systems facilitate the real-time control of gait assistive technologies in neurological conditions. Improving such systems needs the identification of kinematic signals from inertial measurement unit wearables (IMUs) that are robust across different walking conditions without extensive data processing. We quantify changes in two kinematic signals, acceleration and angular velocity, from IMUs worn on the frontal plane of bilateral shanks and thighs in 30 adolescents (8-18 years) on a treadmills and outdoor overground walking at three different speeds (self-selected, slow, and fast). Primary curve-based analyses included similarity analyses such as cosine, Euclidean distance, Poincare analysis, and a newly defined bilateral symmetry dissimilarity test (BSDT). Analysis indicated that superior-inferior shank acceleration (SI shank Acc) and medial-lateral shank angular velocity (ML shank AV) demonstrated no differences to the control signal in BSDT, indicating the least variability across the different walking conditions. Both SI shank Acc and ML shank AV were also robust in Poincare analysis. Secondary parameter-based similarity analyses with conventional spatiotemporal gait parameters were also performed. This normative dataset of walking reports raw signal kinematics that demonstrate the least to most variability in switching between treadmill and outdoor walking to help guide future machine learning models to assist gait in pediatric neurological conditions.

Case report: The gait deviation index may predict neurotherapeutic effects of FES-assisted gait training in children with cerebral palsy.

Background: Children with cerebral palsy (CP) show progressive loss of ambulatory function characterized by kinematic deviations at the hip, knee, and ankle. Functional electrical stimulation (FES) can lead to more typical lower limb kinematics during walking by eliciting appropriately timed muscle contractions. FES-assisted walking interventions have shown mixed to positive results in improving lower limb kinematics through immediate correction of gait during the application of FES, or long-term, persisting effects of non-FES-assisted gait improvements following multi-week FES-assisted gait training, at the absence of stimulation, i.e., neurotherapeutic effects. It is unknown, however, if children with CP will demonstrate a neurotherapeutic response following FES-assisted gait training because of the CP population's heterogeneity in gait deviations and responses to FES. Identifying the neurotherapeutic responders is, therefore, important to optimize the training interventions to those that have higher probability of benefiting from the intervention. Objective: The purpose of this case study was to investigate the relationship between immediate and neurotherapeutic effects of FES-assisted walking to identify responders to a FES-assisted gait training protocol. Methods: The primary outcome was Gait Deviation Index (GDI) and secondary outcome was root mean squared error (RMSE) of the lower extremity joint angles in the sagittal plane between participants with CP and a typically developing (TD) dataset. Potential indicators were defined as immediate improvements from baseline during FES-assisted walking followed by neurotherapeutic improvements at the end of training. Case description: Gait analysis of two adolescent female participants with spastic diplegia (Gross Motor Function Classification System level II and III) was conducted at the start and end of a 12-week FES-assisted treadmill training protocol. Participant 1 had scissoring crouch gait, while participant 2 had jump gait. Outcomes: The GDI showed both immediate (presence of FES) and neurotherapeutic (absence of FES after training period) improvements from baseline in our two participants. Joint angle RMSE showed mixed trends between immediate and neurotherapeutic changes from baseline. The GDI warrants investigation in a larger sample to determine if it can be used to identify responders to FES-assisted gait training.

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.

Evaluation of Multi-layer Perceptron Neural Networks in Predicting Ankle Dorsiflexion in Healthy Adults using Movement-related Cortical Potentials for BCI-Neurofeedback Applications.

Brain computer interface (BCI) systems were initially developed to replace lost function; however, they are being increasingly utilized in rehabilitation to restore motor functioning after brain injury. In such BCI-mediated neurofeedback training (BCI-NFT), the brain-state associated with movement attempt or intention is used to activate an external device which assists the movement while providing sensory feedback to enhance neuroplasticity. A critical element in the success of BCI-NFT is accurate timing of the feedback within the active period of the brain state. The overarching goal of this work was to develop a reliable deep learning model that can predict motion before its onset, and thereby deliver the sensory stimuli in a timely manner for BCI-NFT applications. To this end, the main objective of the current study was to design and evaluate a Multi-layer Perceptron Neural Network (MLP-NN). Movement-related cortical potentials (MRCP) during planning and execution of ankle dorsiflexion was used to train the model to classify dorsiflexion planning vs. rest. The accuracy and reliability of the model was evaluated offline using data from eight healthy individuals (age: 26.3 ± 7.6 years). First, we evaluated three different epoching strategies for defining our 2 classes, to identify the one which best discriminated rest from dorsiflexion. The best model accuracy for predicting ankle dorsiflexion from EEG before movement execution was 84.7%. Second, the effect of various spatial filters on the model accuracy was evaluated, demonstrating that the spatial filtering had minimal effect on model accuracy and reliability.

Aerobic Responses to FES-Assisted and Volitional Cycling in Children with Cerebral Palsy.

Recumbent stationary cycling is a potential exercise modality for individuals with cerebral palsy (CP) that lack the postural control needed for upright exercises. Functional electrical stimulation (FES) of lower extremity muscles can help such individuals reach the cycling intensities that are required for aerobic benefits. The aim of this study was to examine the effect of cycling with and without FES assistance to that of a no-intervention control group on the cardiorespiratory fitness of children with CP. Thirty-nine participants were randomized to a FES group that underwent an 8-week FES-assisted cycling program, the volitional group (VOL), who cycled without FES, or a no-intervention control group (CON) (15 FES, 11 VOL, 13 CON). Cadence, peak VO2, and net rise in heart rate were assessed at baseline, end of training, and washout (8-weeks after cessation of training). Latent growth curve modeling was used for analysis. The FES group showed significantly higher cycling cadences than the VOL and CON groups at POST and WO. There were no differences in improvements in the peak VO2 and peak net HR between groups. FES-assisted cycling may help children with CP attain higher cycling cadences and to retain these gains after training cessation. Higher training intensities may be necessary to obtain improvements in peak VO2 and heart rate.

Evaluation of Individualized Functional Electrical Stimulation-Induced Acute Changes during Walking: A Case Series in Children with Cerebral Palsy.

Functional electrical stimulation (FES) walking interventions have demonstrated improvements to gait parameters; however, studies were often confined to stimulation of one or two muscle groups. Increased options such as number of muscle groups targeted, timing of stimulation delivery, and level of stimulation are needed to address subject-specific gait deviations. We aimed to demonstrate the feasibility of using a FES system with increased stimulation options during walking in children with cerebral palsy (CP). Three physical therapists designed individualized stimulation programs for six children with CP to target participant-specific gait deviations. Stimulation settings (pulse duration and current) were tuned to each participant. Participants donned our custom FES system that utilized gait phase detection to control stimulation to lower extremity muscle groups and walked on a treadmill at a self-selected speed. Motion capture data were collected during walking with and without the individualized stimulation program. Eight gait metrics and associated timing were compared between walking conditions. The prescribed participant-specific stimulation programs induced significant change towards typical gait in at least one metric for each participant with one iteration of FES-walking. FES systems with increased stimulation options have the potential to allow the physical therapist to better target the individual's gait deviations than a one size fits all device.

Characterizing Cycling Smoothness and Rhythm in Children With and Without Cerebral Palsy.

Stationary cycling is a practical exercise modality in children with cerebral palsy (CP) that lack the strength for upright exercises. However, there is a lack of robust, sensitive metrics that can quantitatively assess the motor control during cycling. The purpose of this brief report was to characterize the differences in motor control of cycling in children with CP and with typical development by developing novel metrics to quantify cycling smoothness and rhythm. Thirty one children with spastic diplegic CP and 10 children with typical development cycled on a stationary cycle. Cycling smoothness was measured by cross-correlating the crank angle with an ideal cycling pattern generated from participant-specific cadence and cycling duration. Cycling rhythmicity was assessed by evaluating the revolution-to-revolution variability in the time required to complete a revolution. Statistically significant differences (p < 0.001) using the Wilcoxon Rank Sum test were found between the two groups for both the metrics. Additionally, decision tree analysis revealed thresholds of smoothness <0.01 and rhythm <0.089-0.115 s for discriminating a less smooth, irregular cycling pattern characteristic of CP from typical cycling. In summary, the objective measures developed in this study indicate significantly less smoothness and rhythm of cycling in children with CP compared to children with typical development, suggestive of altered coordination and poor motor control. Such quantitative assessments of cycling motion in children with CP provide insights into neuromotor deficits that prevent them from cycling at intensities required for aerobic benefits and for participating in cycling related physical activities with their peers.

An Evaluation of Three Kinematic Methods for Gait Event Detection Compared to the Kinetic-Based 'Gold Standard'.

Video- and sensor-based gait analysis systems are rapidly emerging for use in 'real world' scenarios outside of typical instrumented motion analysis laboratories. Unlike laboratory systems, such systems do not use kinetic data from force plates, rather, gait events such as initial contact (IC) and terminal contact (TC) are estimated from video and sensor signals. There are, however, detection errors inherent in kinematic gait event detection methods (GEDM) and comparative study between classic laboratory and video/sensor-based systems is warranted. For this study, three kinematic methods: coordinate based treadmill algorithm (CBTA), shank angular velocity (SK), and foot velocity algorithm (FVA) were compared to 'gold standard' force plate methods (GS) for determining IC and TC in adults (n = 6), typically developing children (n = 5) and children with cerebral palsy (n = 6). The root mean square error (RMSE) values for CBTA, SK, and FVA were 27.22, 47.33, and 78.41 ms, respectively. On average, GED was detected earlier in CBTA and SK (CBTA: -9.54 ± 0.66 ms, SK: -33.41 ± 0.86 ms) and delayed in FVA (21.00 ± 1.96 ms). The statistical model demonstrated insensitivity to variations in group, side, and individuals. Out of three kinematic GEDMs, SK GEDM can best be used for sensor-based gait event detection.

Real-Time Detection of Seven Phases of Gait in Children with Cerebral Palsy Using Two Gyroscopes.

A recently designed gait phase detection (GPD) system, with the ability to detect all seven phases of gait in healthy adults, was modified for GPD in children with cerebral palsy (CP). A shank-attached gyroscope sent angular velocity to a rule-based algorithm in LabVIEW to identify the distinct characteristics of the signal. Seven typically developing children (TD) and five children with CP were asked to walk on treadmill at their self-selected speed while using this system. Using only shank angular velocity, all seven phases of gait (Loading Response, Mid-Stance, Terminal Stance, Pre-Swing, Initial Swing, Mid-Swing and Terminal Swing) were reliably detected in real time. System performance was validated against two established GPD methods: (1) force-sensing resistors (GPD-FSR) (for typically developing children) and (2) motion capture (GPD-MoCap) (for both typically developing children and children with CP). The system detected over 99% of the phases identified by GPD-FSR and GPD-MoCap. Absolute values of average gait phase onset detection deviations relative to GPD-MoCap were less than 100 ms for both TD children and children with CP. The newly designed system, with minimized sensor setup and low processing burden, is cosmetic and economical, making it a viable solution for real-time stand-alone and portable applications such as triggering functional electrical stimulation (FES) in rehabilitation systems. This paper verifies the applicability of the GPD system to identify specific gait events for triggering FES to enhance gait in children with CP.

Evaluation of Gait Phase Detection Delay Compensation Strategies to Control a Gyroscope-Controlled Functional Electrical Stimulation System During Walking.

Functional electrical stimulation systems are used as neuroprosthetic devices in rehabilitative interventions such as gait training. Stimulator triggers, implemented to control stimulation delivery, range from open- to closed-loop controllers. Finite-state controllers trigger stimulators when specific conditions are met and utilize preset sequences of stimulation. Wearable sensors provide the necessary input to differentiate gait phases during walking and trigger stimulation. However, gait phase detection is associated with inherent system delays. In this study, five stimulator triggers designed to compensate for gait phase detection delays were tested to determine which trigger most accurately delivered stimulation at the desired times of the gait cycle. Motion capture data were collected on seven typically-developing children while walking on an instrumented treadmill. Participants wore one inertial measurement unit on each ankle and gyroscope data were streamed into the gait phase detection algorithm. Five triggers, based on gait phase detection, were used to simulate stimulation to five muscle groups, bilaterally. For each condition, stimulation signals were collected in the motion capture software via analog channels and compared to the desired timing determined by kinematic and kinetic data. Results illustrate that gait phase detection is a viable finite-state control, and appropriate system delay compensations, on average, reduce stimulation delivery delays by 6.7% of the gait cycle.

Use of a Novel Functional Electrical Stimulation Gait Training System in 2 Adolescents With Cerebral Palsy: A Case Series Exploring Neurotherapeutic Changes.

BACKGROUND AND PURPOSE: Cerebral palsy (CP) is characterized by decreased passive joint range-of-motion and impaired walking, resulting in progressive loss of function. Typical gait training interventions for children with CP appear insufficient to mitigate these effects. The purpose of this case report is to describe the use of a new treadmill-based gait training intervention using active correction with functional electrical stimulation (FES) in 2 adolescents with CP. CASE DESCRIPTION: Two participants with CP (13-year-old girls, Gross Motor Function Classification System [GMFCS] level II and III) trained by walking on a treadmill, with FES assistance, for 30 minutes, 3 times per week, for 12 weeks. The intervention used a feedback control system to detect all 7 phases of gait in real time and triggered FES to the appropriate muscle groups (up to 5 bilaterally) based on the detected gait phase. Joint kinematics, step width, stride length, walking endurance, peak oxygen uptake ($\dot{v}^{o}_{2}$), and oxygen (O2) cost of walking were evaluated preintervention and postintervention. OUTCOMES: Both participants showed improved knee and ankle angles and step width relative to children who are typically developing, and both exhibited increased stride length. One participant (GMFCS III) improved peak $\dot{v}^{o}_{2}$and walking endurance but not O2 cost of walking at her original self-selected walking speed. The other participant (GMFCS II) improved O2 cost of walking but not peak $\dot{v}^{o}_{2}$ or walking endurance. These differences are partly explained by differences in gait type, functional abilities, and initial fitness levels. Most improvements persisted at follow-up, indicating short-term neurotherapeutic effects. DISCUSSION: Most improvements persisted at follow-up, suggesting short-term neurotherapeutic effects. This case series demonstrates the promising utility of FES-assisted gait-training interventions, tailored to target individual gait deviations, in improving walking performance.