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Fine-wire electromyography (EMG) is a traditional laboratory technique to estimate muscle activity of the small foot muscles, however, recordings have not been reported from extensor hallucis brevis (EHB). As an extensor of the great toe, EHB is an important muscle when studying physiological changes associated with foot pathologies such as hallux valgus. The purpose of this study was to develop an ultrasound-guided fine-wire EMG protocol to record EHB muscle activity and report normative EMG profiles of healthy young adults during locomotion. Sixteen asymptomatic young adults completed 20 walking trials at a self-selected velocity. Ensemble averages were calculated from the time normalized linear envelopes and represented from 0% to 100% of the single stance phase of gait. EHB muscle bursts were observed between 0% and 20% of the stance phase of gait in all participants. A second burst of EMG was observed between 80% and 100% of stance in 50% of the participants. This study introduces a novel ultrasound-guided EMG protocol and normative data from EHB recordings suggest a synergistic role to anterior compartment musculature at contact. These results provide preliminary insights into understanding the functional role of EHB and may help elucidate the biomechanical factors exacerbating the progression of hallux pathologies. [ABSTRACT FROM AUTHOR]

Context: The quadriceps femoris is consistently ranked among the muscles most prone to sustain strain injuries in sports involving kicking and sprinting actions. Given the documented preventive effect of Nordic hamstring curl programs against hamstring strain injuries, incorporating exercises that induce eccentric overload on the quadriceps could potentially help mitigate strain injuries within this muscle group. The Reverse Nordic Curl (RNC) has emerged as a viable field-based exercise for eccentrically working the quadriceps. This study aimed to compare quadriceps muscle eccentric activation during the RNC with 3 bodyweight squat-based exercises: single-leg squat (SLS), Bulgarian squat, and forward lunge. Design: Cross-sectional study. Methods: Twenty-three healthy volunteers (15 men) were monitored for rectus femoris, vastus lateralis, and vastus medialis electromyographic signal, as well as knee range of motion, while performing 10 repetitions of each exercise. Electromyography data acquired during eccentric phases were normalized by maximum voluntary isometric contraction of the knee extensors. The exercises were compared based on the electromyography and knee range of motion values. Results: RNC generated a similar rectus femoris and vastus medialis eccentric activation compared with the squat-based exercises (P >.05 for all), and a lower vastus lateralis activation than SLS (P <.001). Among the bodyweight squat-based exercises, SLS generated greater eccentric activation than forward lunge and Bulgarian squat for the 3 muscles (P <.05 for all). RNC was performed with lower knee-flexion range of motion than bodyweight squat-based exercises (P <.001). Conclusions: RNC did not produce superior eccentric quadriceps activation compared to bodyweight squat-based exercises, even proving to be less demanding for the vastus lateralis compared to the SLS. These findings may assist practitioners in selecting exercises to elicit quadriceps eccentric stimulus, with a focus on preventing strain injuries. [ABSTRACT FROM AUTHOR]

Introduction: Unlike the most common training approaches for bodybuilding, powerlifting programs are generally based on maximum and submaximal loads, putting enormous stresses on the lumbar spine. The flexion relaxation phenomenon evaluation is a clinical tool used for low back pain (LBP) assessment. This study aimed to evaluate the role of the flexion relaxation phenomenon in the analysis of LBP in the powerlifters. Methods: Healthy professional powerlifters participated in the study. In fact, we divided the participants into a LBP-low-risk group and a LBP-high-risk group, based on a prior history of LBP. Outcome measures included flexion relaxation ratio (FRR) and trough surface electromyography collected during trunk maximum voluntary flexion; furthermore, during a bench press lifting, we measured the height of the arched back (ARCH), using a camera and the Kinovea video editing software, to consider a potential correlation with the risk of LBP. Results: We included a group of 18 male (aged 24–39 y) powerlifters of 93 kg category. We measured a nonsignificant mean difference of ARCH between low-risk LBP group and high-risk LBP subjects. Curiously, maximum voluntary flexions were both above the threshold of 3.2 μV; therefore, with an absence of appropriate myoelectric silence, on the contrary, the FRR ratios were higher than 9.5, considering the presence of the phenomenon, exclusively for the low-risk group. The lumbar arched back measurement data did not report any association with the LBP risk, regarding the maximum voluntary flexion value, and even more than the FRR there is a relationship with the presence or the absence of LBP risk. Conclusions: FRR could be considered as a useful parameter for studying the risk of LBP in powerlifting. The FRR index not only refers to the possible myoelectric silence of the lumbar muscles in trunk maximum forward flexion but also takes into account the energy value delivered by the lumbar muscles during the flexion. Furthermore, we can indicate that the size of the powerlifter ARCH may not be a determining factor in the occurrence of LBP. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) is revolutionizing clinical neurophysiology (CNP), particularly in its applications to electroencephalography (EEG), electromyography (EMG), and polysomnography (PSG). AI enhances diagnostic accuracy and efficiency while addressing interrater variability and the growing data volume. The evolution of AI tools, from early mimetic methods to advanced deep learning techniques, has significantly improved spike and seizure detection in EEG and facilitated whole EEG evaluations, reducing the workload on clinicians. In EMG, AI demonstrates promise in identifying motor unit abnormalities and analyzing audio signals, though challenges persist due to limited datasets and clinical context considerations. PSG scoring has seen substantial integration of AI, with systems achieving high accuracy through uncertainty estimation and selective manual review, but limitations remain in analyzing epileptic activity and classifying certain sleep stages. As a “co-pilot,” AI augments human expertise by improving quality control, standardizing clinical trials, and enabling rapid data review, particularly for less experienced providers. Future AI advancements in CNP aim to shift from isolated data interpretation to providing clinical context, considering patient history, treatment options, and prognostic implications. While the potential of generative AI and “AI-omics” is transformative, the importance of thoughtful integration to augment rather than replace human expertise must be emphasized, ensuring that AI becomes a tool for collaboration and innovation in medicine. [ABSTRACT FROM AUTHOR]

Brain signals and muscle movements have been analyzed using electroencephalogram (EEG) data in several studies. EEG signals contain a lot of noise, such as electromyographic (EMG) waves. Further studies have been done to improve the quality of the results, though it is thought that the combination of these two signals can lead to a significant improvement in the synergistic analysis of muscle movements and muscle connections. Using graph theory, this study examined the interaction of EMG and EEG signals during hand movement and estimated the synergy between muscle and brain signals. Mapping of the brain diagram was also developed to reconstruct the muscle signals from the muscle connections in the brain diagram. The proposed method included noise removal from EEG and EMG signals, graph feature analysis from EEG, and synergy calculation from EMG. Two methods were used to estimate synergy. In the first method, after calculating the brain connections, the features of the communication graph were extracted and then synergy estimating was made with neural networks. In the second method, a convolutional network created a transition from the matrix of brain connections to the synergistic EMG signal. This study reached the high correlation values of 99.8% and maximum MSE error of 0.0084. Compared to other graph-based methods, this method based on regression analysis had a very significant performance. This research can lead to the improvement of rehabilitation methods and brain-computer interfaces. [ABSTRACT FROM AUTHOR]

AimMethodsResultsConclusionTo investigate central and peripheral nervous system activity and muscle oxygenation in athletes during repeated-sprint exercise in normoxia and normobaric hypoxia.The effects on vastus lateralis muscle strength in a cross-over study were examined in 18 athletes (13 males, 5 females) completing 10 × 6-s cycle sprints. Immediately after and again 5 minutes post-exercise, electromyography (EMG), heart rate variability, maximal voluntary contraction (MVC), muscle oxygenation, peak power output, and arterial oxygen saturation were compared to 2 baseline sets named (“Baseline” and “Pre”).Post-exercise MVC was significantly lower (6.7 ± 10.0%) than Baseline, but root-mean-square amplitude during hypoxia (all-times) was significantly lower than normoxia (0.38 ± 0.19 vs 0.41 ± 0.17 mV). Comparative frequency analysis of the percentage change in pre- to post-exercise EMG area, at low 1–29 hz (type-1 fibre) and high 75–100 hz (type-2 fibre) areas, revealed a significant reduction in type-1 fibre activity relative to type-2, by 20–30% across time and by 10% in type-1 activity between conditions.Exercise in hypoxia appeared to cause a temporary increase in central sympathetic nervous system activity and greater recruitment of type-2 muscle fibres, with accompanying reduction in type-1. Acute hypoxia may stimulate type-2 fibre conditioning. [ABSTRACT FROM AUTHOR]

Background: In this study, we evaluated the potential of a network approach to electromyography and electroencephalography recordings to detect covert command-following in healthy participants. The motivation underlying this study was the development of a diagnostic tool that can be applied in common clinical settings to detect awareness in patients that are unable to convey explicit motor or verbal responses, such as patients that suffer from disorders of consciousness (DoC). Methods: We examined the brain and muscle response during movement and imagined movement of simple motor tasks, as well as during resting state. Brain-muscle networks were obtained using non-negative matrix factorization (NMF) of the coherence spectra for all the channel pairs. For the 15/38 participants who showed motor imagery, as indexed by common spatial filters and linear discriminant analysis, we contrasted the configuration of the networks during imagined movement and resting state at the group level, and subject-level classifiers were implemented using as features the weights of the NMF together with trial-wise power modulations and heart response to classify resting state from motor imagery. Results: Kinesthetic motor imagery produced decreases in the mu-beta band compared to resting state, and a small correlation was found between mu-beta power and the kinesthetic imagery scores of the Movement Imagery Questionnaire-Revised Second version. The full-feature classifiers successfully distinguished between motor imagery and resting state for all participants, and brain-muscle functional networks did not contribute to the overall classification. Nevertheless, heart activity and cortical power were crucial to detect when a participant was mentally rehearsing a movement. Conclusions: Our work highlights the importance of combining EEG and peripheral measurements to detect command-following, which could be important for improving the detection of covert responses consistent with volition in unresponsive patients. [ABSTRACT FROM AUTHOR]

This study introduces an innovative method for minimizing artifacts in electroencephalography (EEG) signals by integrating brainstorm optimization (BSO) with a variational autoencoder generative adversarial network (VAE-GAN), resulting in the BrOpt_VAGAN model. EEG signals are critical for the diagnosis of neurological disorders, for brain-computer interface (BCI) applications, and for the monitoring of neurological disabilities. However, EEG data often contains artifacts from physiological sources — such as electrooculographic (EOG), electromyographic (EMG), and electrocardiographic (ECG) signals — which can distort the accuracy of brain activity readings. Our proposed BrOpt_VAGAN model combines BSO with a VAE-GAN framework to more effectively remove these artifacts, thus improving the clarity and accuracy of EEG signals. In this model, the VAE first reduces the raw EEG signals into a lower-dimensional representation that captures the essential signal patterns while filtering out the noise. The GAN component then refines this representation via adversarial training, effectively minimizing artifacts and improving the quality of the processed EEG data. BSO optimally adjusts the encoding and decoding parameters within the VAE-GAN structure, enabling the model to handle different noise levels and helps to find different neurological disorders. Preliminary results show that BrOpt_VAGAN performs significantly better with an accuracy of 98.5 % and an error rate of 11.23 %, enabling a clearer and more precise EEG signal reconstruction. [ABSTRACT FROM AUTHOR]

Introduction: Early increases in muscle strength following unilateral resistance training are typically accompanied by strength gains in the contralateral untrained muscles, a phenomenon known as cross-education. However, the specific motor unit adaptations responsible for this gain transfer remain poorly understood. To address this gap, we recorded myoelectrical activity from the biceps brachii using high-density electromyography. Methods: Nine participants performed 8-week unilateral resistance training and were compared to nine control individuals who did no intervention. Discharge characteristics of longitudinally tracked motor units were assessed during maximal voluntary contractions and isometric ramp contractions at 35% and 70% of the maximal voluntary force (MVF) at baseline (T0), 4 weeks (T1), and 8 weeks (T2) post-intervention. Results: MVF increased by 7% in untrained muscles at T1 and 10% at T2 (p < 0.05). These gains were accompanied by significant decreases in motor unit recruitment thresholds (p < 0.01) and higher net discharge rate (i.e., gain in discharge rate from recruitment to peak) following intervention (p < 0.05). Trained muscles presented greater MVF (+11%, T1; +19%, T2) with similar motor unit adaptations, including a lower recruitment threshold (p < 0.01) and a higher net discharge rate (p < 0.01). Discussion: Our findings indicate that higher strength in untrained muscles is associated with a higher net discharge rate, implying a greater spinal motoneuron output to muscles. The present results underscore the role of motor unit adaptations in the transfer of strength gains to non-trained muscles, offering novel insights into the neural mechanisms underlying cross-education. [ABSTRACT FROM AUTHOR]

We investigated the effects of static and dynamic fatigue on motor synergies, focusing on their hierarchical control. Specifically, we examined whether changes in fatigue influence the central nervous system's ability to preserve movement stability. In addition to exploring the direct impact of fatigue on motor synergies, we also analyzed its effects at two distinct levels of hierarchical control, aiming to elucidate the mechanisms by which fatigue alters motor coordination and stability. Thirteen healthy, young and right-handed male participants took part in the study. Participants performed a bilateral accurate force production task under static and dynamic fatigue conditions at 30% of maximal voluntary contraction level with elbow flexors. Muscle activity level were collected from five muscles of each limb: biceps brachii, brachialis, brachioradialis, flexor carpi radialis, and flexor carpi ulnaris. The results revealed distinct effects of fatigue on isometric force production in the elbow joint tasks. On the higher level of hierarchy control of synergies, there were non-significant effects of different types of fatigue on movement performance, however, on the lower level we observed a strong effect of fatigue on forming motor synergies. There was no significant difference between the type of applied fatigue protocol on force and muscle activity data, nevertheless, the contribution of involved muscles to the task has changed. Our findings indicate that the central nervous system employs specific strategies to counteract fatigue and preserve movement stability during performance. However, the precise mechanisms by which variability at lower levels of hierarchical control influence higher levels remain unclear, highlighting a critical gap in our understanding of motor coordination under fatigue. Future studies should explore how these interactions across hierarchical levels contribute to movement stability under different fatigue conditions. [ABSTRACT FROM AUTHOR]

This study aimed to first investigate changes in electromyography (EMG) patterns after multilevel surgical treatment in patients with cerebral palsy (CP) and then to assess the connection between the measure of EMG and motor control indices and surgery outcomes. We analyzed retrospective EMG and gait data from 167 patients with CP before and after surgery and from 117 typically developed individuals as a reference group. The patients underwent at least one soft tissue surgery on their shank and foot muscles. Using Repeated Measures ANOVA, we examined the norm-distance (ND) of the kinematics, kinetics, and EMG patterns, in addition to the Kerpape-Rennes EMG-based Gait Index (EDI), EMG Profile Score (EPS), and Walking Dynamic Motor Control Index (DMC) before and after surgery. Participants were divided into different response groups (poor, mild, and good gait quality) according to their pre- and post-treatment Gait Deviation Index (GDI), using the K-means-PSO clustering algorithm. The gait and EMG indices were compared between the responders using the nonparametric Mann–Whitney test. The ND for all kinematics and kinetics parameters significantly improved (p-value < 0.05) after the surgery. Regarding EMG, a significant reduction was only observed in the ND of the rectus femoris (p-value < 0.001) and soleus (p-value = 0.006). Among the indices, DMC was not altered post-operatively (p-value = 0.88). Although EDI and EPS were consistent across responders with a similar pre-treatment gait, a higher DMC was significantly associated with a greater improvement, particularly in patients with poor gait (p-value < 0.05). These findings indicate systematic changes in the EMG of patients with CP following surgery, which can also be demonstrated through indices. DMC is a measure that can potentially serve as a partial predictor of outcomes, particularly in patients with poor pre-operative gait. Future research should investigate the effects of different surgical strategies on the improvement of these patients. [ABSTRACT FROM AUTHOR]

• Spinal maps represent spatiotemporal motoneural activation from EMG signals. • A reference dataset of spinal maps in upper limb movements is presented. • Maps were computed on total, phasic (motion-related) and tonic (anti-gravitary) EMG. • Intra-subject and inter-subject similarity of spinal maps were evaluated. Reaching movements are essential for daily tasks and they have been widely investigated through kinematic, kinetic, and electromyographic (EMG) analyses. Recent studies have suggested that the central nervous system simplifies control of reaching movements by using muscle synergies. An alternative approach is to investigate how EMG activity reflects at the neural level with the representation of spinal maps that visualize the spatiotemporal activity of motoneuronal pools. Spinal maps have been rarely used and their investigation could be made by exploiting recent findings in EMG processing such as the separation of phasic (motion-related) and tonic components (anti-gravity). In this study, we aimed at characterizing spinal maps in the upper limb workspace. EMG data from 15 participants were recorded during repeated point-to-point movements toward target boards placed in five orientations. EMG waveforms were divided into total EMG envelope, tonic EMG, and phasic EMG. The multidimensional Pearson's correlation coefficient was used to assess the similarity of spinal maps among repetitions of movements within subjects (intra-subject variability) and among participants (inter-subject variability). Spinal maps of tonic and total EMG showed high intra- and inter-subject similarity in all planes, while phasic spinal maps were less repeatable and more subject-specific. These results may be useful as a reference for rehabilitation, clinical, and neurological evaluations, especially for longitudinal assessments. [ABSTRACT FROM AUTHOR]

Although the dominant hand has been shown to have performance advantages over the nondominant hand, these interlimb differences have found to be dependent on task and biomechanical demands. The dynamic dominance hypothesis suggests that the left hemisphere is specialized for the control of intersegmental dynamics while the nondominant right hemisphere is specialized for postural control, in right-handers. In a real-world scenario, however, cognitive challenges might be expected to modulate these specialized behaviors. Therefore, we hypothesized that with increased cognitive load, lateralized motor control processes would become even more asymmetrical. We recruited 16 right-handed older adults (11 females, 5 males; 65.88 yr ± 1.99 SE) to perform 170 trials of a unilateral reaching task with each of their hands on the Kinereach system. In each trial, participants rapidly memorized pictorial instructions before identifying and reaching for the correct object on a screen. The complexity of the task increased over the course of the experiment. Our results demonstrated higher reaction times in the right than in the left hand (P = 0.0004). Movements became increasingly curved and erroneous with cognitive load, but interlimb differences in movement quality were absent. We found higher joint cocontraction in the right than in the left arm (P < 0.05), but these differences were unaffected by cognitive load. Hence, with the addition of a cognitive load, we observed asymmetries in reaction time but not in joint coordination or movement quality. This highlights the role of cognitive load in modulating limb/hemisphere specializations for control processes. NEW & NOTEWORTHY: Although we know that motor control processes are lateralized to each hemisphere, the role of cognitive load on these specialized processes is undefined. We designed a unique task that incorporates a cognitive challenge to a typical reaching movement to examine how cognitive load affects limb asymmetries in motor control. In a group of typical older adults, we demonstrated interlimb asymmetries in reaction time but not in joint coordination or movement quality. [ABSTRACT FROM AUTHOR]

The number and layout of options within pie menus are crucial for determining the direction of radial swiping in mid-air interactions, influencing the physical demands imposed on users. This research examined six distinct option quantities, referred to as menu breadth, and investigated two layouts, designated as menu orientations. These orientations encompass landscape and portrait formats, with the former positioning a top option centred parallel to the horizontal axis, while the latter situates two top options on either side of the vertical axis. The study employed comprehensive metrics, including muscle activity, wrist movement, user performance, and subjective assessments. Our results indicated that the breadth should be controlled to no more than six to ensure high efficiency and align with users' interactive experience, while breadth 2 should be avoided to eliminate the potential risk of wrist musculoskeletal disorders. Besides, the portrait orientation for breadth 3 and the landscape orientation for breadth 6 were recommended for their lower physiological loads and higher efficiency. Also, the landscape orientation for breadth 4 should be favoured as it outperformed portrait orientation in both wrist movement dimensions. These findings could provide scientific design principles for using pie menus in mid-air interaction within future HCI applications. [ABSTRACT FROM AUTHOR]