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Active systems of self-propelled agents, e.g., birds, fish, and bacteria, can organize their collective motion into myriad autonomous behaviors. Ubiquitous in nature and across length scales, such phenomena are also amenable to artificial settings, e.g., where brainless self-propelled robots orchestrate their movements into spatial-temporal patterns via the application of external cues or when confined within flexible boundaries. Like their natural counterparts, these approaches typically require many units to initiate collective motion, so controlling the ensuing dynamics is challenging. Here, we demonstrate a simple mechanism that leverages nonlinear elasticity to tame near-diffusive motile particles in forming structures capable of directed motion and other emergent behaviors. Our elasto-active system comprises two centimeter-sized self-propelled microbots connected with elastic beams. These microbots exert forces that suffice to buckle the beam and set the structure in motion. We first rationalize the physics of the interaction between the beam and the microbots. Then we use reduced-order models to predict the interactions of our elasto-active structures with boundaries, e.g., walls and constrictions, and demonstrate how they can exhibit remarkable emergent behaviors such as maze navigation. These findings demonstrate that allowing and understanding changes in body morphology can enhance the capabilities of active matter systems and enable the design of robotic materials capable of space exploration, adaptation, and complex interactions with their surrounding environment., Competing Interests: Competing interests statement:The authors declare no competing interest.

Abstract: Zhitao, L, Junlong, D, Rui, Y, Leijiao, Y, Cheng, G, and Jun, Y. Relationships between functional movement quality and sports performance in elite figure skating athletes of China. J Strength Cond Res 38(11): e678-e685, 2024-This study aimed to determine the optimal functional movement screen (FMS) cut score for assessing the risk of sports injuries and to explore the correlations between functional movement quality and sports performance among elite figure skaters. A total of 22 elite figure pairs skaters in China underwent FMS, sports performance, and clinical examinations for sports injuries. The FMS cut score was determined using the receiver operating characteristic curve. Pearson's rank correlation analysis was used to quantify associations between the variables. (a) The optimal FMS cut score for assessing the risk of sports injuries was 13 (p = 0.008), with an area under curve of 0.838. The sensitivity and specificity were 0.889 and 0.692, respectively. (b) The trunk stability push-up (TSPU), an individual FMS test, predicted injuries in figure skaters (p = 0.015). (c) Moderate correlations were found between shoulder mobility and bench strength (r = -0.453, p = 0.034), counter movement jump (r = -0.582, p = 0.007), and 30-m sprint (r = 0.567, p = 0.009). A strong correlation was observed with squat jump (r = -0.774, p = 0.001). In addition, TSPU scores moderately correlated with 30-m sprint times (r = -0.511, p = 0.021) and 30-s average anaerobic power (r = 0.503, p = 0.024). These findings indicate that both the FMS total score ≤13 and the FMS individual score serve as indicators of injury risk in figure skaters. However, only the FMS individual score reflected the sports performance. This likely results from the similarity in kinetic chain systems and movement patterns involved in both the FMS individual test and sports performance, suggesting a promising assessment strategy for sports performance., (Copyright © 2024 National Strength and Conditioning Association.)

This study investigated differences in electroencephalography (EEG) activity within motor-related brain areas during three phases of a single-leg squat (SLS)-i.e., descending, holding, and ascending phases. Specifically, utilizing advanced magnetic resonance imaging guided EEG source localization techniques and markerless motion capture technology, we explored the interplay between concurrently recorded lower-extremity biomechanics and brain activity. Among the phases of a nondominant leg SLS, differences in contralateral brain activity (right hemisphere) were found in the activity of the precentral gyrus, the postcentral gyrus, and the sensory motor area. Alternatively, during the dominant SLS leg, differences among the three SLS phases in contralateral brain activity were fewer. Hemispheric dependent brain activity also significantly correlated with participants' knee valgus angle range of motion (right hemisphere) and peak knee valgus angles (left hemisphere). In addition to the novel brain and biomechanical findings, this study sheds light on the technical feasibility of recording EEG during complex multi-joint movements and its potential applications in understanding sensorimotor behavior., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

We explored in 75 s long trials the effects of visually induced self-rotation and displacement (SR&D) on the horizontally extended right arm of standing subjects (N = 12). A "tool condition" was included in which subjects held a long rod. The extent of arm movement was contingent on whether the arm was extended out Freely or Pointing at a briefly proprioceptively specified target position. The results were nearly identical when subjects held the rod. Subjects in the Free conditions showed significant unintentional arm deviations, averaging 55° in the direction opposite the induced illusory self-motion. Deviations in the Pointing conditions were on average a fifth of those in the Free condition. Deviations of head and torso positions also occurred in all conditions. Total arm and head deviations were the sum of deviations of the arm and head with respect to the torso and deviations of the torso with respect to space. Pointing subjects were able to detect and correct for arm and head deviations with respect to the torso but not for the arm and head deviations with respect to space due to deviations of the torso. In all conditions, arm, head, and torso deviations began before subjects experienced SR&D. We relate our findings to being an extension of the manual following response (MFR) mechanism to influence passive arm control and arm target maintenance as well. Visual-vestibular convergence at vestibular nuclei cells and multiple cortical movement related areas can explain our results, MFR results, and classical Pass Pointing. We distinguish two Phases in the induction of SR&D. In Phase 1, the visual stimulation period prior to SR&D onset, the arm, head, and torso deviations are first apparent, circa < 1 s after stimulus begins. They are augmented at the onset of Phase 2 that starts when SR&D is first sensed. In Phase 2, reaching movements first show curved paths that are compensatory for the Coriolis forces that would be generated on the reaching arm were subjects actually physically rotating. These movement deviations are in the opposite direction to the MFR and the arm, head, and torso deviations reported here. Our results have implications for vehicle control in environments that can induce illusory self motion and displacement., (© 2024. The Author(s).)

We present HOIMotion - a novel approach for human motion forecasting during human-object interactions that integrates information about past body poses and egocentric 3D object bounding boxes. Human motion forecasting is important in many augmented reality applications but most existing methods have only used past body poses to predict future motion. HOIMotion first uses an encoder-residual graph convolutional network (GCN) and multi-layer perceptrons to extract features from body poses and egocentric 3D object bounding boxes, respectively. Our method then fuses pose and object features into a novel pose-object graph and uses a residual-decoder GCN to forecast future body motion. We extensively evaluate our method on the Aria digital twin (ADT) and MoGaze datasets and show that HOIMotion consistently outperforms state-of-the-art methods by a large margin of up to 8.7% on ADT and 7.2% on MoGaze in terms of mean per joint position error. Complementing these evaluations, we report a human study (N=20) that shows that the improvements achieved by our method result in forecasted poses being perceived as both more precise and more realistic than those of existing methods. Taken together, these results reveal the significant information content available in egocentric 3D object bounding boxes for human motion forecasting and the effectiveness of our method in exploiting this information.

Brain-computer interfaces (BCI) are widely used in the field of disability assistance and rehabilitation, and virtual reality (VR) is increasingly used for visual guidance of BCI-MI (motor imagery). Therefore, how to improve the quality of electroencephalogram (EEG) signals for MI in VR has emerged as a critical issue. People can perform MI more easily when they visualize the hand used for visual guidance as their own, and the Rubber Hand Illusion (RHI) can increase people's ownership of the prosthetic hand. We proposed to induce RHI in VR to enhance participants' MI ability and designed five methods of inducing RHI, namely active movement, haptic stimulation, passive movement, active movement mixed with haptic stimulation, and passive movement mixed with haptic stimulation, respectively. We constructed a first-person training scenario to train participants' MI ability through the five induction methods. The experimental results showed that through the training, the participants' feeling of ownership of the virtual hand in VR was enhanced, and the MI ability was improved. Among them, the method of mixing active movement and tactile stimulation proved to have a good effect on enhancing MI. Finally, we developed a BCI system in VR utilizing the above training method, and the performance of the participants improved after the training. This also suggests that our proposed method is promising for future application in BCI rehabilitation systems.

In overt movement, internal models make predictions about the sensory consequences of a desired movement, generating the appropriate motor commands to achieve that movement. Using available sensory feedback, internal models are updated to allow for movement adaptation and in-turn better performance. Whether internal models are updated during motor imagery, the mental rehearsal of movement, is not well established. To investigate internal modelling during motor imagery, 66 participants were exposed to a leftwards prism shift while performing actual pointing movements (physical practice; PP), imagined pointing movements (motor imagery; MI), or no pointing movements (control). If motor imagery updates internal models, we hypothesized that aftereffects (pointing in the direction opposite the prism shift) would be observed in MI, like that of PP, and unlike that of control. After prism exposure, the magnitude of aftereffects was significant in PP (4.73° ± 1.56°), but not in MI (0.34° ± 0.96°) and control (0.34° ± 1.04°). Accordingly, PP differed significantly from MI and control. Our results show that motor imagery does not update internal models, suggesting that it is not a direct simulation of overt movement. Furthering our understanding of the mechanisms that underlie learning through motor imagery will lead to more effective applications of motor imagery., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Background: Reaching and grasping (R&G) in rats is commonly used as an outcome measure to investigate the effectiveness of rehabilitation or treatment strategies to recover forelimb function post spinal cord injury. Kinematic analysis has been limited to the wrist and digit movements. Kinematic profiles of the more proximal body segments that play an equally crucial role in successfully executing the task remain unexplored. Additionally, understanding of different forelimb muscle activity, their interactions, and their correlation with the kinematics of R&G movement is scarce., New Method: In this work, novel methodologies to comprehensively assess and quantify the 3D kinematics of the proximal and distal forelimb joints along with associated muscle activity during R&G movements in adult rats are developed and discussed., Results: Our data show that different phases of R&G identified using the novel kinematic and EMG-based approach correlate with the well-established descriptors of R&G stages derived from the Whishaw scoring system. Additionally, the developed methodology allows describing the temporal activity of individual muscles and associated mechanical and physiological properties during different phases of the motor task., Comparison With Existing Method(s): R&G phases and their sub-components are identified and quantified using the developed kinematic and EMG-based approach. Importantly, the identified R&G phases closely match the well-established qualitative descriptors of the R&G task proposed by Whishaw and colleagues., Conclusions: The present work provides an in-depth objective analysis of kinematics and EMG activity of R&G behavior, paving the way to a standardized approach to assessing this critical rodent motor function in future studies., Competing Interests: Declaration of Competing Interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Objectives: We aimed to investigate the effects of ankle taping on lower extremity biomechanics related to injury development and how these effects change after sports-specific use., Design: Randomized, repeated measures design with three conditions: Barefoot, tape applied fresh, and tape after sports-specific use (between-subject factor: sex)., Methods: Twenty-five healthy participants (ten female) performed sports-specific movements, including running, drop jumping, and 180° change of direction, under the three conditions. Kinetic and kinematic data were collected using 3D motion capturing and force platforms., Results: Tape applied fresh and tape after sports-specific use significantly reduced peak ankle inversion. Biomechanical risk factors for anterior cruciate ligament or running overuse injuries were either unchanged or decreased with tape applied fresh, except for the peak loading rate of the resultant ground reaction force, which increased between 4% and 18% between movement types. After 15 minutes of sports-specific use of the tape, the alterations induced by tape applied fresh remained for some biomechanical risk factors while they became closer to barefoot again for others, indicating a differential response to prolonged use of taping for different biomechanical variables., Conclusions: Ankle taping protects the ankle joint by reducing biomechanical risk factors associated with ankle sprains, and most biomechanical risk factors for anterior cruciate ligament or running overuse injuries are not increased. Further research is needed to explore the duration of protective effects, variations across sports, and its impact on patients with chronic ankle instability, contributing to a more comprehensive understanding of ankle taping's influence on lower extremity biomechanics., Competing Interests: Declaration of interest statement The authors state that they have no competing interests., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Electroencephalography (EEG) and electrocorticography (ECoG) recordings have been used to decode finger movements by analyzing brain activity. Traditional methods focused on single bandpass power changes for movement decoding, utilizing machine learning models requiring manual feature extraction., New Method: This study introduces a 3D convolutional neural network (3D-CNN) model to decode finger movements using ECoG data. The model employs adaptive, explainable AI (xAI) techniques to interpret the physiological relevance of brain signals. ECoG signals from epilepsy patients during awake craniotomy were processed to extract power spectral density across multiple frequency bands. These data formed a 3D matrix used to train the 3D-CNN to predict finger trajectories., Results: The 3D-CNN model showed significant accuracy in predicting finger movements, with root-mean-square error (RMSE) values of 0.26-0.38 for single finger movements and 0.20-0.24 for combined movements. Explainable AI techniques, Grad-CAM and SHAP, identified the high gamma (HG) band as crucial for movement prediction, showing specific cortical regions involved in different finger movements. These findings highlighted the physiological significance of the HG band in motor control., Comparison With Existing Methods: The 3D-CNN model outperformed traditional machine learning approaches by effectively capturing spatial and temporal patterns in ECoG data. The use of xAI techniques provided clearer insights into the model's decision-making process, unlike the "black box" nature of standard deep learning models., Conclusions: The proposed 3D-CNN model, combined with xAI methods, enhances the decoding accuracy of finger movements from ECoG data. This approach offers a more efficient and interpretable solution for brain-computer interface (BCI) applications, emphasizing the HG band's role in motor control., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Redundant manipulators, as mechanical equipments imitating human arms, have been applied to various areas in recent years from the perspective of control. Different from pure control technologies, the motion capability of a human arm is achieved by a complex and efficient neural system, with the cerebellum playing a pivotal role. Motivated by this fact, we design a cerebellum model based on an echo state network (ESN) for the learning and control of redundant manipulators. In addition, to simulate the skillful control ability of the cerebellum over movements of human arms, the proposed model is constructed at the joint velocity level. Furthermore, to improve the accuracy and applicability, we propose an ESN-based Kalman-filter-incorporated and cerebellum-inspired (KFICI) scheme for the learning and control of redundant manipulators with Kalman filter incorporated. The proposed scheme enables a redundant manipulator to track the desired trajectory at the velocity level and tolerate noises. Finally, simulations and experiments based on a physical redundant manipulator are performed to verify the effectiveness of the proposed control scheme.

Background: There is limited knowledge about the possible long-term effects on jaw motor function after whiplash trauma., Objectives: The primary aim was to evaluate integrated jaw and head-neck movement amplitudes during jaw function in individuals 2 years after whiplash trauma, compared to controls. The secondary aim was to evaluate changes between the acute stage and a 2-year follow-up in terms of jaw and head-neck movement amplitudes during jaw function., Methods: This study included 28 cases exposed to a whiplash trauma 2 years earlier (13 women) and 28 controls (13 women) without previous neck trauma. Head and jaw movement amplitudes were recorded during maximal jaw opening-closing movements using an optoelectronic 3D recording system. For a subpopulation of 12 cases and 15 controls, recordings had also been performed in the acute stage after the whiplash trauma. Jaw and head movement amplitudes were analysed using linear regression with group and sex as independent variables. The subpopulation longitudinal analysis was adjusted for movement amplitudes at baseline., Results: Jaw movement amplitudes were significantly associated with group (coefficient: -0.359: 95% CI: -10.70 to -1.93, p = .006) with smaller amplitudes of jaw movements for whiplash cases. Head movement amplitudes were not associated with group (coefficient: -0.051, 95% CI: -4.81 to 3.20, p = .687). In the longitudinal analysis, both jaw and head movement amplitudes showed significant associations between baseline and the 2-year follow-up., Conclusion: The present findings indicate that the effects on jaw function in terms of jaw opening capacity in the acute stage after whiplash trauma do not spontaneously recover., (© 2024 The Author(s). Journal of Oral Rehabilitation published by John Wiley & Sons Ltd.)

Hand motion detection is particularly important for managing the movement of individuals who have limbs amputated. The existing algorithm is complex, time-consuming and difficult to achieve better accuracy. A DNN is suggested to recognize human hand movements in order to get over these problems.Initially, the raw input EMG signal is captured then the signal is pre-processed using high-pass Butterworth filter and low-pass filter which is utilized to eliminate the noise present in the signal. After that pre-processed EMG signal is segmented using sliding window which is used for solving the issue of overlapping. Then the features are extracted from the segmented signal using Fast Fourier Transform. Then selected the appropriate and optimal number of features from the feature subset using coot optimization algorithm. After that selected features are given as input for deep neural network classifier for recognizing the hand movements of human. The simulation analysis shows that the proposed method obtain 95% accuracy, 0.05% error, precision is 94%, and specificity is 92%.The simulation analysis shows that the developed approach attain better performance compared to other existing approaches. This prediction model helps in controlling the movement of amputee patients suffering from disable hand motion and improve their living standard.

Isokinetic knee tests mostly evaluate reciprocal concentric-concentric flexor-extensor movements in a seated position. Discrete tests generate higher moments, but time requirements impede their widespread implementation. This study examined if hip angle (flexed vs. extended) and test modality (discrete vs. reciprocal) affect camera-based data (100 fps). Sixteen healthy males performed concentric (con) and eccentric (ecc) isokinetic knee flexor (H) and extensor (Q) movements (60°/s). Peak moments and contractional work of discrete and reciprocal tests (QconQecc, HconHecc) strongly correlated for extended (Q:91%≥R 2 ≥71%; H:95%≥R 2 ≥87%) and flexed hip (Q:88%≥R 2 ≥70%; H:81%≥R 2 ≥75%) without significant differences ( p >0.05) between test modalities. Discrete and "traditional" seated QconHcon-tests revealed substantially lower correlations for extended (Q:44%≥R 2 ≥43%; H:55%≥R 2 ≥54%) and flexed hip (Q:81%≥R 2 ≥77%; H:48%≥R 2 ≥47%). Although most mean values did not significantly differ, moderate correlations were predominant and the respective limits of agreement demonstrated considerable effects of hip angle and test modality. These insights assist practitioners in interpreting isokinetic data of different test procedures. If time constraints prevent discrete knee tests (gold standard), concentric-eccentric movements provide highly correlated outcomes, independent of the hip angle.

Flexible capacitive sensors have attracted the attention of researchers owing to their simple structure, ease of realization, and wearability. Currently, flexible capacitive sensors mainly have three-dimensional and two-dimensional structures, which are subject to several limitations in their applications. A low-cost, high-efficiency, and continuously processable process was used to wrap nylon DTY (PA) filaments on the surface of silver-coated nylon (SCN) core yarns and impregnate them with waterborne polyurethane (WPU) to obtain SCN/PA/WPU composite yarns, which were then utilized in the design of SCN/PA/WPU for the preparation of one-dimensionally structured flexible capacitive sensors. The morphology and mechanical properties of the SCN core yarn, SCN/PA wrapped yarn, and SCN/PA/WPU composite yarn were characterized. The strain-sensing performance of the sensor was analyzed, and the sensor was used to monitor human physiological activities. The sensor exhibited excellent strain capacitance sensing performance with a strain range of up to 140%. With a gauge factor of 0.66 at 10% tensile strain, it can detect strains as low as 1% and has good repeatability, withstanding more than 3200 tensile-unload cycles at 80% strain. The one-dimensional structure sensor can be used to monitor the large-scale movements of joints and muscles in various parts of the human body and the physiological signals of tiny human movements, such as breathing, coughing, and facial expressions, which have potential applications in the fields of sports monitoring and smart wearable.

Objective. Cortical beta (13-30 Hz) and gamma (30-60 Hz) oscillations are prominent in the motor cortex and are known to be transmitted to the muscles despite their limited direct impact on force modulation. However, we currently lack fundamental knowledge about the saliency of these oscillations at spinal level. Here, we developed an experimental approach to examine the modulations in high-frequency inputs to motoneurons under different motor states while maintaining a stable force, thus constraining behaviour. Approach. Specifically, we acquired brain and muscle activity during a 'GO'/'NO-GO' task. In this experiment, the effector muscle for the task (tibialis anterior) was kept tonically active during the trials, while participants ( N = 12) reacted to sequences of auditory stimuli by either keeping the contraction unaltered ('NO-GO' trials), or by quickly performing a ballistic contraction ('GO' trials). Motor unit (MU) firing activity was extracted from high-density surface and intramuscular electromyographic signals, and the changes in its spectral contents in the 'NO-GO' trials were analysed. Main results. We observed an increase in beta and low-gamma (30-45 Hz) activity after the 'NO-GO' cue in the MU population activity. These results were in line with the brain activity changes measured with electroencephalography. These increases in power occur without relevant alterations in force, as behaviour was restricted to a stable force contraction. Significance. We show that modulations in motor cortical beta and gamma rhythms are also present in muscles when subjects cancel a prepared ballistic action while holding a stable contraction in a 'GO'/'NO-GO' task. This occurs while force levels produced by the task effector muscle remain largely unaltered. Our results suggest that muscle recordings are informative also about motor states that are not force-control signals. This opens up new potential use cases of peripheral neural interfaces., (Creative Commons Attribution license.)

Aesthetic appreciation of full-body movements is likely shaped by our cumulative bodily experiences, yet most of the extant literature in this domain has focused on expertise and familiarity. We ran two experiments exploring individual differences in embodied experience and experience with the arts: In Study 1, we explored how participants' (n = 41) abilities to learn a choreography shaped their aesthetic perceptions while viewing learned vs. unknown movements, using functional near-infrared spectroscopy (fNIRS) to measure cortical activation over the Action Observation Network (i.e., inferior frontal gyrus [IFG], inferior parietal lobule, middle temporal gyrus [MTG]). Study 1 demonstrated that embodied experience enhanced ratings of enjoyment, familiarity, and reproducibility of movements, and that individual differences in participants' performance of the learned choreography were not associated with aesthetic ratings, but rather cortical activation in IFG and right MTG while viewing learned choreography. In Study 2, we combined the behavioural data from Study 1 with data from additional participants (total n = 141) to examine the relationship between arts experience and aesthetic perceptions of movements robustly. Study 2 revealed that previous arts and sports experience correlated with aesthetic judgements of familiarity and reproducibility of movements. Our findings highlight the relevance of examining individual experiences to fill theoretical gaps in our understanding of action aesthetics., (© 2024. The Author(s).)

This study aimed to explore the differences in joint kinematic characteristics and stroke effect between fast and slow strokes of table tennis players. Thirty-four table tennis players were randomly selected as participants for this experiment. A high-speed infrared motion capture system was used to collect kinematic data of the right-side upper and lower limb joints during strokes. Simultaneously, a high-speed camera was used to measure the stroke effect. According to the duration of a stroke, the stroke data were classified into two types: fast-stroke and slow-stroke using a two-step clustering algorithm. The duration of the three phases of fast-stroke was shorter, with faster ball speed and stronger spin. Compared with slow-stroke, fast-stroke exhibited shorter displacements in the three lower limb joints and faster linear velocities in the three upper limb joints. In addition, the motion angles of the knee and ankle joints were smaller, while the angles of the hip, shoulder, and elbow joints were larger, with higher angular velocities. Increasing the extension speed of the lower limbs, the flexion speed of the elbow joints, and the wrist movement speed can achieve fast strokes, enhancing ball speed and spin. Small and quick hip joint movement can effectively transfer energy to the upper limbs, increasing the movement speed of the elbow and wrist joints, thus improving the ball speed and spin of the stroke., (© 2024. The Author(s).)

Kinematic analysis is a central component of movement biomechanics, describing the relative motion of joint segments during different activities, in different subject cohorts, and at different timepoints. Establishing whether two sets of kinematic signals represent fundamentally similar or different underlying motion patterns is especially challenging, given 1) the lack of consensus around reference frame and joint axis definition, and 2) the substantial effect that minimal variations in frame position and orientation are known to have on signal magnitude and characteristics. As such, enormous variability in the reporting of tibiofemoral kinematics has resulted in joint movement patterns that remain controversially discussed. Previously, we demonstrated the ability of the REference FRame Alignment MEthod (REFRAME) to reorientate and reposition differently aligned local segment frames to achieve convergence in signals representing the same underlying motion, thereby offering a novel approach to consistently report joint motion. In this study, for the first time, we apply REFRAME to assess the rotational and translational in vivo tibiofemoral motion of ten healthy subjects during stair descent based on kinematic signals collected using a moving videofluoroscope. Kinematics were analysed before and after different REFRAME implementations, revealing generally neutral ab/adduction behaviour, accompanied by varying degrees of a sinusoidal int/external tibial rotation pattern over the activity cycle. Our data demonstrate that different selected implementations of REFRAME are able to highlight different characteristics of the motion patterns: Minimisation of the translational root-mean-square revealed proximodistal translation patterns with overall neutral progression, while anteroposterior translation showed seemingly different levels of correlation with flexion/extension in different subjects. On the other hand, REFRAME minimisation of translational variances exposed differences in the relative mean displacement between the femoral and tibial origins between subjects, highlighting differences in mean centre of rotation positions. This early application of REFRAME for providing an understanding of tibiofemoral kinematics demonstrates the potential of this novel approach to bring clarity to an otherwise complex representation of highly variable time-series signals, while highlighting the philosophical challenges of clinically interpretating kinematic signals in the first place., (© 2024. The Author(s).)

Contrary to expert readers, children learning to read have limited ability to preprocess letters in parafoveal vision. Parafoveal letters induce crowding cost: the features of neighboring letters interfere with target letter identification. We longitudinally studied the weight of parafoveal cost and benefit in two group of children (N = 42), during their first school year (Group 1) and at the end of second school year (Groupe 2). Using a novel digit-tracking method, a blurred text was presented and rendered unblurred by touching the screen, allowing the user to discover a window of visible text as the finger moved along it. We compared two conditions: (1) a large window, where crowding was enhanced by the presence of parafoveal information; (2) a small window, where crowding was suppressed by blurred parafoveal information. Finger kinematics were simultaneously recorded. We found that at the beginning of first-grade, digital fixations - brief slowing or stopping of the finger on a specific point - are significantly longer in the large compared to the small window condition, as parafoveal crowding increases text processing difficulty. This effect diminishes and disappears at the end of second-grade as reading performance improves. In the large window condition, longer digital saccades - rapid movements of the finger changing position - appear by the end of first grade suggesting that parafoveal exposure become more beneficial than harmful when children acquire basic reading skills. Our results show that in beginning readers, crowding has a cognitive cost that interfere with the speed of the learning reading process. Our findings are relevant to the field of education by showing that visual crowding in first grade should not be underestimated., (© 2024. The Author(s).)

Purpose: Tongue anatomy and function is widely described as consisting of four extrinsic muscles to control position and four intrinsic muscles to control shape. This myoarchitecture cannot, however, explain independent tongue body and blade movement nor accurately model the subtlety of observed lingual shapes. This study presents the case for a finer neuromuscular structure and functional description., Method: Using the theoretical framework of the partitioning hypothesis, evidence for neuromuscular compartments of each of the lingual muscles was discerned by reviewing studies of lingual anatomy, hypoglossal nerve staining, hypoglossal motoneuron axon tracing, muscle fiber type distribution, and electromyography. Muscle fibers of the visible human female were manually traced to produce a three-dimensional atlas of muscular compartments. A kinematic study was undertaken to determine the degree of independent movement between different parts of the tongue. A simple biomechanical model was used to demonstrate how synergistic groups of compartments can control sectors of the tongue., Results: Results indicated as many as 10 compartments of genioglossus, two each of superior and inferior longitudinal, eight of styloglossus, three of hyoglossus, and six each of transversus and verticalis, while palatoglossus may not have a significant role in tongue function. Kinematic analysis indicated independent control of five sectors of the tongue body, and biomechanical modeling demonstrated how this control may be achieved., Conclusion: Evidence is presented for a lingual structure based on neuromuscular compartments, which work together to position and shape sectors of the tongue and independently control tongue body and blade.

Purpose: This study aimed to investigate the effect of stimulus signal length on tongue and lip motion pattern stability in speakers diagnosed with amyotrophic lateral sclerosis (ALS) compared to healthy controls., Method: Electromagnetic articulography was used to derive articulatory motion patterns from individuals with mild ( n = 27) and severe ( n = 16) ALS and healthy controls ( n = 25). The spatiotemporal index (STI) was used as a measure of articulatory stability. Two experiments were conducted to evaluate signal length effects on the STI: (a) the effect of the number of syllables on STI values and (b) increasing lengths of subcomponents of a single phrase. Two-way mixed analyses of variance were conducted to assess the effects of syllable length and group on the STI for the tongue tip (TT), tongue back (TB), and lower lip (LL)., Results: Experiment 1 showed a significant main effect of syllable length (TT, p < .001; TB, p < .001; and LL, p < .001) and group (TT, p = .037; TB, p = .007; and LL, p = .017). TB and LL stability was generally higher with speech stimuli that included a greater number of syllables. Articulatory variability was significantly higher in speakers diagnosed with ALS compared to healthy controls. Experiment 2 showed a significant main effect of length (TT, p < .001; TB, p = .015; and LL, p < .001), providing additional support that STI values tend to be greater when calculated on longer speech signals., Conclusions: Articulatory stability is influenced by the length of speech signals and manifests similarly in both healthy speakers and persons with ALS. TT stability may be significantly impacted by phonemic content due to greater movement flexibility. Compared to healthy controls, there was an increase in articulatory variability in those with ALS, which likely reflects deviations in speech motor control., Supplemental Material: https://doi.org/10.23641/asha.24463924.

Purpose: This study investigated whether temporal coupling was present between lower limb motion rate and different speech tempi during different exercise intensities. We hypothesized that increased physical workload would increase cycling rate and that this could account for previous findings of increased speech tempo during exercise. We also investigated whether the choice of speech task (read vs. spontaneous speech) affected results., Method: Forty-eight women who were ages 18-35 years participated. A within-participant design was used with fixed-order physical workload and counterbalanced speech task conditions. Motion capture and acoustic data were collected during exercise and at rest. Speech tempo was assessed using the amplitude envelope and two derived intrinsic mode functions that approximated syllable-like and footlike oscillations in the speech signal. Analyses were conducted with linear mixed-effects models., Results: No direct entrainment between leg cycling rate and speech rate was observed. Leg cycling rate significantly increased from low to moderate workload for both speech tasks. All measures of speech tempo decreased when participants changed from rest to either low or moderate workload., Conclusions: Speech tempo does not show temporal coupling with the rate of self-generated leg motion at group level, which highlights the need to investigate potential faster scale momentary coupling. The unexpected finding that speech tempo decreases with increased physical workload may be explained by multiple mental and physical factors that are more diverse and individual than anticipated. The implication for real-world contexts is that even light physical activity-functionally equivalent to walking-may impact speech tempo.

Motility coupled to responsive behavior is essential for many microorganisms to seek and establish appropriate habitats. One of the simplest possible responses, reversing the direction of motion, is believed to enable filamentous cyanobacteria to form stable aggregates or accumulate in suitable light conditions. Here, we demonstrate that filamentous morphology in combination with responding to light gradients by reversals has consequences far beyond simple accumulation: Entangled aggregates form at the boundaries of illuminated regions, harnessing the boundary to establish local order. We explore how the light pattern, in particular its boundary curvature, impacts aggregation. A minimal mechanistic model of active flexible filaments resembles the experimental findings, thereby revealing the emergent and generic character of these structures. This phenomenon may enable elongated microorganisms to generate adaptive colony architectures in limited habitats or guide the assembly of biomimetic fibrous materials., (© 2024. The Author(s).)

Incentives tend to drive improvements in performance. But when incentives get too high, we can "choke under pressure" and underperform right when it matters most. What neural processes might lead to choking under pressure? We studied rhesus monkeys performing a challenging reaching task in which they underperformed when an unusually large "jackpot" reward was at stake, and we sought a neural mechanism that might result in that underperformance. We found that increases in reward drive neural activity during movement preparation into, and then past, a zone of optimal performance. We conclude that neural signals of reward and motor preparation interact in the motor cortex (MC) in a manner that can explain why we choke under pressure., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024. Published by Elsevier Inc.)

Striatum and its predominant input, motor cortex, are responsible for the selection and performance of purposive movement, but how their interaction guides these processes is not understood. To establish its neural and behavioral contributions, we bilaterally lesioned motor cortex and recorded striatal activity and reaching performance daily, capturing the lesion's direct ramifications within hours of the intervention. We observed reaching impairment and an absence of striatal motoric activity following lesion of motor cortex, but not parietal cortex control lesions. Although some aspects of performance began to recover after 8-10 days, striatal projection and interneuronal dynamics did not-eventually entering a non-motor encoding state that aligned with persisting kinematic control deficits. Lesioned mice also exhibited a profound inability to switch motor plans while locomoting, reminiscent of clinical freezing of gait (FOG). Our results demonstrate the necessity of motor cortex in generating trained and untrained actions as well as striatal motoric dynamics., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background: Following a stroke, brain activation reorganisation, movement compensatory strategies, motor performance and their evolution through rehabilitation are matters of importance for clinicians. Two non-invasive neuroimaging methods allow for recording task-related brain activation: functional near-infrared spectroscopy (fNIRS) and electroencephalography (fEEG), respectively based on hemodynamic response and neuronal electrical activity. Their simultaneous measurement during movements could allow a better spatiotemporal mapping of brain activation, and when associated to kinematic parameters could unveil underlying mechanisms of functional upper limb (UL) recovery. This study aims to depict the motor cortical activity patterns using combined fNIRS-fEEG and their relationship to motor performance and strategies during UL functional tasks in chronic post-stroke patients., Methods: Twenty-one healthy old adults and 21 chronic post-stroke patients were recruited and completed two standardised functional tasks of the UL: a paced-reaching task where they had to reach a target in front of them and a circular steering task where they had to displace a target using a hand-held stylus, as fast as possible inside a circular track projected on a computer screen. The activity of the bilateral motor cortices and motor performance were recorded simultaneously utilizing a fNIRS-fEEG and kinematics platform., Results and Conclusions: Kinematic analysis revealed that post-stroke patients performed worse in the circular steering task and used more trunk compensation in both tasks. Brain analysis of bilateral motor cortices revealed that stroke individuals over-activated during the paretic UL reaching task, which was associated with more trunk usage and a higher level of impairment (clinical scores). This work opens up avenues for using such combined methods to better track and understand brain-movement evolution through stroke rehabilitation., (© 2024. The Author(s).)

A growing body of literature has found that synchronising movements with a group subsequently increases self-other blurring and social closeness with synchronised partners. However, movement synchrony has not been studied in online settings. Our study has a primarily methodological focus to investigate whether synchronous movement leads to changes in self-other blurring and proxemics in an online, desktop-mediated environment. We conducted two experiments to manipulate synchrony with a group of virtual agents and investigate its impact on self-other blurring and comfort distance judgments. In Experiment 1, we compared synchronous movement to a no-movement condition; in Experiment 2, we introduced an unpredictable movement condition. In both experiments, we found that our manipulation of synchronous movement between participants and a virtual group of agents led to an increase in explicit self-other blurring compared to the no and unpredictable movement conditions; however, we did not find reliable effects on comfort distance judgments., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Biswas, Brass. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Objective . Motor-related neural activity is more widespread than previously thought, as pervasive brain-wide neural correlates of motor behavior have been reported in various animal species. Brain-wide movement-related neural activity have been observed in individual brain areas in humans as well, but it is unknown to what extent global patterns exist. Approach. Here, we use a decoding approach to capture and characterize brain-wide neural correlates of movement. We recorded invasive electrophysiological data from stereotactic electroencephalographic electrodes implanted in eight epilepsy patients who performed both an executed and imagined grasping task. Combined, these electrodes cover the whole brain, including deeper structures such as the hippocampus, insula and basal ganglia. We extract a low-dimensional representation and classify movement from rest trials using a Riemannian decoder. Main results . We reveal global neural dynamics that are predictive across tasks and participants. Using an ablation analysis, we demonstrate that these dynamics remain remarkably stable under loss of information. Similarly, the dynamics remain stable across participants, as we were able to predict movement across participants using transfer learning. Significance . Our results show that decodable global motor-related neural dynamics exist within a low-dimensional space. The dynamics are predictive of movement, nearly brain-wide and present in all our participants. The results broaden the scope to brain-wide investigations, and may allow combining datasets of multiple participants with varying electrode locations or calibrationless neural decoder., (Creative Commons Attribution license.)

To validate active human body models for investigating occupant safety in autonomous cars, it is crucial to comprehend the responses of vehicle occupants during evasive maneuvers. This study sought to quantify the behavior of midsize male and small female passenger seat occupants in both upright and reclined postures during three types of vehicle maneuvers. Volunteer tests were conducted using a minivan, where vehicle kinematics were measured with a DGPS sensor and occupant kinematics were captured with a stereo-vision motion capture system. Seatbelt loads, belt pull-out, and footrest reaction forces were also documented. The interior of the vehicle was 3D-scanned for modeling purposes. Results indicated that seatback angles significantly affected occupant kinematics, with small female volunteers displaying reduced head and torso movements, except during emergency braking with a upright posture seatback. Lane-change maneuvers revealed that maximum lateral head excursions varied depending on the maneuver's direction. The study concluded that seatback angles were crucial in determining the extent of occupant movement, with notable variations in head and torso excursions observed. The collected data assist in understanding occupant behavior during evasive maneuvers and contribute to the validation of human body models, offering essential insights for enhancing safety systems in autonomous vehicles.

The control of hand movement during sailing is important for performance. To quantify the amount of regularity and the unpredictability of hand fluctuations during the task, the mathematical algorithm Approximate Entropy (ApEn) of the hand acceleration can be used. Approximate Entropy is a mathematical algorithm that depends on the combination of two input parameters including (1) the length of the sequences to be compared (m), and (2) the tolerance threshold for accepting similar patterns between two segments (r). The aim of this study is to identify the proper combinations of 'm' and 'r' parameter values for ApEn measurement in the hand movement acceleration data during sailing. Inertial Measurement Units (IMUs) recorded acceleration data for both the mainsail (non-dominant) and tiller (dominant) hands across the X-, Y-, and Z-axes, as well as vector magnitude. ApEn values were computed for 24 parameter combinations, with 'm' ranging from 2 to 5 and 'r' from 0.10 to 0.50. The analysis revealed significant differences in acceleration ApEn regularity between the two hands, particularly along the Z-axis, where the mainsail hand exhibited higher entropy values ( p = 0.000673), indicating greater acceleration complexity and unpredictability. In contrast, the tiller hand displayed more stable and predictable acceleration patterns, with lower ApEn values. ANOVA results confirmed that parameter 'm' had a significant effect on acceleration complexity for both hands, highlighting differing motor control demands between the mainsail and tiller hands. These findings demonstrate the utility of IMU sensors and ApEn in detecting nuanced variations in acceleration dynamics during sailing tasks. This research contributes to the understanding of hand-specific acceleration patterns in sailing and provides a foundation for further studies on adaptive sailing techniques and motor control strategies for both novice and expert sailors.

Background: ActiMotus, a thigh-accelerometer-based software used for the classification of postures and movements (PaMs), has shown high accuracy among adults and school-aged children; however, its accuracy among younger children and potential differences between sexes are unknown. This study aimed to evaluate the accuracy of ActiMotus to measure PaMs among children between 3 and 14 years and to assess if this was influenced by the sex or age of children., Method: Forty-eight children attended a structured ~1-hour data collection session at a laboratory. Thigh acceleration was measured using a SENS accelerometer, which was classified into nine PaMs using the ActiMotus software. Human-coded video recordings of the session provided the ground truth., Results: Based on both F1 scores and balanced accuracy, the highest levels of accuracy were found for lying, sitting, and standing (63.2-88.2%). For walking and running, accuracy measures ranged from 48.0 to 85.8%. The lowest accuracy was observed for classifying stair climbing. We found a higher accuracy for stair climbing among girls compared to boys and for older compared to younger age groups for walking, running, and stair climbing., Conclusions: ActiMotus could accurately detect lying, sitting, and standing among children. The software could be improved for classifying walking, running, and stair climbing, particularly among younger children.

Objective: To evaluate knee biomechanics of patients about 12 months after anterior cruciate ligament (ACL) reconstruction during cutting and determine the abnormal biomechanical characteristics., Methods: Sixteen males about 12 months after ACL reconstruction were recruited for this study. Three-dimensional kinematic and kinetic data were collected during cutting movement. Knee joint angles and moments were calculated. Paired t -tests were used to compare the differences in knee biomechanics between the surgical leg and nonsurgical leg., Results: The peak posterior ground reaction force (surgical leg: 0.380±0.071; nonsurgical leg: 0.427±0.069, P = 0.003) and vertical ground reaction force (surgical leg: 1.996±0.202, nonsurgical leg: 2.110±0.182, P = 0.001) were significantly smaller in the surgical leg than in the nonsurgical leg. When compared with the uninjured leg, the surgical leg demonstrated a smaller knee flexion angle (surgical leg: 38.3°± 7.4°; nonsurgical leg: 42.8°± 7.9°, P < 0.001) and larger external rotation angle (surgical leg: 10.3°± 2.4°; nonsurgical leg: 7.7°± 2.1°, P = 0.008). The surgical leg also demonstrated a smaller peak knee extension moment (surgical leg: 0.092 ± 0.031; nonsurgical leg: 0.133 ± 0.024, P < 0.001) and peak knee external rotation moment (surgical leg: 0.005 ± 0.004; nonsurgical leg: 0.008 ± 0.004, P = 0.015) when compared with the nonsurgical leg., Conclusion: The individuals with ACL reconstruction mainly showed asymmetrical movements in the sagittal and horizontal planes. The surgical leg demonstrated a smaller peak knee flexion angle, knee extension moment, and knee external rotation moment, with greater knee external rotation angle.

Sports-related concussion (SRC) in adolescent athletes is associated with an increased risk of subsequent lower extremity injury. Neuromuscular training (NMT) has shown promise for reducing lower extremity injuries following SRC, however, neural adaptations in response to changes in lower extremity biomechanics following NMT in athletes with a history of SRC (HxSRC) remains poorly understood. Therefore, the purpose of this study was to identify changes in neural activity associated with lower extremity movement adaptations following a six-week NMT intervention in athletes with a HxSRC. Thirty-two right-hand/foot-dominant female adolescent athletes (16 with self-reported HxSRC, 16 age- and anthropometrically-matched controls) completed a bilateral leg press task with 3D motion analysis during functional magnetic resonance imaging (fMRI). Movement adaptations were defined as a change in frontal and sagittal plane range of motion (ROM) during the fMRI bilateral leg press task. Significant pre- to post-NMT reductions were observed in the non-dominant (left) mean frontal plane ROM. Whole-brain neural correlate analysis revealed that increased cerebellar activity was significantly associated with reduced mean left-knee frontal ROM for matched controls. Exploratory within group analyses identified neural correlates in the postcentral gyrus for the HxSRC group which was associated with reduced mean left-knee frontal plane ROM. These distinct longitudinal changes provide preliminary evidence of differential neural activity associated with NMT to support knee frontal plane control in athletes with and without a HxSRC., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Gregory D. Myer has consulted with Commercial entities to support application to the US Food and Drug Administration but has no financial interest in the commercialization of the products. Dr. Myer’s institution receives current and ongoing grant funding from National Institutes of Health/National Institute of Arthritis and Musculoskeletal and Skin Diseases Grants U01AR067997, R01 AR070474, R01AR055563, R01AR076153, R01 AR077248 and has received industry sponsored research funding related to brain injury prevention and assessment with Q30 Innovations, LLC, and ElMinda, Ltd. Dr. Myer receives author royalties from Human Kinetics and Wolters Kluwer. Dr. Myer is an inventor of biofeedback technologies (2017 Non-Provisional Patent Pending- Augmented and Virtual reality for Sport Performance and Injury Prevention Application filed 11/10/2016 (62/420,119), Software Copyrighted.) designed to enhance rehabilitation and prevent injuries and receives licensing royalties. Dr. Myer and Dr. Diekfuss receive inventor-related royalties resultant from biofeedback technologies (Include Health: LIC1907082014-0706). Dr. Grooms has current and ongoing funding support from the National Institutes of Health/National Center for Complementary and Integrative Health (R21 AT009339-02) and National Institutes of Health/National Institute of Arthritis and Musculoskeletal and Skin Diseases (R01AR076153, R01AR077248) and the US Department of Defense Congressionally Directed Medical Research Program Peer Reviewed Orthopaedic Research Program (OR170266), research award (81XWH-18-1-0707). Opinions, interpretations, conclusions, and recommendations are those of the author and are not necessarily endorsed by the Department of Defense. Dr. Diekfuss also receives author royalties from Kendall Hunt Publishing Company., (Copyright © 2024 International Brain Research Organization (IBRO). Published by Elsevier Inc. All rights reserved.)

Collective motion, such as milling, flocking, and collective turning, is a common and captivating phenomenon in nature, which arises in a group of many self-propelled individuals using local interaction mechanisms. Recently, vision-based mechanisms, which establish the relationship between visual inputs and motion decisions, have been applied to model and better understand the emergence of collective motion. However, previous studies often characterize the visual input as a transient Boolean-like sensory stream, which makes it challenging to capture the salient movements of neighbors. This further hinders the onset of the collective response in vision-based mechanisms and increases demands on visual sensing devices in robotic swarms. An explicit and context-related visual cue serving as the sensory input for decision-making in vision-based mechanisms is still lacking. Here, we hypothesize that body orientation change (BOC) is a significant visual cue characterizing the motion salience of neighbors, facilitating the emergence of the collective response. To test our hypothesis, we reveal the significant role of BOC during collective U-turn behaviors in fish schools by reconstructing scenes from the view of individual fish. We find that an individual with the larger BOC often takes on the leading role during U-turns. To further explore this empirical finding, we build a pairwise interaction mechanism on the basis of the BOC. Then, we conduct experiments of collective spin and collective turn with a real-time physics simulator to investigate the dynamics of information transfer in BOC-based interaction and further validate its effectiveness on 50 real miniature swarm robots. The experimental results show that BOC-based interaction not only facilitates the directional information transfer within the group but also leads to scale-free correlation within the swarm. Our study highlights the practicability of interaction governed by the neighbor's body orientation change in swarm robotics and the effect of scale-free correlation in enhancing collective response., (© 2024. The Author(s).)

The purpose of this paper is to introduce a method of measuring spatiotemporal gait patterns, tibial accelerations, and heart rate that are matched with high resolution geographical terrain features using publicly available data. These methods were demonstrated using data from 218 Marines, who completed loaded outdoor ruck hikes between 5-20 km over varying terrain. Each participant was instrumented with two inertial measurement units (IMUs) and a GPS watch. Custom code synchronized accelerometer and positional data without a priori sensor synchronization, calibrated orientation of the IMUs in the tibial reference frame, detected and separated only periods of walking or running, and computed acceleration and spatiotemporal outcomes. GPS positional data were georeferenced with geographic information system (GIS) maps to extract terrain features such as slope, altitude, and surface conditions. This paper reveals the ease at which similar data can be gathered among relatively large groups of people with minimal setup and automated data processing. The methods described here can be adapted to other populations and similar ground-based activities such as skiing or trail running.

Introduction: Stroke survivors often face motor dysfunction, increasing fall risk. Lower extremity muscle weakness is a key factor affecting walking ability. Tai chi (TC) has been shown to improve muscle strength and mobility in patients with stroke more effectively than traditional walking training. However, existing TC programmes for stroke rehabilitation are often too simplified and fail to fully use TC's benefits. Additionally, subjective assessment scales are time-consuming and prone to bias. This study proposes integrating TC's early movement features with neurodevelopmental therapy, using surface electromyography and inertial measurement unit (IMU) sensors to thoroughly analyse diverse TC movements. Tailored exercises, based on stroke-induced impairments, will be objectively assessed through biomechanical analysis., Methods and Analysis: The study unfolds in two phases. The initial phase employs the IMU sensor and electromyography to objectively analyse TC's biomechanics, informing personalised rehabilitation plans aligned with distinct movement impairments. The second phase adopts a randomised, single-blind, parallel controlled trial design involving 60 patients with stroke randomly assigned to either the intervention or control group. The intervention group undergoes biomechanics-based TC training alongside routine rehabilitation for 12 weeks, practicing the 24-form TC three times weekly. The control group engages in routine rehabilitation thrice weekly for the same duration. Primary and secondary outcomes, including kinematic/dynamic data, surface electromyography, motion analysis, comprehensive the international classification of functioning, disability and health Core Set for Stroke, Modified Barthel Index and Fugl-Meyer Assessment, will be evaluated at baseline and post-intervention., Ethics and Dissemination: The study has received approval from the Ethics Committee of Zhongda Hospital Southeast University (2023ZDSYLL378-P01). All prospective participants will receive comprehensive information regarding the study protocol, and their informed consent will be obtained before their participation. Additionally, the trial will be registered with the Chinese Clinical Trial Registry to ensure transparency and compliance with research regulations. Results from this study will be disseminated through peer-reviewed journals, conference presentations and public databases to ensure wide accessibility and to contribute to the advancement of medical knowledge., Protocol Version: 2.0 (14 June 2024)., Trial Registration Number: www.chictr.org.cn, identifier ChiCTR2400080158., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Mandibular movement is complex and individual due to variations in the temporomandibular joint (TMJ). Consequently, patient-centered dentistry should incorporate patients' specific anatomy and condylar function in treatment planning. Real-time magnetic resonance imaging (rt-MRI) visualizes relevant structures and tracks mandibular movement. However, current assessments rely on qualitative observations or time-consuming manual tracking, lacking reliability. This study developed an automatic tracking algorithm for mandibular movement in rt-MRI using least mean square registration (LMS) and compared it to manual tracking (MT) during mouth opening. Ten participants with skeletal class I underwent rt-MRI (10 frames/s). The same operator tracked the condylar pathway for the two methods, setting 2000 landmarks (2 landmarks x100 frames x10 participants) for MT and 210 landmarks (3 landmarks x7 frames x10 participants) for LMS. Time required, superimposition error, and the distance between tracked condylar pathways were compared between methods. LMS tracking was 76% faster and showed significantly better superimposition (0.0289 ± 0.0058) than MT (0.059 ± 0.0145) (p = 0.002). During one-third of the movement, the pathways tracked by both methods were more than 1 mm and 1° apart. These findings highlight the benefits of automatic condylar movement tracking in rt-MRI, laying the groundwork for more objective and quantitative observation of TMJ function., (© 2024. The Author(s).)

Understanding the athlete's movements and the restrictions incurred by protective equipment is crucial for improving the equipment and subsequently, the athlete's performance. The task of equipment improvement is especially challenging in sports including advanced manoeuvres such as ice hockey and requires a holistic approach guiding the researcher's attention toward the right variables. The purposes of this study were (a) to quantify the effects of protective equipment in ice hockey on player's performance and (b) to identify the restrictions incurred by it. Twenty male hockey players performed four different drills with and without protective equipment while their performance was quantified. A neural network accompanied by layer-wise relevance propagation was applied to the 3D kinematic data to identify variables and time points that were most relevant for the neural network to distinguish between the equipment and no equipment condition, and therefore presumable result from restrictions incurred by the protective equipment. The study indicated that wearing the protective equipment, significantly reduced performance. Further, using the 3D kinematics, an artificial neural network could accurately distinguish between the movements performed with and without the equipment. The variables contributing the most to distinguishing between the equipment conditions were related to the upper extremities and movements in the sagittal plane. The presented methodology consisting of artificial neural networks and layer-wise relevance propagation contributed to insights without prior knowledge of how and to which extent joint angles are affected in complex maneuvers in ice hockey in the presence of protective equipment. It was shown that changes to the equipment should support the flexion movements of the knee and hip and should allow players to keep their upper extremities closer to the torso., Competing Interests: This work was funded by CCM Hockey (Montreal, Canada) and Biomechanigg Sport and Health Research (BSHR; Calgary, Canada). CCM Hockey also funded subject recruitment and data collection. However, the results presented in this article do not in any way represent a bias toward CCM products over other brands. The principal investigator, Dr. Benno Nigg, is also the Chief Science Officer of the sponsoring company BSHR. BSHR covered material costs for this research and was simply interested in the outcome of the study, regardless of the findings. The company BSHR did not benefit from the results of the findings. BSHR had no influence on the outcome of this study. The results of the study were presented clearly, honestly, and without fabrication, falsification, or inappropriate data manipulation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. This does not alter our adherence to PLOS ONE policies on sharing data and materials., (Copyright: © 2024 Lennartz et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Beta band oscillations in the sensorimotor cortex and subcortical structures, such as the subthalamic nucleus (STN) and internal pallidum (GPi), are closely linked to motor control. Recent research suggests that low-beta (14.5-23.5 Hz) and high-beta (23.5-35 Hz) cortico-STN coherence arise through distinct networks, possibly reflecting indirect and hyperdirect pathways. In this study, we sought to probe whether low- and high-beta coherence also exhibit different functional roles in facilitating and inhibiting movement. Twenty patients with Parkinson's disease who had deep brain stimulation electrodes implanted in either STN or GPi performed a classical go/nogo task while undergoing simultaneous magnetoencephalography and local field potentials recordings. Subjects' expectations were manipulated by presenting go- and nogo-trials with varying probabilities. We identified a lateral source in the sensorimotor cortex for low-beta coherence, as well as a medial source near the supplementary motor area for high-beta coherence. Task-related coherence time courses for these two sources revealed that low-beta coherence was more strongly implicated than high-beta coherence in the performance of go-trials. Accordingly, average pre-stimulus low-beta but not high-beta coherence or spectral power correlated with overall reaction time across subjects. High-beta coherence during unexpected nogo-trials was higher compared to expected nogo-trials at a relatively long latency of 3 s after stimulus presentation. Neither low- nor high-beta coherence showed a significant correlation with patients' symptom severity at baseline assessment. While low-beta cortico-subcortical coherence appears to be related to motor output, the role of high-beta coherence requires further investigation., Competing Interests: Declaration of competing interest We declare that we have no competing financial interests or personal relationships that could have appeared to influence the work reported in our manuscript ‘Low-beta versus high-beta band cortico-subcortical coherence in movement inhibition and expectation’., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

As a cutting-edge technology of connecting biological brain and external devices, brain-computer interface (BCI) exhibits promising applications on extensive fields such as medical and military. As for the disable individuals with four limbs losing the motor functions, it is a potential treatment way to drive mechanical equipments by the means of non-invasive BCI, which is badly depended on the accuracy of the decoded electroencephalogram (EEG) singles. In this study, an explanatory convolutional neural network namely EEGNet based on SimAM attention module was proposed to enhance the accuracy of decoding the EEG singles of index and thumb fingers for both left and right hand using sensory motor rhythm (SMR). An average classification accuracy of 72.91% the data of eight healthy subjects was obtained, which were captured from the one second before finger movement to two seconds after action. Furthermore, the character of event-related desynchronization (ERD) and event related synchronization (ERS) of index and thumb fingers was also studied in this study. These findings have significant importance for controlling external devices or other rehabilitation equipment using BCI in a fine way., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

This study aimed to validate the automated temporal analysis of countermovement vertical jump (CMJ) using MMPose, a markerless pose estimation framework, by comparing it with the gold-standard 3D marker-based motion capture system. Twelve participants performed five CMJ trials, which were simultaneously recorded using the marker-based system and two smartphone cameras capturing both sides of the body. Key kinematic points, including center of mass (CoM) and toe trajectories, were analyzed to determine jump phases and temporal variables. The agreement between methods was assessed using Bland-Altman analysis, root mean square error (RMSE), and Pearson's correlation coefficient (r), while consistency was evaluated via intraclass correlation coefficient (ICC 3,1) and two-way repeated-measures ANOVA. Cohen's effect size (d) quantified the practical significance of differences. Results showed strong agreement (r > 0.98) with minimal bias and narrow limits of agreement for most variables. The markerless system slightly overestimated jump height and CoM vertical velocity, but ICC values (ICC > 0.91) confirmed strong reliability. Cohen's d values were near zero, indicating trivial differences, and no variability due to recording side was observed. Overall, MMPose proved to be a reliable alternative for in-field CMJ analysis, supporting its broader application in sports and rehabilitation settings.

Neurodevelopment is a highly intricate process, and early detection of abnormalities is critical for optimizing outcomes through timely intervention. Accurate and cost-effective diagnostic methods for neurological disorders, particularly in infants, remain a significant challenge due to the heterogeneity of data and the variability in neurodevelopmental conditions. This study recruited twelve parent-infant pairs, with infants aged 3 to 12 months. Approximately 25 min of 2D video footage was captured, documenting natural play interactions between the infants and toys. We developed a novel, open-source method to classify and analyse infant movement patterns using deep learning techniques, specifically employing a transformer-based fusion model that integrates multiple video features within a unified deep neural network. This approach significantly outperforms traditional methods reliant on individual video features, achieving an accuracy of over 90%. Furthermore, a sensitivity analysis revealed that the pose estimation contributed far less to the model's output than the pre-trained transformer and convolutional neural network (CNN) components, providing key insights into the relative importance of different feature sets. By providing a more robust, accurate and low-cost analysis of movement patterns, our work aims to enhance the early detection and potential prediction of neurodevelopmental delays, whilst providing insight into the functioning of the transformer-based fusion models of diverse video features.

As social beings, we are adept at coordinating our body movements and gaze with others. Often, when coordinating with another person, we orient ourselves to face them, as mutual gaze provides valuable cues pertaining to attention and intentions. Moreover, movement synchrony and mutual gaze are associated with prosocial outcomes, yet the perceptual consequences of these forms of coordination remain poorly understood. Across two experiments, we assessed how movement synchrony and gaze direction influence observers' perceptions of dyads. Observers' behavioural responses indicated that dyads are perceived as more socially connected and are more enjoyable to watch when moving synchronously and facing each other. Neuroimaging results showed modulation of the Action Observation and Theory of Mind networks by movement synchrony and mutual gaze, with more robust brain activity when evaluating togetherness (i.e., active and intentional collaboration) than aesthetic value (i.e., enjoyment). A fuller understanding of the consequences of movement synchrony and mutual gaze from the observer's viewpoint holds important implications for social perception, in terms of how observers intuit social relationships within dyads, and the aesthetic value derived from watching individuals moving in these ways., (© 2024. The Author(s).)

Conventional approaches to enhance movement coordination, such as providing instructions and visual feedback, are often inadequate in complex motor tasks with multiple degrees of freedom (DoFs). To effectively address coordination deficits in such complex motor systems, it becomes imperative to develop interventions grounded in a model of human motor learning; however, modeling such learning processes is challenging due to the large DoFs. In this paper, we present a computational motor learning model that leverages the concept of motor synergies to extract low-dimensional learning representations in the high-dimensional motor space and the internal model theory of motor control to capture both fast and slow motor learning processes. We establish the model's convergence properties and validate it using data from a target capture game played by human participants. We study the influence of model parameters on several motor learning trade-offs such as speed-accuracy, exploration-exploitation, satisficing, and flexibility-performance, and show that the human motor learning system tunes these parameters to optimize learning and various output performance metrics., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Kamboj et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Inertial measurement units (IMUs) provide benefits over the traditional optoelectronic motion capture (OMC) systems in measuring kinematics for the low back pain population. The reliability and validity of IMUs to quantify three-dimensional motion for multiple hip/spine segments have not been systematically evaluated. The purpose of this study was to determine the repeated-measures reliability and concurrent validity of an IMU system for measuring the three-dimensional spine/hip kinematics in six common movement assessments. Seventeen participants (32.3 (14.7) years; 11 female) performed two trials each of six range-of-motion assessments while fitted with four IMUs (T1/T2, T12/L1, L5/S1, and femur). The IMUs showed good-excellent reliability for most of the movements in the primary plane and poor-moderate reliability in the non-primary planes. The IMU and OMC systems showed generally good-excellent agreement in the primary plane and RMSE values between 3.03° and 15.75°. The removal of outliers based on the Bland-Altman analysis resulted in RMSE values between 2.44° and 10.30°. The system agreement in the non-primary planes was generally poor-moderate, and the RMSE values ranged from 2.19° to 45.88°. Anomalies in the proprietary sensor fusion algorithm or calibration may have contributed to the large RMSE values, highlighting the importance of assessing data for physiological relevance. The results suggest that these IMUs may be best suited for population-based studies measuring movement in the primary plane and point toward the need for the development of more robust approaches for broader implementation.

Background: Understanding the relationship between the functional state of the musculoskeletal system and skating performance in ice hockey players is essential, as it can provide valuable insights for the development of training programs tailored to the specific needs of athletes. This study investigated the relationship between functional movement patterns, dynamic balance, and ice speed and agility in young elite male ice hockey players., Methods: The study involved sixty elite male ice hockey players aged 14 to 18 years, with an average age of 15.9 ± 0.85 years and training experience ranging from 7 to 9 years. Functional movement patterns were evaluated using the Functional Movement Screen ™ (FMS TM ). Dynamic balance was assessed using the lower quarter Y-Balance test (YBT-LQ). Fitness tests on ice were conducted using a professional Smart Speed measurement system., Results: Negative correlations were found between the in-line lunge and the results of the 5-m forward (rho = -0.31, p = 0.018) and 5-m backward (rho = -0.27, p = 0.040), as well as between the hurdle step and the 30-m forward skating test result (rho = -0.26, p = 0.043). Positive correlations were observed between shoulder mobility and both forward (5-m: rho = 0.27, p = 0.035) and backward skating results (5-m: rho = 0.35, p = 0.006; 30-m: rho = 0.26, p = 0.047), and between active straight leg rise and both the 5-m forward skating (rho = 0.38, p = 0.002) and agility tests (rho = 0.39, p = 0.002). The study also revealed positive correlations between the magnitude of asymmetries in the anterior reach distance of the right and left legs and the results of 5-m forward (rho = 0.34, p = 0.009) and backward skating (rho = 0.32, p = 0.013). Additionally, a positive correlation was found between the agility test and the magnitude of asymmetries in the posteromedial reach distance (r = 0.32, p = 0.012) as well as the composite YBT score (r = 0.28, p = 0.031). Negative correlations were found between normalized reach distances in the YBT-LQ and performance outcomes in both forward and backward skating, as well as in the agility test, indicating that greater reach distance corresponds to faster skating., Conclusions: These findings suggest the potential impact of balance and hip mobility on skating speed and agility and emphasize the importance of symmetry for optimal performance among ice hockey players., Competing Interests: The authors declare that they have no competing interests., (© 2024 Grabara and Bieniec.)

Objective. The accurate temporal analysis of muscle activations is of great importance in several research areas spanning from the assessment of altered muscle activation patterns in orthopaedic and neurological patients to the monitoring of their motor rehabilitation. Several studies have highlighted the challenge of understanding and interpreting muscle activation patterns due to the high cycle-by-cycle variability of the sEMG data. This makes it difficult to interpret results and to use sEMG signals in clinical practice. To overcome this limitation, this study aims at presenting a toolbox to help scientists easily characterize and assess muscle activation patterns during cyclical movements. Approach. CIMAP(Clustering for the Identification of Muscle Activation Patterns) is an open-source Python toolbox based on agglomerative hierarchical clustering that aims at characterizing muscle activation patterns during cyclical movements by grouping movement cycles showing similar muscle activity. Main results. From muscle activation intervals to the graphical representation of the agglomerative hierarchical clustering dendrograms, the proposed toolbox offers a complete analysis framework for enabling the assessment of muscle activation patterns. The toolbox can be flexibly modified to comply with the necessities of the scientist.CIMAPis addressed to scientists of any programming skill level working in different research areas such as biomedical engineering, robotics, sports, clinics, biomechanics, and neuroscience. CIMAP is freely available on GitHub (https://github.com/Biolab-PoliTO/CIMAP). Significance. CIMAPtoolbox offers scientists a standardized method for analyzing muscle activation patterns during cyclical movements., (Creative Commons Attribution license.)