Evaluation of movement and brain activity

A Complementary Dual-Mode Ion-Electron Conductive Hydrogel Enables Sustained Conductivity for Prolonged Electroencephalogram Recording

Conductive gel interface materials are widely employed as reliable agents for electroencephalogram (EEG) recording. However, prolonged EEG recording poses challenges in maintaining stable and efficient capture due to inevitable evaporation in hydrogels, which restricts sustained high conductivity. This study introduces a novel ion-electron dual-mode conductive hydrogel synthesized through a cost-effective and streamlined process. By embedding graphite nanoparticles into ionic hyaluronic acid (HAGN), the hydrogel maintains higher conductivity for over 72 h, outperforming commercial gels. Additionally, it exhibits superior low skin contact impedance, considerable electrochemical capability, and excellent tensile and adhesion performance in both dry and wet conditions. The biocompatibility of the HAGN hydrogel, verified through in vitro cell viability assays and in vivo skin irritation tests, underscores its suitability for prolonged skin contact without eliciting adverse reactions. Furthermore, in vivo EEG tests confirm the HAGN hydrogel's capability to provide high-fidelity signal acquisition across multiple EEG protocols. The HAGN hydrogel proves to be an effective interface for prolonged high-quality EEG recording, facilitating high-performance capture and classification of evoked potentials, thereby providing a reliable conductive medium for EEG-based systems.

Connecting the dots - A systematic review on coherence analysis in dystonia

BACKGROUND

Increased 4-12 Hz oscillatory activity in the cortico-basal ganglia-thalamo-cortical (CBGTC) loop is reported in dystonia. Coherence analysis is a measure of linear coupling between two signals, revealing oscillatory activity drives that are common across motor units. By performing coherence analysis, activity of the CBGTC-loop can be measured with modalities like local field potentials (LFPs), electromyography (EMG), and electro-encephalography (EEG). The aim of this study is to perform a systematic review on the use of coherence analysis for clinical assessment and treatment of dystonia.

METHODS

A systematic review was performed on a search in Embase and PubMed on June 28th, 2023. All studies incorporating coherence analysis and an adult dystonia cohort were included. Three authors evaluated the eligibility of the articles. Quality was assessed using the QUADAS-2 checklist.

RESULTS

A total of 41 articles were included, with data of 395 adult dystonia patients. In the selected records, six different types of coherence were investigated: corticocortical, corticopallidal, corticomuscular, pallidopallidal, pallidomuscular, and intermuscular coherence. Various types of 4-12 coherence were found to be increased in all dystonia subtypes.

CONCLUSION

There is increased 4-12 Hz coherence found between the cortex, basal ganglia, and affected muscles in all dystonia subtypes. However, the relationship between 4-12 Hz coherence and the dystonic clinical state has not been established. DBS treatment leads to a reduction of 4-12 Hz coherence. In combination with the results of this review, the 4-12 Hz frequency band can be used as a promising phenomenon for the development of a biomarker.

Leg stereotypy syndrome: phenomenological and quantitative analysis

BACKGROUND

Leg stereotypy syndrome (LSS) is a very common, yet underrecognized condition. The pathophysiology of the condition is not well understood.

OBJECTIVE

To evaluate and describe the visual kinematic characteristics of the repetitive leg movements in individuals with LSS.

METHODS

In this study, we identified and videotaped individuals diagnosed with LSS at the Parkinson's Disease Center and Movement Disorders Clinic, Baylor College of Medicine, Houston, Texas between 2000 and 2023. Only patients with LSS and without any co-morbidities were included in the study. Their medical records were carefully reviewed, and the demographic and clinical data were entered into a database. Video recordings of the repetitive leg movements were then analyzed using TremAn software.

RESULTS

We identified 14 individuals with LSS who were videotaped at our center. The videos of the 5 cases were too brief and therefore not suitable for TremAn quantitative analysis. The remaining 9 individuals exhibited regular rhythmic oscillations of the legs. Among these, two individuals displayed rhythmic movements only in video segments where their legs were in crossed positions. The other 7 individuals had regular rhythmic oscillations, always with the toes resting on the floor with the heels raised. Frequency analysis showed values between 4.5 and 6.5 Hz, fairly consistent with a variance below 0.5 Hz in individual cases. The oscillation frequency changed from 5.7 Hz to 2.7 Hz while standing.

CONCLUSION

In this study, 6 of 9 individuals with LSS showed 4.5-6.5 Hz regular rhythmic leg movements. Studies involving a larger LSS population with additional electrophysiological evaluations are needed to obtain further insights into this common movement disorder.

Magnetoencephalography for the pediatric population, indications, acquisition and interpretation for the clinician

Magnetoencephalography (MEG) is an imaging technique that enables the assessment of cortical activity via direct measures of neurophysiology. It is a non-invasive and passive technique that is completely painless. MEG has gained increasing prominence in the field of pediatric neuroimaging. This dedicated review article for the pediatric population summarizes the fundamental technical and clinical aspects of MEG for the clinician. We discuss methods tailored for children to improve data quality, including child-friendly MEG facility environments and strategies to mitigate motion artifacts. We provide an in-depth overview on accurate localization of neural sources and different analysis methods, as well as data interpretation. The contemporary platforms and approaches of two quaternary pediatric referral centers are illustrated, shedding light on practical implementations in clinical settings. Finally, we describe the expanding clinical applications of MEG, including its pivotal role in presurgical evaluation of epilepsy patients, presurgical mapping of eloquent cortices (somatosensory and motor cortices, visual and auditory cortices, lateralization of language), its emerging relevance in autism spectrum disorder research and potential future clinical applications, and its utility in assessing mild traumatic brain injury. In conclusion, this review serves as a comprehensive resource of clinicians as well as researchers, offering insights into the evolving landscape of pediatric MEG. It discusses the importance of technical advancements, data acquisition strategies, and expanding clinical applications in harnessing the full potential of MEG to study neurological conditions in the pediatric population.

Biomechanical Assessment Methods Used in Chronic Stroke: A Scoping Review of Non-Linear Approaches

Non-linear and dynamic systems analysis of human movement has recently become increasingly widespread with the intention of better reflecting how complexity affects the adaptability of motor systems, especially after a stroke. The main objective of this scoping review was to summarize the non-linear measures used in the analysis of kinetic, kinematic, and EMG data of human movement after stroke. PRISMA-ScR guidelines were followed, establishing the eligibility criteria, the population, the concept, and the contextual framework. The examined studies were published between 1 January 2013 and 12 April 2023, in English or Portuguese, and were indexed in the databases selected for this research: PubMed®, Web of Science®, Institute of Electrical and Electronics Engineers®, Science Direct® and Google Scholar®. In total, 14 of the 763 articles met the inclusion criteria. The non-linear measures identified included entropy (n = 11), fractal analysis (n = 1), the short-term local divergence exponent (n = 1), the maximum Floquet multiplier (n = 1), and the Lyapunov exponent (n = 1). These studies focused on different motor tasks: reaching to grasp (n = 2), reaching to point (n = 1), arm tracking (n = 2), elbow flexion (n = 5), elbow extension (n = 1), wrist and finger extension upward (lifting) (n = 1), knee extension (n = 1), and walking (n = 4). When studying the complexity of human movement in chronic post-stroke adults, entropy measures, particularly sample entropy, were preferred. Kinematic assessment was mainly performed using motion capture systems, with a focus on joint angles of the upper limbs.

Cross-frequency cortex-muscle interactions are abnormal in young people with dystonia

Sensory processing and sensorimotor integration are abnormal in dystonia, including impaired modulation of beta-corticomuscular coherence. However, cortex-muscle interactions in either direction are rarely described, with reports limited predominantly to investigation of linear coupling, using corticomuscular coherence or Granger causality. Information-theoretic tools such as transfer entropy detect both linear and non-linear interactions between processes. This observational case-control study applies transfer entropy to determine intra- and cross-frequency cortex-muscle coupling in young people with dystonia/dystonic cerebral palsy. Fifteen children with dystonia/dystonic cerebral palsy and 13 controls, aged 12-18 years, performed a grasp task with their dominant hand. Mechanical perturbations were provided by an electromechanical tapper. Bipolar scalp EEG over contralateral sensorimotor cortex and surface EMG over first dorsal interosseous were recorded. Multi-scale wavelet transfer entropy was applied to decompose signals into functional frequency bands of oscillatory activity and to quantify intra- and cross-frequency coupling between brain and muscle. Statistical significance against the null hypothesis of zero transfer entropy was established, setting individual 95% confidence thresholds. The proportion of individuals in each group showing significant transfer entropy for each frequency combination/direction was compared using Fisher's exact test, correcting for multiple comparisons. Intra-frequency transfer entropy was detected in all participants bidirectionally in the beta (16-32 Hz) range and in most participants from EEG to EMG in the alpha (8-16 Hz) range. Cross-frequency transfer entropy across multiple frequency bands was largely similar between groups, but a specific coupling from low-frequency EMG to beta EEG was significantly reduced in dystonia [P = 0.0061 (corrected)]. The demonstration of bidirectional cortex-muscle communication in dystonia emphasizes the value of transfer entropy for exploring neural communications in neurological disorders. The novel finding of diminished coupling from low-frequency EMG to beta EEG in dystonia suggests impaired cortical feedback of proprioceptive information with a specific frequency signature that could be relevant to the origin of the excessive low-frequency drive to muscle.

Clinical neurophysiology of functional motor disorders: IFCN Handbook Chapter

Functional Motor Disorders are common and disabling. Clinical diagnosis has moved from one of exclusion of other causes for symptoms to one where positive clinical features on history and examination are used to make a "rule in" diagnosis wherever possible. Clinical neurophysiological assessments have developed increasing importance in assisting with this positive diagnosis, not being used simply to demonstrate normal sensory-motor pathways, but instead to demonstrate specific abnormalities that help to positively diagnose these disorders. Here we provide a practical review of these techniques, their application, interpretation and pitfalls. We also highlight particular areas where such tests are currently lacking in sensitivity and specificity, for example in people with functional dystonia and functional tic-like movements.

Action-rule-based cognitive control enables efficient execution of stimulus-response conflict tasks: a model validation of Simon task performance

Introduction

The human brain can flexibly modify behavioral rules to optimize task performance (speed and accuracy) by minimizing cognitive load. To show this flexibility, we propose an action-rule-based cognitive control (ARC) model. The ARC model was based on a stochastic framework consistent with an active inference of the free energy principle, combined with schematic brain network systems regulated by the dorsal anterior cingulate cortex (dACC), to develop several hypotheses for demonstrating the validity of the ARC model.

Methods

A step-motion Simon task was developed involving congruence or incongruence between important symbolic information (illustration of a foot labeled "L" or "R," where "L" requests left and "R" requests right foot movement) and irrelevant spatial information (whether the illustration is actually of a left or right foot). We made predictions for behavioral and brain responses to testify to the theoretical predictions.

Results

Task responses combined with event-related deep-brain activity (ER-DBA) measures demonstrated a key contribution of the dACC in this process and provided evidence for the main prediction that the dACC could reduce the Shannon surprise term in the free energy formula by internally reversing the irrelevant rapid anticipatory postural adaptation. We also found sequential effects with modulated dip depths of ER-DBA waveforms that support the prediction that repeated stimuli with the same congruency can promote remodeling of the internal model through the information gain term while counterbalancing the surprise term.

Discussion

Overall, our results were consistent with experimental predictions, which may support the validity of the ARC model. The sequential effect accompanied by dip modulation of ER-DBA waveforms suggests that cognitive cost is saved while maintaining cognitive performance in accordance with the framework of the ARC based on 1-bit congruency-dependent selective control.

Posturography Approaches: An Insightful Window to Explore the Role of the Brain in Socio-Affective Processes

A significant amount of research has highlighted the importance of a motor component in the brain's processing of emotional, motivational and social information. Posturography has emerged as an interesting way to assess motor correlates associated with this process. In this review, we highlight recent results within the functional context of painful stimulus perception and discuss the interest in broadening the use of posturography to other motivational and societal functional contexts. Although characterized by significant feasibility, the single measurement of the COP's anteroposterior displacement presents limitations for attesting approach-avoidance behavior towards a visual target. Here, we discuss a number of methodological avenues that could go some way towards overcoming these limitations.

Supplementary Motor Area Activity Differs in Parkinson's Disease with and without Freezing of Gait

The study aimed to investigate the neural changes that differentiate Parkinson's disease patients with freezing of gait and age-matched controls, using ambulatory electroencephalography event-related features. Compared to controls, definite freezers exhibited significantly less alpha desynchronization at the motor cortex about 300 ms before and after the start of overground walking and decreased low-beta desynchronization about 300 ms before and about 300 and 700 ms after walking onset. The late slope of motor potentials also differed in the sensory and motor areas between groups of controls, definite, and probable freezers. This difference was found both in preparation and during the execution of normal walking. The average frontal peak of motor potential was also found to be largely reduced in the definite freezers compared with the probable freezers and controls. These findings provide valuable insights into the underlying structures that are affected in patients with freezing of gait, which could be used to tailor drug development and personalize drug care for disease subtypes. In addition, the study's findings can help in the evaluation and validation of nonpharmacological therapies for patients with Parkinson's disease.

EMG-projected MEG High-Resolution Source Imaging of Human Motor Execution: Brain-Muscle Coupling above Movement Frequencies

Magnetoencephalography (MEG) is a non-invasive functional imaging technique for pre-surgical mapping. However, movement-related MEG functional mapping of primary motor cortex (M1) has been challenging in presurgical patients with brain lesions and sensorimotor dysfunction due to the large numbers of trails needed to obtain adequate signal to noise. Moreover, it is not fully understood how effective the brain communication is with the muscles at frequencies above the movement frequency and its harmonics. We developed a novel Electromyography (EMG)-projected MEG source imaging technique for localizing M1 during ~1 minute recordings of left and right self-paced finger movements (~1 Hz). High-resolution MEG source images were obtained by projecting M1 activity towards the skin EMG signal without trial averaging. We studied delta (1-4 Hz), theta (4-7 Hz), alpha (8-12 Hz), beta (15-30 Hz), and gamma (30-90 Hz) bands in 13 healthy participants (26 datasets) and two presurgical patients with sensorimotor dysfunction. In healthy participants, EMG-projected MEG accurately localized M1 with high accuracy in delta (100.0%), theta (100.0%), and beta (76.9%) bands, but not alpha (34.6%) and gamma (0.0%) bands. Except for delta, all other frequency bands were above the movement frequency and its harmonics. In both presurgical patients, M1 activity in the affected hemisphere was also accurately localized, despite highly irregular EMG movement patterns in one patient. Altogether, our EMG-projected MEG imaging approach is highly accurate and feasible for M1 mapping in presurgical patients. The results also provide insight into movement related brain-muscle coupling above the movement frequency and its harmonics.

Wearable Electromyography Classification of Epileptic Seizures: A Feasibility Study

Accurate diagnosis and classification of epileptic seizures can greatly support patient treatments. As many epileptic seizures are convulsive and have a motor component, the analysis of muscle activity can provide valuable information for seizure classification. Therefore, this paper present a feasibility study conducted on healthy volunteers, focusing on tracking epileptic seizures movements using surface electromyography signals (sEMG) measured on human limb muscles. For the experimental studies, first, compact wireless sensor nodes were developed for real-time measurement of sEMG on the gastrocnemius, flexor carpi ulnaris, biceps brachii, and quadriceps muscles on the right side and the left side. For the classification of the seizure, a machine learning model has been elaborated. The 16 common sEMG time-domain features were first extracted and examined with respect to discrimination and redundancy. This allowed the features to be classified into irrelevant features, important features, and redundant features. Redundant features were examined with the Big-O notation method and with the average execution time method to select the feature that leads to lower complexity and reduced processing time. The finally selected six features were explored using different machine learning classifiers to compare the resulting classification accuracy. The results show that the artificial neural network (ANN) model with the six features: IEMG, WAMP, MYOP, SE, SKEW, and WL, had the highest classification accuracy (99.95%). A further study confirms that all the chosen eight sensors are necessary to reach this high classification accuracy.

Revisiting the use of Hoffmann reflex in motor control research on humans

Research in movement science aims at unravelling mechanisms and designing methods for restoring and maximizing human functional capacity, and many techniques provide access to neural adjustments (acute changes) or long-term adaptations (chronic changes) underlying changes in movement capabilities. First described by Paul Hoffmann over a century ago, when an electrical stimulus is applied to a peripheral nerve, this causes action potentials in afferent axons, primarily the Ia afferents of the muscle spindles, which recruit homonymous motor neurons, thereby causing an electromyographic response known as the Hoffmann (H) reflex. This technique is a valuable tool in the study of the neuromuscular function in humans and has provided relevant information in the neural control of movement. The large use of the H reflex in motor control research on humans relies in part to its relative simplicity. However, such simplicity masks subtleties that require rigorous experimental protocols and careful data interpretation. After highlighting basic properties and methodological aspects that should be considered for the correct use of the H-reflex technique, this brief narrative review discusses the purpose of the H reflex and emphasizes its use as a tool to assess the effectiveness of Ia afferents in discharging motor neurones. The review also aims to reconsider the link between H-reflex modulation and Ia presynaptic inhibition, the use of the H-reflex technique in motor control studies, and the effects of ageing. These aspects are summarized as recommendations for the use of the H reflex in motor control research on humans.

Experiment protocols for brain-body imaging of locomotion: A systematic review

Introduction

Human locomotion is affected by several factors, such as growth and aging, health conditions, and physical activity levels for maintaining overall health and well-being. Notably, impaired locomotion is a prevalent cause of disability, significantly impacting the quality of life of individuals. The uniqueness and high prevalence of human locomotion have led to a surge of research to develop experimental protocols for studying the brain substrates, muscle responses, and motion signatures associated with locomotion. However, from a technical perspective, reproducing locomotion experiments has been challenging due to the lack of standardized protocols and benchmarking tools, which impairs the evaluation of research quality and the validation of previous findings.

Methods

This paper addresses the challenges by conducting a systematic review of existing neuroimaging studies on human locomotion, focusing on the settings of experimental protocols, such as locomotion intensity, duration, distance, adopted brain imaging technologies, and corresponding brain activation patterns. Also, this study provides practical recommendations for future experiment protocols.

Results

The findings indicate that EEG is the preferred neuroimaging sensor for detecting brain activity patterns, compared to fMRI, fNIRS, and PET. Walking is the most studied human locomotion task, likely due to its fundamental nature and status as a reference task. In contrast, running has received little attention in research. Additionally, cycling on an ergometer at a speed of 60 rpm using fNIRS has provided some research basis. Dual-task walking tasks are typically used to observe changes in cognitive function. Moreover, research on locomotion has primarily focused on healthy individuals, as this is the scenario most closely resembling free-living activity in real-world environments.

Discussion

Finally, the paper outlines the standards and recommendations for setting up future experiment protocols based on the review findings. It discusses the impact of neurological and musculoskeletal factors, as well as the cognitive and locomotive demands, on the experiment design. It also considers the limitations imposed by the sensing techniques used, including the acceptable level of motion artifacts in brain-body imaging experiments and the effects of spatial and temporal resolutions on brain sensor performance. Additionally, various experiment protocol constraints that need to be addressed and analyzed are explained.

Altered cerebellar-motor loop in benign adult familial myoclonic epilepsy type 1: The structural basis of cortical tremor

OBJECTIVE

Cortical tremor/myoclonus is the hallmark feature of benign adult familial myoclonic epilepsy (BAFME), the mechanism of which remains elusive. A hypothesis is that a defective control in the preexisting cerebellar-motor loop drives cortical tremor. Meanwhile, the basal ganglia system might also participate in BAFME. This study aimed to discover the structural basis of cortical tremor/myoclonus in BAFME.

METHODS

Nineteen patients with BAFME type 1 (BAFME1) and 30 matched healthy controls underwent T1-weighted and diffusion tensor imaging scans. FreeSurfer and spatially unbiased infratentorial template (SUIT) toolboxes were utilized to assess the motor cortex and the cerebellum. Probabilistic tractography was generated for two fibers to test the hypothesis: the dentato-thalamo-(M1) (primary motor cortex) and globus pallidus internus (GPi)-thalamic projections. Average fractional anisotropy (FA), axial diffusivity (AD), mean diffusivity (MD), and radial diffusivity (RD) of each tract were extracted.

RESULTS

Cerebellar atrophy and dentate nucleus alteration were observed in the patients. In addition, patients with BAFME1 exhibited reduced AD and FA in the left and right dentato-thalamo-M1 nondecussating fibers, respectively false discovery rate (FDR) correction q < .05. Cerebellar projections showed negative correlations with somatosensory-evoked potential P25-N33 amplitude and were independent of disease duration and medication. BAFME1 patients also had increased FA and decreased MD in the left GPi-thalamic projection. Higher FA and lower RD in the right GPi-thalamic projection were also observed (FDR q < .05).

SIGNIFICANCE

The present findings support the hypothesis that the cerebello-thalamo-M1 loop might be the structural basis of cortical tremor in BAFME1. The basal ganglia system also participates in BAFME1 and probably serves a regulatory role.

Synchronous analyses between electroencephalogram and surface electromyogram based on motor imagery and motor execution

The functional coupling of the cerebral cortex and muscle contraction indicates that electroencephalogram (EEG) and surface electromyogram (sEMG) signals are coherent. The objective of this study is to clearly describe the coupling relationship between EEG and sEMG through a variety of analysis methods. We collected the EEG and sEMG data of left- or right-hand motor imagery and motor execution from six healthy subjects and six stroke patients. To enhance the coherence coefficient between EEG and sEMG signals, the algorithm of EEG modification based on the peak position of sEMG signals is proposed. Through analyzing a variety of signal synchronization analysis methods, the most suitable coherence analysis algorithm is selected. In addition, the wavelet coherence analysis method based on time spectrum estimation was used to study the linear correlation characteristics of the frequency domain components of EEG and sEMG signals, which verified that wavelet coherence analysis can effectively describe the temporal variation characteristics of EEG-sEMG coherence. In the task of motor imagery, the significant EEG-sEMG coherence is mainly in the imagination process with the frequency distribution of the alpha and beta frequency bands; in the task of motor execution, the significant EEG-sEMG coherence mainly concentrates before and during the task with the frequency distribution of the alpha, beta, and gamma frequency bands. The results of this study may provide a theoretical basis for the cooperative working mode of neurorehabilitation training and introduce a new method for evaluating the functional state of neural rehabilitation movement.

Clinical neurophysiology of Parkinson's disease and parkinsonism

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This review is part of the series on the clinical neurophysiology of movement disorders and focuses on Parkinson’s disease and parkinsonism.

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The pathophysiology of cardinal parkinsonian motor symptoms and myoclonus are reviewed.

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The recordings from microelectrode and deep brain stimulation electrodes are reported in detail.

This review is part of the series on the clinical neurophysiology of movement disorders. It focuses on Parkinson’s disease and parkinsonism. The topics covered include the pathophysiology of tremor, rigidity and bradykinesia, balance and gait disturbance and myoclonus in Parkinson’s disease. The use of electroencephalography, electromyography, long latency reflexes, cutaneous silent period, studies of cortical excitability with single and paired transcranial magnetic stimulation, studies of plasticity, intraoperative microelectrode recordings and recording of local field potentials from deep brain stimulation, and electrocorticography are also reviewed. In addition to advancing knowledge of pathophysiology, neurophysiological studies can be useful in refining the diagnosis, localization of surgical targets, and help to develop novel therapies for Parkinson’s disease.

Dystonia, chorea, hemiballismus and other dyskinesias

Hyperkinesias are heterogeneous involuntary movements that significantly differ in terms of clinical and semeiological manifestations, including rhythm, regularity, speed, duration, and other factors that determine their appearance or suppression. Hyperkinesias are due to complex, variable, and largely undefined pathophysiological mechanisms that may involve different brain areas. In this chapter, we specifically focus on dystonia, chorea and hemiballismus, and other dyskinesias, specifically, levodopa-induced, tardive, and cranial dyskinesia. We address the role of neurophysiological studies aimed at explaining the pathophysiology of these conditions. We mainly refer to human studies using surface and invasive in-depth recordings, as well as spinal, brainstem, and transcortical reflexology and non-invasive brain stimulation techniques. We discuss the extent to which the neurophysiological abnormalities observed in hyperkinesias may be explained by pathophysiological models. We highlight the most relevant issues that deserve future research efforts. The potential role of neurophysiological assessment in the clinical context of hyperkinesia is also discussed.

Creating IoT-Enriched Learner-Centered Environments in Sports Science Higher Education during the Pandemic

In the pandemic context, creating IoT-enriched learner-centered environments was not only a tendency but a requirement for sustainable teaching and learning in universities with sports science programs for theoretical classes and practical activities. Our study aims to assess both the extent to which the sports science academic environment has been prepared for online teaching and the key features of dedicated e-learning teaching and training in sports science to provide the highest-quality educational services in pandemic conditions. An online survey was administered to academic staff in the field of sports science from two Romanian universities. The results of the study reveal that online teaching has been associated with major changes in terms of methods and methodology, but also with a new dynamic of external and internal factors regarding teachers and their relationship with students. At the same time, it depends on a solid specific infrastructure and IoT facilities (MOOCs, VR/AR, mobile devices). As a mirror of the student-centered approach, universities in the field of sports science have experienced the same concerns about the outcomes of the educational process. In this regard, universities can become sustainable if they positively integrate e-learning into their teaching system and consolidate their quality standards from an e-learning perspective.