Search Results (21)

Sensorimotor rhythms (SMR) are widely employed in brain–machine interface applications, although their reliable detection during overt upper-limb movements remains challenging because of motion artifacts and concurrent peripheral activity. This study investigated whether SMR modulation can be decoded during elbow flexion and extension performed under active and resistive conditions resembling robot-assisted rehabilitation, with and without voluntary modulation. Nine healthy participants executed four experimental conditions while electroencephalography (EEG), electromyography (EMG), and inertial measurement unit (IMU) signals were synchronously acquired. EEG data were analyzed using a filter bank common spatial pattern (FBCSP)-based classification pipeline, whereas EMG signals were used to estimate exerted force. Subjective workload was evaluated through the NASA-TLX questionnaire. Classification accuracies generally exceeded the theoretical chance level, reaching average values above 73% ± 14% and above 80% ± 12% when discriminating voluntary SMR modulation independently of movement type. Only a few individual cases were at or below the theoretical chance level. EMG analyses confirmed higher force production during resistive tasks, while event-related desynchronization/synchronization analyses revealed distinct cortical modulations in the $\mu$ and $\beta$ bands, indicating the presence of task-related cortical modulation underlying the decoded features. These findings demonstrate the feasibility of detecting SMR modulation during overt upper-limb movements and support the potential of the proposed framework for future adaptive robot-assisted rehabilitation systems, where movement resistance could be modulated according to real-time neural activity. Full article

SARS-CoV-2 infection is associated with not only acute respiratory symptoms but is also characterized by strong neurotropism which may contribute to the development of the multisystem post-COVID syndrome (PASC). Patients frequently report chronic neurocognitive disorders such as brain fog, significant attention deficits and increased susceptibility to epileptiform discharges. The aim of this review is to systematize the knowledge regarding deviations in quantitative electroencephalography (QEEG) recordings in convalescents and to evaluate the utility of this method as an objective biomarker. This work constitutes a comprehensive literature review integrating the latest data on neuroinflammation, blood-brain barrier damage and changes in cortical oscillatory dynamics induced by the infection. The literature analysis indicates that the virus may induce a pathological excitation and inhibition imbalance (E/I imbalance) in neuronal networks. In QEEG studies this manifests as excessive activity of slow bands (Theta, Delta), a deficit of rhythms responsible for attention and sensorimotor integration (SMR) and a pathologically elevated Theta to Beta ratio (TBR). In conclusion, QEEG can serve as an objective and highly sensitive tool supporting the diagnosis and stratification of patients with neurocognitive complications of Long COVID. The integration of precise electrophysiological phenotyping with targeted behavioral neuromodulation (e.g., EEG-Biofeedback) fits into the paradigm of personalized medicine and offers a prospective strategy for mitigating long-term neurological burdens. Full article

This systematic review synthesized the existing evidence on neurofeedback interventions applied to football players, aiming to clarify their effects on cognitive, technical–tactical, physical and psychological performance. Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, four databases (PubMed, Web of Science, SCOPUS and SportsDiscus) were searched up to November 2025. Seven studies met the inclusion criteria, involving 133 players across youth, amateur, national and elite levels. Neurofeedback protocols primarily targeted alpha or sensorimotor rhythm (SMR) activity, and some were combined with heart rate variability (HRV) biofeedback. Across studies, neurofeedback may be associated with improvements in several cognitive outcomes, including improvements in working memory, visuospatial memory, task switching, mental rotation and decision-making. Limited evidence suggests potential improvements in technical skills (particularly shooting accuracy) and tactical decision-making. Some studies reported changes in physiological markers and stress-recovery capacity, although their interpretation remains uncertain. However, the evidence base remains constrained by small samples, heterogeneous protocols and limited use of randomized controlled designs. Overall, neurofeedback appears to be a potentially promising but still experimental tool to support cognitive and psychophysiological readiness in football, warranting more rigorous and standardized research to establish efficacy and optimal training parameters. Full article

Background/Objectives: Post-traumatic epileptogenesis is a frequent and clinically relevant consequence of traumatic brain injury (TBI), often contributing to worsened neurological and functional outcomes. In patients experiencing early post-injury seizures, rehabilitative strategies that support recovery while considering increased epileptogenic risk are needed. This case study explores the potential benefits of combining neurofeedback (NFB) with motor therapy on cognitive and motor recovery. Methods: A patient hospitalized for severe TBI who experienced an acute symptomatic seizure in the early post-injury phase underwent baseline quantitative EEG (qEEG), neuromotor, functional, and neuropsychological assessments. The patient then completed a three-week rehabilitation program (five days/week) including 30 sensorimotor rhythm (SMR) NFB sessions (35 min each) combined with daily one-hour motor therapy. qEEG and clinical assessments were repeated post-intervention and at 6-month follow-up. Results: Post-intervention qEEG showed significant reductions in Delta and Theta power, reflecting decreased cortical slowing and enhanced neural activation. Relative power analysis indicated reduced Theta activity and Alpha normalization, suggesting improved cortical stability. Increases were observed in Beta and High-beta activity, alongside significant reductions in the Theta/Beta ratio, consistent with improved attentional regulation. Neuropsychological outcomes revealed reliable improvements in global cognition, memory, and visuospatial abilities, mostly maintained or enhanced at follow-up. Depressive and anxiety symptoms decreased markedly. Motor and functional assessments demonstrated meaningful improvements in motor performance, coordination, and functional independence. Conclusions: Findings suggest that integrating NFB with motor therapy may support recovery processes and be associated with sustained neuroplastic changes in the early post-injury phase after TBI, a condition associated with elevated risk for post-traumatic epilepsy. Full article

Background: Neurofeedback training has emerged as a promising tool for enhancing performance by targeting specific brain activity patterns linked to motor skills, decision-making, and concentration. This study aimed to explore the associations between neurofeedback outcomes and football-specific performance metrics, including anthropometric, physical, technical, and tactical dimensions. Methods: A quasi-experimental design was used to examine the effects of a six-week neurofeedback training program on motor skills, tactical decision-making, and physical performance in young women’s football players (n = 8, aged 14–18). Participants underwent 30-min sessions three times a week targeting sensorimotor rhythms (SMRs) in the 12–15 Hz range within virtual football scenarios. Pre- and post-intervention assessments included anthropometric measures, neurophysiological evaluations, Loughborough Soccer Shooting Test (LSST), and Yo-Yo Intermittent Recovery Test Level 1 (YYIR1). Tactical decision-making was evaluated with a FUT-SAT-based instrument, and biological maturity was estimated using the Mirwald equations. Results: Statistical analyses using Pearson’s correlations revealed significant associations between neurofeedback outcomes, motor efficiency indices (MEIs), decision-making (DM), and football performance metrics. Correlation coefficients ranged from 0.504 to 0.998, with p-values from 0.010 to <0.001, indicating significant associations across physical, technical, and tactical dimensions. Conclusions: This study highlights the beneficial impact of neurofeedback on football performance in young female athletes. Full article

(1) Background: Neurofeedback (NFB) and biofeedback (BFB) have been shown to reduce stress, enhance physiological self-regulation, improve cognitive performance, and accelerate response times. Stimulating the sensorimotor rhythm (12–15 Hz) is particularly effective in improving working memory and selective attention. However, most studies on air force pilots focus on addressing post-traumatic stress disorder rather than investigating how these interventions might enhance performance and safety during flights, as explored in the present study. (2) Methods: Twelve Spanish Air Force fighter pilot trainees (mean age = 22.83 (0.94) years) participated in the study. Six pilots underwent 24 sessions of combined NFB and BFB training (experimental group), while six served as controls. (3) Results: The experimental group demonstrated improved heart rate variability during baseline, alarm sounds, math tasks, and real flights, which is indicative of greater parasympathetic modulation. A significant decrease in the Theta/SMR ratio was observed in the experimental group during the same conditions, suggesting improved focus, with lower values than the control group. Cognitive performance improved in the experimental group, with higher accuracy and a greater number of completed operations during math tasks. Regarding dual-task performance, the experimental group showed lower reaction time and a better ratio taps/reaction post-intervention. Psychological benefits included reduced cognitive, somatic, and state anxiety levels, along with increased self-confidence. (4) Conclusions: Neurofeedback and biofeedback training, integrated with real flights, simulators, and virtual reality, can enhance physiological regulation, cognitive performance, and emotional resilience, contributing to improved performance and safety in air force pilots. Full article

Parkinson’s disease (PD) is a progressive neurodegenerative disorder, with pharmacological treatments predominantly focusing on dopaminergic therapies. In the early stages of PD, symptoms may also be alleviated through non-pharmacological interventions. One such non-invasive technique is electroencephalogram neurofeedback (EEG NFB), which has shown promising results in improving the cognitive and motor functions of PD patients. The aim of our study was to assess the existing evidence, identify key trends and determine potential opportunities for future research in the field of EEG NFB for PD. This analysis explores the impact of EEG NFB on motor deficits in PD and identifies key factors for the successful implementation of EEG NFB as evidenced in the literature. The synthesis includes findings from five relevant studies, including one case study, one pilot study and three randomized controlled trials. Study selection followed the PICO framework to ensure relevance and rigor. The results suggest a correlation between sensorimotor rhythm (SMR) and beta rhythms, with increases in SMR (13–15 Hz) and beta (12–15 Hz) rhythms linked to improvements in balance, mobility and stability in PD patients. However, limitations such as small sample sizes, brief intervention durations and lack of follow-up warrant a cautious interpretation. Future research should prioritize robust protocols, larger samples and extended neurofeedback training to fully assess EEG NFB’s potential for PD management. Full article

Neurofeedback (NF) is a brain–computer interface in which users can learn to modulate their own brain activation while receiving real-time feedback thereof. To increase motivation and adherence to training, virtual reality has recently been used as a feedback modality. In the presented study, we focused on the effects of augmented reality (AR) based visual feedback on subjective user experience, including positive/negative affect, cybersickness, flow experience, and experience with the use of this technology, and compared it with a traditional 2D feedback modality. Also, half of the participants got real feedback and the other half got sham feedback. All participants performed one NF training session, in which they tried to increase their sensorimotor rhythm (SMR, 12–15 Hz) over central brain areas. Forty-four participants received conventional 2D visual feedback (moving bars on a conventional computer screen) about real-time changes in SMR activity, while 45 participants received AR feedback (3D virtual flowers grew out of a real pot). The subjective user experience differed in several points between the groups. Participants from the AR group received a tendentially higher flow score, and the AR sham group perceived a tendentially higher feeling of flow than the 2D sham group. Further, participants from the AR group reported a higher technology usability, experienced a higher feeling of control, and perceived themselves as more successful than those from the 2D group. Psychological factors like this are crucial for NF training motivation and success. In the 2D group, participants reported more concern related to their performance, a tendentially higher technology anxiety, and also more physical discomfort. These results show the potential advantage of the use of AR-based feedback in NF applications over traditional feedback modalities. Full article

Announced by WHO in 2020, the global COVID-19 pandemic caused by SARS-CoV-2 has affected many people, leading to serious health consequences. These consequences are observed in the daily lives of infected patients as various dysfunctions and limitations. More and more people are suffering post-COVID-19 complications that interfere with or completely prevent them from working or even functioning independently on a daily basis. The aim of our study was to demonstrate that innovative quantitative electroencephalography (QEEG) can be used to assess cognitive function disorders reported after the COVID-19 pandemic. It is worth noting that no similar study has been conducted to date in a group of pilots. The QEEG method we used is currently one of the basic neurological examinations, enabling easy observation of post-COVID-19 changes in the nervous system. With the innovativeness of this technique, our study shows that the use of quantitative electroencephalography can be a precursor in identifying complications associated with cognitive function disorders after COVID-19. Our study was conducted on twelve 26-year-old pilots. All participants had attended the same flight academy and had contracted SARS-CoV-2 infection. The pilots began to suspect COVID-19 infection when they developed typical symptoms such as loss of smell and taste, respiratory problems, and rapid fatigue. Quantitative electroencephalography (QEEG), which is one of the most innovative forms of diagnostics, was used to diagnose the patients. Comparison of the results between the study and control groups showed significantly higher values of all measurements of alpha, theta, and beta2 waves in the study group. In the case of the sensorimotor rhythm (SMR), the measurement results were significantly higher in the control group compared to the study group. Our study, conducted on pilots who had recovered from COVID-19, showed changes in the amplitudes of brain waves associated with relaxation and concentration. The results confirmed the issues reported by pilots as evidenced by the increased amplitudes of alfa, theta, and beta2 waves. It should be emphasized that the modern diagnostic method (QEEG) presented here has significant importance in the medical diagnosis of various symptoms and observation of treatment effects in individuals who have contracted the SARS-CoV-2 virus. The present study demonstrated an innovative approach to the diagnosis of neurological complications after COVID-19. Full article

Background: Brain injuries are a common problem in combat sports, especially in disciplines such as kickboxing. Kickboxing is a combat sport that has several variations of competition, with the most contact-oriented fights being carried out under the format of K-1 rules. While these sports require a high level of skill and physical endurance, frequent micro-traumas to the brain can have serious consequences for the health and well-being of athletes. According to studies, combat sports are one of the riskiest sports in terms of brain injuries. Among the sports disciplines with the highest number of brain injuries, boxing, mixed martial arts (MMA), and kickboxing are mentioned. Methods: The study was conducted on a group of 18 K-1 kickboxing athletes who demonstrate a high level of sports performance. The subjects were between the ages 18 and 28. QEEG (quantitative electroencephalogram) is a numeric spectral analysis of the EEG record, where the data is digitally coded and statistically analysed using the Fourier transform algorithm. Each examination of one person lasts about 10 min with closed eyes. The wave amplitude and power for specific frequencies (Delta, Theta, Alpha, Sensorimotor Rhythm (SMR), Beta 1, and Beta2) were analysed using 9 leads. Results: High values were shown in the Alpha frequency for central leads, SMR in the Frontal 4 (F4 lead), Beta 1 in leads F4 and Parietal 3 (P3), and Beta2 in all leads. Conclusions: The high activity of brainwaves such as SMR, Beta and Alpha can have a negative effect on the athletic performance of kickboxing athletes by affecting focus, stress, anxiety, and concentration. Therefore, it is important for athletes to monitor their brainwave activity and use appropriate training strategies to achieve optimal results. Full article

A major concern voiced by motor behavior scientists is to find useful practice techniques that can be effective in improving motor learning and performance. Neurofeedback and self-controlled practice are among the techniques that have recently drawn attention from specialists in this area. The present study examined the additive and individual effects of sensorimotor rhythm (SMR) neurofeedback as well as self-controlled practice on motor learning and performance in novice golfers. In this semi-empirical study, forty adults (20 females, Mean_age = 26.10, SD = 5.56 years) were conveniently selected and randomly assigned to four groups: (1) neurofeedback/self-controlled practice, (2) neurofeedback/yoked practice, (3) sham/self-controlled practice, and (4) sham/yoked practice. The participants performed golf putting task in four stages, namely pretest (12 trials), intervention (one day after pretest; 6 sessions, 36 trails each), post-test (one day after intervention; 12 trials), and follow-up (two weeks after interventions; 12 trials). In addition, the participants had their EEG (SMR wave in Cz point) recorded during pretest, post-test, and follow-up. The results indicated that, although no additive effect was observed for the two practices during different stages of the experiment (p > 0.05), in acquisition and post-test stages, SMR neurofeedback and self-controlled practice independently facilitated golf putting (p ≤ 0.05). However, in the follow-up test, only the neurofeedback practice maintained its positive effects (p ≤ 0.05). The results also showed that participation in SMR neurofeedback practice can enhance the power of the SMR wave (p ≤ 0.05), regardless of the type of the self-controlled practice used. In sum, the two practice techniques seem to be independently effective in facilitating motor learning in instructional settings, particularly for golfers. Full article

Brain–computer interfaces (BCIs) are becoming more popular in the neurological rehabilitation field, and sensorimotor rhythm (SMR) is a type of brain oscillation rhythm that can be captured and analyzed in BCIs. Previous reviews have testified to the efficacy of the BCIs, but seldom have they discussed the motor task adopted in BCIs experiments in detail, as well as whether the feedback is suitable for them. We focused on the motor tasks adopted in SMR-based BCIs, as well as the corresponding feedback, and searched articles in PubMed, Embase, Cochrane library, Web of Science, and Scopus and found 442 articles. After a series of screenings, 15 randomized controlled studies were eligible for analysis. We found motor imagery (MI) or motor attempt (MA) are common experimental paradigms in EEG-based BCIs trials. Imagining/attempting to grasp and extend the fingers is the most common, and there were multi-joint movements, including wrist, elbow, and shoulder. There were various types of feedback in MI or MA tasks for hand grasping and extension. Proprioception was used more frequently in a variety of forms. Orthosis, robot, exoskeleton, and functional electrical stimulation can assist the paretic limb movement, and visual feedback can be used as primary feedback or combined forms. However, during the recovery process, there are many bottleneck problems for hand recovery, such as flaccid paralysis or opening the fingers. In practice, we should mainly focus on patients’ difficulties, and design one or more motor tasks for patients, with the assistance of the robot, FES, or other combined feedback, to help them to complete a grasp, finger extension, thumb opposition, or other motion. Future research should focus on neurophysiological changes and functional improvements and further elaboration on the changes in neurophysiology during the recovery of motor function. Full article

Research on sensorimotor rhythms (SMR) based on neurofeedback (NFb) emphasizes improvements in selective attention associated with SMR amplification. However, the long-term training proposed in most studies posed the question of acceptability, which led to the evaluation of the potential of a single NFb session. Based on cognitive and autonomic controls interfering with attention processes, we hypothesized changes in selective attention after a single SMR-NFb session, along with changes in brain–heart interplay, which are reflected in the multifractality of heartbeat dynamics. Here, young healthy participants (n = 35, 20 females, 21 ± 3 years) were randomly assigned either to a control group (Ctrl) watching a movie or to a neurofeedback (NFb) group performing a single session of SMR-NFb. A headset with EEG electrodes (positioned on C3 and C4) connected to a smartphone app served to guide and to evaluate NFb training efficacy. A Stroop task was performed for 8 min by each group before and after the intervention (movie vs. SMR-NFb) while collecting heart rate variability and C4-EEG for 20 min. When compared to Ctrl, the NFb group exhibited better Stroop performance, especially when facing incongruent trials. The multifractality and NFb training efficacy were identified as strong predictors of the gain in global Stroop performance, while multifractality was the only predictor regarding incongruent trials. We conclude that a single session of SMR-NFb improves selective attention in healthy individuals through the specific reorganization of brain–heart interplay, which is reflected in multifractal heartbeat dynamics. Full article

A brain–computer interface (BCI) is a promising technology that can analyze brain signals and control a robot or computer according to a user’s intention. This paper introduces our studies to overcome the challenges of using BCIs in daily life. There are several methods to implement BCIs, such as sensorimotor rhythms (SMR), P300, and steady-state visually evoked potential (SSVEP). These methods have different pros and cons according to the BCI type. However, all these methods are limited in choice. Controlling the robot arm according to the intention enables BCI users can do various things. We introduced the study predicting three-dimensional arm movement using a non-invasive method. Moreover, the study was described compensating the prediction using an external camera for high accuracy. For daily use, BCI users should be able to turn on or off the BCI system because of the prediction error. The users should also be able to change the BCI mode to the efficient BCI type. The BCI mode can be transformed based on the user state. Our study was explained estimating a user state based on a brain’s functional connectivity and a convolutional neural network (CNN). Additionally, BCI users should be able to do various tasks, such as carrying an object, walking, or talking simultaneously. A multi-function BCI study was described to predict multiple intentions simultaneously through a single classification model. Finally, we suggest our view for the future direction of BCI study. Although there are still many limitations when using BCI in daily life, we hope that our studies will be a foundation for developing a practical BCI system. Full article

Quantitative electroencephalography (QEEG) is becoming an increasingly common method of diagnosing neurological disorders and, following the recommendations of The American Academy of Neurology (AAN) and the American Clinical Neurophysiology Society (ACNS), it can be used as a complementary method in the diagnosis of epilepsy, vascular diseases, dementia, and encephalopathy. However, few studies are confirming the importance of QEEG in the diagnosis of mental disorders and changes occurring as a result of therapy; hence, there is a need for analyses in this area. The aim of the study is analysis of the usefulness of QEEG in the diagnosis of people with generalized anxiety disorders. Our research takes the form of case studies. The paper presents an in-depth analysis of the QEEG results of five recently studied people with a psychiatric diagnosis: generalized anxiety disorder. The results show specific pattern amplitudes at C3 and C4. In all of the examined patients, two dependencies are repeated: low contribution of the sensorimotor rhythm (SMR) wave amplitudes and high beta2 wave amplitudes, higher or equal to the alpha amplitudes. The QEEG study provides important information about the specificity of brain waves of people with generalized anxiety disorder; therefore, it enables the preliminary and quick diagnosis of dysfunction. It is also possible to monitor changes due to QEEG, occurring as a result of psychotherapy, pharmacological therapy and EEG-biofeedback. Full article