Muscle Movement Research Articles

A highly parallel algorithm for simulating the elastodynamics of a patient-specific human heart with four chambers using a heterogeneous hyperelastic model

In this paper a highly parallel method is developed for simulating the elastodynamics of a four-chamber human heart with patient-specific geometry. The heterogeneous hyperelastic model is discretized by a finite element method in space and a fully implicit adaptive method in time, and the resulting nonlinear algebraic systems are solved by a scalable domain decomposition algorithm. The deformations of the cardiac muscles are quite complex due to the realistic geometry, the heterogeneous hyperelasticity of the cardiac tissue, and the myocardial fibers with active stresses. Moreover, the deformations in different chambers and at different phases of the cardiac cycle are very different. To simulate all the muscle movements including the atrial diastole, the atrial systole, the isovolumic contraction, the ventricular ejection, the isovolumic relaxation, and the ventricular filling, the temporal-spatial mesh needs to be sufficiently fine, but not too fine so that the overall computing time is manageable, we introduce a baseline mesh in space and a two-level time stepping strategy including a uniform baseline time step size to obtain the desired time accuracy and an adaptive time stepping method within a baseline time step to guarantee the convergence of the nonlinear solver. Through numerical experiments, we investigate the performance of the proposed method with respect to the material coefficients, the fiber orientations, as well as the mesh sizes and the time step sizes. For an unstructured tetrahedral mesh with more than 200 million degree of freedoms, the method scales well for up to 16,384 processor cores for all steps of an entire cardiac cycle.

An on-skin triboelectric sensor system enabled by heterogeneous parallel channel fusion model for human-machine interactions

The highly flexible wearable device for human-machine interaction is a burgeoning technology that has garnered considerable attention among researchers. However, current wearable devices such as data gloves, wrist bands and exoskeleton devices require additional fixation aids, which interfere with the users’ movements and cause discomfort. Here, a flexible on-skin triboelectric sensor is developed for high-precision human-machine interaction, which is in the form of a thin film containing a soft substrate and two triboelectric layers with mismatched elastic modulus. The on-skin triboelectric sensors can be mounted on the forearm epidermis by their own adhesion, which is rarely perceptible and does not impede hand and wrist mobility. On the basis, the sensors can accurately measure the tiny deformations caused by muscle movement. Meanwhile, a heterogeneous parallel channel fusion (HPCF) model is proposed for advanced signal processing and recognition of sensor data, where varying signal features are extracted by different-sized convolutional kernels. The human-machine interaction system by combining the on-skin triboelectric sensors and algorithm achieves up to 99.12% accuracy when identifying 26 distinct gestures, which holds vast potential in several areas, such as gesture recognition, virtual reality, and teleoperation.

Differential Cortical and Subcortical Activations during Different Stages of Muscle Control: A Functional Magnetic Resonance Imaging Study.

Movement and muscle control are crucial for the survival of all free-living organisms. This study aimed to explore differential patterns of cortical and subcortical activation across different stages of muscle control using functional magnetic resonance imaging (fMRI). An event-related design was employed. In each trial, participants (n = 10) were instructed to gently press a button with their right index finger, hold it naturally for several seconds, and then relax the finger. Neural activation in these temporally separated stages was analyzed using a General Linear Model. Our findings revealed that a widely distributed cortical network, including the supplementary motor area and insula, was implicated not only in the pressing stage, but also in the relaxation stage, while only parts of the network were involved in the steady holding stage. Moreover, supporting the direct/indirect pathway model of the subcortical basal ganglia, their substructures played distinct roles in different stages of muscle control. The caudate nucleus exhibited greater involvement in muscle contraction, whereas the putamen demonstrated a stronger association with muscle relaxation; both structures were implicated in the pressing stage. Furthermore, the subthalamic nucleus was exclusively engaged during the muscle relaxation stage. We conclude that even the control of simple muscle movements involves intricate automatic higher sensory-motor integration at a neural level, particularly when coordinating relative muscle movements, including both muscle contraction and muscle relaxation; the cortical and subcortical regions assume distinct yet coordinated roles across different stages of muscle control.

Decoding Group Emotional Dynamics in a Web-Based Collaborative Environment: A Novel Framework Utilizing Multi-Person Facial Expression Recognition

As a crucial form of non-verbal communication, facial expressions can convey an individual’s emotional state through a combination of facial muscle movements and provide an effective approach to understanding emotional shifts among group members to a certain extent. However, in real-time collaborative environments, the increasing influx of audiovisual information can overwhelm an individual’s limited visual attention, making it challenging to observe and analyze other group members’ facial expressions continually. The failure to promptly recognize and interpret facial expressions can disrupt individual and group-level comprehension and evaluation of emotional dynamics during collaborative interactions, consequently hindering subsequent emotion management and communication. This article delves into the classification of facial expression information and its formation mechanism to thoroughly analyze the relationship between group members’ emotional perceptions and expressions in the collaboration process. Leveraging the YOLO-FaceV2 face detection model, FaceNet face recognition model, and CERN expression recognition model, we present a novel Collaborative Emotion Analysis Framework (CEAF) for multi-person facial expression recognition. By employing Web real-time communication technology, this framework is integrated into an online group meetings system, which can identify the faces and expressions of the participants and provide real-time visual analysis of their expression information. After the conclusion of the meeting, the system can perform an emotional evaluation with pre-defined operators, providing invaluable insights into the emotional dynamics of the group and individual members throughout the collaborative process. Ultimately, validation through an online meeting instance indicates that this system can facilitate groups in interpreting emotional changes among collaborative group members to a considerable extent.

How Essential Oils Affect Children with Congenital Zika Virus Syndrome (CZVS)

Introduction: Within the field of dentistry, essential oils are well-known and extensively researched; eugenol is one of the most used, which until recently characterized the predominant smell of dental offices. Children with congenital Zika virus syndrome (CZVS) have various impairments, and in the dental area, the vast majority exhibit underdevelopment of the stomatognathic system compared to established normality standards. Many use various medications, such as anticonvulsants, muscle relaxants, sedatives, neuroleptics, among others, to control symptoms. These drug interactions can trigger involuntary muscle movements, including bruxism. There are several treatment proposals for teeth grinding and clenching, including appliance therapy, emotional therapies, medication, and also aromatherapy. Material and method: Syndromic and bruxist children were selected through validated questionnaires and clinical examination. A convenience sample of 19 syndromic children from Maceió was divided into two random groups: group 1 received a blend of essential oils, and group 2 received a control oil. They were instructed to apply it topically to the masseter, temples, and cervical area twice a day for two months. Sleep analysis was carried out through a questionnaire with 15 questions plus filling out a sleep chart for three days and collecting saliva in Salivette tubes for cortisol evaluation, with both data sets collected pre and post-use of essential oils. Discussion: Previous studies report that individuals with cognitive difficulties are more prone to bruxism due to spasticity, however, they are not definitive according to other studies. There are other factors such as stress, depression, external environmental stimuli that can influence this condition, in addition to the drug interaction they use to alleviate symptoms such as seizures, drooling, muscle spasms, muscle stiffness, insomnia. The etiology of bruxism is still considered multifactorial, requiring a multidisciplinary clinical team for more effective treatment. The use of essential oils as a stress and insomnia reliever is reported in studies with satisfactory results, being observed in this research. Result: In the finalization phase. Conclusion: Given the above, the proposal was to evaluate the efficacy of using essential oils in syndromic and bruxist children. Although we cannot confirm results yet, there are reports from mothers who evaluated the initiative positively, corroborating in some way the alleviation of symptoms and drug interactions, providing more emotional and physical comfort for those involved. However, more clinical trials are still necessary regarding the safety and efficacy aspects of essential oils.

Insights on Platelet-Derived Growth Factor Receptor α-Positive Interstitial Cells in the Male Reproductive Tract.

Male infertility is a significant factor in approximately half of all infertility cases and is marked by a decreased sperm count and motility. A decreased sperm count is caused by not only a decreased production of sperm but also decreased numbers successfully passing through the male reproductive tract. Smooth muscle movement may play an important role in sperm transport in the male reproductive tract; thus, understanding the mechanism of this movement is necessary to elucidate the cause of sperm transport disorder. Recent studies have highlighted the presence of platelet-derived growth factor receptor α (PDGFRα)-positive interstitial cells (PICs) in various smooth muscle organs. Although research is ongoing, PICs in the male reproductive tract may be involved in the regulation of smooth muscle movement, as they are in other smooth muscle organs. This review summarizes the findings to date on PICs in male reproductive organs. Further exploration of the structural, functional, and molecular characteristics of PICs could provide valuable insights into the pathogenesis of male infertility and potentially lead to new therapeutic approaches.

Primary isolated extranodal NK/T-cell lymphoma of the orbit: A case report and diagnostic dilemma

Natural killer T-cell lymphoma (NKTL) is associated with Epstein-Barr virus, a highly malignant tumor that typically arises in the nose and/or paranasal sinuses isolated orbital involvement by NKTL is extremely rare. Herein, we report a case of primary orbital NKTL in a young female patient. A 32-year-old female presented with gradually increasing painful swelling of the right eye. On examination, abaxial proptosis, inferolateral displacement of the eyeball, restricted extraocular muscle movement, and solid mass in the subconjunctival fornix and superior quadrant. The rest of the ocular and systemic examination was unremarkable. Magnetic resonance imaging with contrast of the orbit shows a lobulated mass lesion 35×30×18 mm involving the medial aspect of the right orbit extraconal and superior intraconal space extending up to the preseptal region. Informed consent and biopsy were done and sent for histopathology examination. Histopathological examination shows the spectrum of atypical lymphoid cells, indented or cleaved nuclei and pale to clear cytoplasm, few histiocytes, giant cells, and apoptotic body. To rule out lymphoma, immunohistochemistry (IHC) was advised. On IHC, tumor cells were positive for CD3, D56, CD4 focally, CD7, Ki-67–90% and negative for CD20, CD2, Tdt, PAX5, CD34, CD5, Cd8 leading to a diagnosis of extranodal NKTL of the orbit. To the best of our knowledge, around 20 cases of isolated orbital extranodal NKTL were reported in the literature review. Polymorphic lymphoid cell in a young patient often mimics the inflammatory conditions of orbit. The rarity of this tumor and inflammatory signs make it challenging to identify these tumors early.

High Sensitivity and Wide Linear Range Flexible Piezoresistive Pressure Sensor with Microspheres as Spacers for Pronunciation Recognition.

Flexible piezoresistive pressure sensors have received great popularity in flexible electronics due to their simple structure and promising applications in health monitoring and artificial intelligence. However, the contradiction between sensitivity and detection range limits the application of the sensors in the medium-pressure regime. Here, a flexible piezoresistive pressure sensor is fabricated by combining a hierarchical spinous microstructure sensitive layer and a periodic microsphere array spacer. The sensor achieves high sensitivity (39.1 kPa-1) and outstanding linearity (0.99, R2 coefficient) in a medium-pressure regime, as well as a wide range of detection (100 Pa-160.0 kPa), high detection precision (<0.63‰ full scale), and excellent durability (>5000 cycles). The mechanism of the microsphere array spacer in improving sensitivity and detection range was revealed through finite element analysis. Furthermore, the sensors have been utilized to detect muscle and joint movements, spatial pressure distributions, and throat movements during pronouncing words. By means of a full-connect artificial neural network for machine learning, the sensor's output of different pronounced words can be precisely distinguished and classified with an overall accuracy of 96.0%. Overall, the high-performance flexible pressure sensor based on a microsphere array spacer has great potential in health monitoring, human-machine interface, and artificial intelligence of medium-pressure regime.

Exploring the muscle architecture effect on the mechanical behaviour of mouse rotator cuff muscles

Incorporating detailed muscle architecture aspects into computational models can enable researchers to gain deeper insights into the complexity of muscle function, movement, and performance. In this study, we employed histological, multiphoton image processing, and finite element method techniques to characterise the mechanical dependency on the architectural behaviour of supraspinatus and infraspinatus mouse muscles. While mechanical tests revealed a stiffer passive behaviour in the supraspinatus muscle, the collagen content was found to be two times higher in the infraspinatus. This effect was unveiled by analysing the alignment of fibres during muscle stretch with the 3D models and the parameters obtained in the fitting. Therefore, a strong dependence of muscle behaviour, both active and passive, was found on fibre orientation rather than collagen content.

Effects of scapular treatment on chronic neck pain: a systematic review and meta-analysis of randomized controlled trials

BackgroundChronic neck pain (CNP) is a common public health problem that affects daily living activities and quality of life. There is biomechanical interdependence between the neck and scapula. Studies have shown that shoulder blade function might be related to chronic neck pain. We therefore evaluated the effects of scapular targeted therapy on neck pain and function in patients with CNP.MethodsDatabases, including MEDLINE (via PubMed), EMBASE (via Ovid), Ovid, Web of Science, and Scopus, were systematically searched for randomized controlled trials published in English investigating treatment of the scapula for CNP before July 16, 2023.ResultsA total of 313 participants were included from 8 RCTs. Compared with those in the control group, the intervention in the scapular treatment group exhibited greater improvement in pain intensity (standardized mean difference (SMD) = 2.55; 95% CI = 0.97 to 4.13; P = 0.002), with moderate evidence. Subgroup analysis for pain intensity revealed a significant difference between the sexes, with only the female population (SMD = 6.23, 95% CI = 4.80 to 7.65) showing better outcomes than those with both sexes (SMD = 1.07, 95% CI = 0.57 to 1.56) (p < 0.00001). However, moderate evidence demonstrated no improvement in neck disability after scapular treatment (SMD of 0.24[-0.14, 0.62] of Neck Disability Index or Northwick Park Neck Pain Questionnaire). No effect of scapular treatment was shown on the pressure pain threshold (PPT). The cervical range of motion (CROM) and electromyographic activity of neck muscles could not be conclusively evaluated due to limited support in the articles, and further study was needed. However, the patient’s head forward posture appeared to be corrected after scapular treatment.ConclusionScapular therapy was beneficial for relieving pain intensity in patients with CNP, especially in women. Head forward posture might also be corrected with scapular therapy. However, scapular therapy may have no effect on the PPT or neck disability. However, whether scapular therapy could improve CROM and cervical muscle activation in patients with CNPs had not been determined and needed further study.

Proximal Policy Optimization With Time-Varying Muscle Synergy for the Control of an Upper Limb Musculoskeletal System

Because of their unique adaptability, flexibility, and robustness, musculoskeletal robotic systems are regarded potentially as next-generation robots. However, motion learning and generation of such a robotic system are still challenging. This paper presents a neuromuscular control method, namely, TMS-PPO, based on time-varying muscle synergy (TMS) and proximal policy optimization (PPO). The electromyogram (EMG) activation signals of actual human motions are decomposed to obtain TMSs based on the temporal properties of the TMS. The weights of networks are trained to generate the scale and phase coefficients through the PPO. The coefficients modulate the TMSs to generate appropriate activation patterns to optimize motion learning of the musculoskeletal system. To verify the effectiveness of the proposed method, the TMSs are extracted from human upper limb muscle activation signals, and we compare TMS-PPO with PPO in the motion learning and generation process of an upper limb musculoskeletal system. The results show that TMS-PPO can complete the control tasks because the average errors of the joints are less than 0.05 rad. In the meantime, TMSs are used as motion primitives of the musculoskeletal system to simulate the process of the human CNS controlling muscles. It shows that TMS-PPO reduces the energy consumption and improves the learning rate significantly compared with the PPO. The learning episodes reduce from <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">\(10^4\)</tex-math> </inline-formula> to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">\(10^3\)</tex-math> </inline-formula> , which indicates that TMS-PPO has a stronger learning ability and better physiological explanation. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —Due to the superiorities of the musculoskeletal system, humanoid robots that imitate human driven mechanisms are vigorously carried out worldwide. Taking advantages of human-like characteristics, the musculoskeletal robot provides new opportunities to understand and validate the human mechanisms of muscle control and motion learning, to compare the performance of the robot to that of humans as well as work in real world, e.g., human interactive robots, amusement robots and medical training robots in the future. However, strong redundancy, coupling, and nonlinearity of the system also raises many challenges for the investigation of the control problem. Inspired by how the human CNS controls a musculoskeletal system and realize motion generalization, a novel muscle-synergies-based neuromuscular control that combines time-varying muscle synergy (TMS) and Proximal Policy Optimization (PPO), namely, TMS-PPO is proposed in this paper. The learning efficiency of PPO and the physiological interpretation of the control process are improved during the motion learning and generation processes of the musculoskeletal system. Preliminary simulation experiments suggest that this method is feasible in terms of control accuracy and efficiency. Moreover, the performance of the TMS-PPO is comparable to the PPO without significant improvement. To solve this problem, in future work, we will introduce the cerebellar model into the control method which plays the role of adjusting and correcting the motions of the limbs to achieve accurate and stable control in the actions process of humans.

140 Muscle Accelerometry as a Novel Marker of Axonal Injury in Chronic Entrapment Neuropathy

INTRODUCTION: Chronic entrapment neuropathy results in a clinical syndrome ranging from mild-pain to debilitating atrophy. There remains a lack of objective metrics that quantify nerve dysfunction and guide surgical decision-making. Muscle accelerometry quantify mechanical-motor-activity after stimulation of neuromuscular tissue and may enable evaluation of underlying nerve function. METHODS: Experimental Lewis-rats underwent compressions at proximal- and distal-sites of sciatic nerves using silicone-conduits. To simulate chronic-entrapment, sciatic nerves were compressed for 2-, 3-, and 4-months (n = 6 in each month) and were serially evaluated by accelerometry, compound-muscle-action-potential (CMAP), and compound-neural-action-potential (CNAP). To simulate recovery, sciatic nerves were decompressed at 3-months and tracked for additional 2-months with accelerometry, CMAP, and CNAP. In each group, the left-side served as control nerve and right-side served as experimental nerve. Accelerometry was acquired by custom-built-device after direct electrical-nerve-stimulation from 0.1-mA to 1.5-mA current. The accelerometry was quantified by composite magnitude of muscle movement in x-, y-, and z-axis. At each endpoint, histomorphometry analysis was performed to evaluate nerve injury and recovery. RESULTS: After each month of nerve compression, there was a trend in worsening of nerve function indicated by decline in accelerometry at higher stimulation current of 1.5-mA .This finding was correlated with CMAP and CNAP.At each endpoint of 2-, 3-, and 4-month, there was significant worsening in g-ratio of compressed nerve as compared to the control nerves. After decompression at 3-months, muscle accelerometry at 0.5 mA current indicated a clear trend in recovery of nerve function. This finding was correlated with CNAP, however, CMAP results were variable. CONCLUSIONS: The muscle accelerometry may serve as a quantitative marker of axonal function and neuromuscular reinnervation in chronic entrapment neuropathy.

Coupled simulations and parameter inversion for neural system and electrophysiological muscle models

AbstractThe functioning of the neuromuscular system is an important factor for quality of life. With the aim of restoring neuromuscular function after limb amputation, novel clinical techniques such as the agonist‐antagonist myoneural interface (AMI) are being developed. In this technique, the residual muscles of an agonist‐antagonist pair are (re‐)connected via a tendon in order to restore their mechanical and neural interaction. Due to the complexity of the system, the AMI can substantially profit from in silico analysis, in particular to determine the prestretch of the residual muscles that is applied during the procedure and determines the range of motion of the residual muscle pair. We present our computational approach to facilitate this. We extend a detailed multi‐X model for single muscles to the AMI setup, that is, a two‐muscle‐one‐tendon system. The model considers subcellular processes as well as 3D muscle and tendon mechanics and is prepared for neural process simulation. It is solved on high performance computing systems. We present simulation results that show (i) the performance of our numerical coupling between muscles and tendon and (ii) a qualitatively correct dependence of the range of motion of muscles on their prestretch. Simultaneously, we pursue a Bayesian parameter inference approach to invert for parameters of interest. Our approach is independent of the underlying muscle model and represents a first step toward parameter optimization, for instance, finding the prestretch, to be applied during surgery, that maximizes the resulting range of motion. Since our multi‐X fine‐grained model is computationally expensive, we present inversion results for reduced Hill‐type models. Our numerical results for cases with known ground truth show the convergence and robustness of our approach.

Effect of Filters in Photoplethysmography Analog Signals Using Open-Source LTspice Software

Analog signal processing plays a crucial role in the realm of biomedical signal analysis. This study investigates the application of analog signal processing techniques in the domain of biomedical signals, focusing on enhancing the quality and reliability of recorded physiological data. The primary emphasis is on the implementation of analog filters and amplifiers to address challenges such as noise reduction, signal conditioning, and overall signal improvement. The processing of physiological signals, such as photoplethysmography (PPG), necessitates the use of amplifiers and filters within a range of 0.4 to 5Hz. Signal noise can stem from various sources, including the test subject’s muscle movement, respiration, humming, power line interference, or even from the device itself. The research methodology involves a comparison of 3 different order of Butterworth filter circuits and their impact on the signal. The test input signal is derived from an SpO$_2$ simulator, read by a standard PPG sensor, and processed by the internal 12-bit ADC of Nucleo-F429ZI. The resulting data is stored in CSV format for subsequent use in filter design simulations with SPICE. For analog circuit designers, the utilization of SPICE in the form of LTspice proves invaluable. This open software, LTspice, boasts a simple yet powerful interface, facilitating a focus on the conceptualization and performance of the design

Motor or non-motor speech interference? A multimodal fMRI and direct cortical stimulation mapping study

We retrospectively analyzed data from 15 patients, with a normal pre-operative cognitive performance, undergoing awake surgery for left fronto-temporal low-grade glioma. We combined a pre-surgical measure (fMRI maps of motor- and language-related centers) with intra-surgical measures (MNI-registered cortical sites data obtained during intra-operative direct electrical stimulation, DES, while they performed the two most common language tasks: number counting and picture naming).Selective DES effects along the precentral gyrus/inferior frontal gyrus (and/or the connected speech articulation network) were obtained. DES of the precentral gyrus evoked the motor speech arrest, i.e., anarthria (with apparent mentalis muscle movements). We calculated the number of shared voxels between the lip-tongue and overt counting related- and silent naming-related fMRI maps and the Volumes of Interest (VOIs) obtained by merging together the MNI sites at which a given speech disturbance was observed, normalized on their mean the values (i.e., Z score). Both tongue- and lips-related movements fMRI maps maximally overlapped (Z = 1.05 and Z = 0.94 for lips and tongue vs. 0.16 and −1.003 for counting and naming) with the motor speech arrest seed. DES of the inferior frontal gyrus, pars opercularis and the rolandic operculum induced speech arrest proper (without apparent mentalis muscle movements). This area maximally overlapped with overt counting-related fMRI map (Z = −0.11 and Z = 0.09 for lips and tongue vs. 0.9 and 0.0006 for counting and naming). Interestingly, our fMRI maps indicated reduced Broca's area activity during silent speech compared to overt speech. Lastly, DES of the inferior frontal gyrus, pars opercularis and triangularis evoked variations of the output, i.e., dysarthria, a motor speech disorder occurring when patients cannot control the muscles used to produce articulated sounds (phonemes). Silent object naming-related fMRI map maximally overlapped (Z = −0.93 and Z = −1.04 for lips and tongue vs. −1.07 and 0.99 for counting and naming) with this seed.Speech disturbances evoked by DES may be thought of as selective interferences with specific recruitment of left inferior frontal gyrus and precentral cortex which are differentiable in terms of the specific interference induced.

Tripolar concentric ring electrodes for capturing localised electroencephalography signals during sleep.

By design, tripolar concentric ring electrodes (TCRE) provide more focal brain activity signals than conventional electroencephalography (EEG) electrodes placed further apart. This study compared spectral characteristics and rates of data loss to noisy epochs with TCRE versus conventional EEG signals recorded during sleep. A total of 20 healthy sleepers (12 females; mean [standard deviation] age 27.8 [9.6] years) underwent a 9-h sleep study. Participants were set up for polysomnography recording with TCRE to assess brain activity from 18 sites and conventional electrodes for EEG, eyes, and muscle movement. A fast Fourier transform using multitaper-based estimation was applied in 5-s epochs to scored sleep. Odds ratios with Bonferroni-adjusted 95% confidence intervals were calculated to determine the proportional differences in the number of noisy epochs between electrode types. Relative power was compared in frequency bands throughout sleep. Linear mixed models showed significant main effects of signal type (p < 0.001) and sleep stage (p < 0.001) on relative spectral power in each power band, with lower relative spectral power across all stages in TCRE versus EEG in alpha, beta, sigma, and theta activity, and greater delta power in all stages. Scalp topography plots showed distinct beta activation in the right parietal lobe with TCRE versus EEG. EEG showed higher rates of noisy epochs compared to TCRE (1.3% versus 0.8%, p < 0.001). TCRE signals showed marked differences in brain activity compared to EEG, consistent with more focal measurements and region-specific differences during sleep. TCRE may be useful for evaluating regional differences in brain activity with reduced muscle artefact compared to conventional EEG.

Degradable silk fibroin based piezoresistive sensor for wearable biomonitoring

Degradable wearable electronics are attracting increasing attention to weaken or eliminate the negative effect of waste e-wastes and promote the development of medical implants without secondary post-treatment. Although various degradable materials have been explored for wearable electronics, the development of degradable wearable electronics with integrated characteristics of highly sensing performances and low-cost manufacture remains challenging. Herein, we developed a facile, low-cost, and environmentally friendly approach to fabricate a biocompatible and degradable silk fibroin based wearable electronics (SFWE) for on-body monitoring. A combination of rose petal templating and hollow carbon nanospheres endows as-fabricated SFWE with good sensitivity (5.63 kPa−1), a fast response time (147 ms), and stable durability (15,000 cycles). The degradable phenomenon has been observed in the solution of 1 M NaOH, confirming that silk fibroin based wearable electronics possess degradable property. Furthermore, the as-fabricated SFWE have been demonstrated that have abilities to monitor knuckle bending, muscle movement, and facial expression. This work offers an ecologically-benign and cost-effective approach to fabricate high-performance wearable electronics.

3D Printing Self-Healing and Self-Adhesive Elastomers for Wearable Electronics in Amphibious Environments.

To meet the demands of challenging usage scenarios, there is an increasing need for flexible electronic skins that can operate properly not only in terrestrial environments but also extend to complex aquatic conditions. In this study, we develop an elastomer by incorporating dynamic urea bonds and hydrogen bonds into the polydimethylsiloxane backbone, which exhibits excellent autonomous self-healing and reversible adhesive performance in both dry and wet environments. A multifunctional flexible sensor with excellent sensing stability, amphibious self-healing capacity, and amphibious self-adhesive performance is fabricated through solvent-free 3D printing. The sensor has a high sensing sensitivity (GF = 45.1) and a low strain response threshold (0.25%) and can be used to detect small human movements and physiological activities, such as muscle movement, joint movement, respiration, and heartbeat. The wireless wearable sensing system assembled by coupling this device with a bluetooth transmission system is suitable for monitoring strenuous human movement in amphibious environments, such as playing basketball, cycling, running (terrestrial environments), and swimming (aquatic environments). The design strategy provides insights into enhancing the self-healing and self-adhesive properties of soft materials and promises a prospective avenue for fabricating flexible electronic skin that can work properly in amphibious environments.

Hydration Programmable, Shape Memorable Artificial Muscles for Antagonistic Movements

AbstractShape memory polymers (SMPs) capable of generating various deformations from anisotropic temporary shapes to permanent shapes have been emerging as soft robots. However, traditional SMPs cannot imitate the antagonistic movement of human skeletal muscles due to their modulus limitations in shape programming and recovery process. Herein, hydration programmable shape memory polymer (HP‐SMP)‐based fibers that can undergo reversible actuation by assembling antagonistic pairs are reported, where the shape programming of the antagonist muscle relies on the contraction of agonist muscle. HP‐SMP fibers are composed of tunicate cellulose nanocrystals (TCNCs) reinforced semi‐interpenetrating polymer networks. Leveraging their distinctive structure and hydration programmability, the HP‐SMP fibers exhibit large actuation strain (−60%) and high work capacity (751 J kg−1), allowing for reversible actuation under constant stress. Most significantly, the continuous antagonistic movements of HP‐SMP fibers assembled into artificial limbs are demonstrated to realize humanoid motion. This work provides new possibilities for replicating a series of lifelike human movements through the biomimetic design of antagonistic pairs of artificial muscles, utilizing renewable and sustainable biosourced materials.

Disruption of Neuromuscular Junction Following Spinal Cord Injury and Motor Neuron Diseases.

The neuromuscular junction (NMJ) is a crucial structure that connects the cholinergic motor neurons to the muscle fibers and allows for muscle contraction and movement. Despite the interruption of the supraspinal pathways that occurs in spinal cord injury (SCI), the NMJ, innervated by motor neurons below the injury site, has been found to remain intact. This highlights the importance of studying the NMJ in rodent models of various nervous system disorders, such as amyotrophic lateral sclerosis (ALS), Charcot-Marie-Tooth disease (CMT), spinal muscular atrophy (SMA), and spinal and bulbar muscular atrophy (SBMA). The NMJ is also involved in myasthenic disorders, such as myasthenia gravis (MG), and is vulnerable to neurotoxin damage. Thus, it is important to analyze the integrity of the NMJ in rodent models during the early stages of the disease, as this may allow for a better understanding of the condition and potential treatment options. The spinal cord also plays a crucial role in the functioning of the NMJ, as the junction relays information from the spinal cord to the muscle fibers, and the integrity of the NMJ could be disrupted by SCI. Therefore, it is vital to study SCI and muscle function when studying NMJ disorders. This review discusses the formation and function of the NMJ after SCI and potential interventions that may reverse or improve NMJ dysfunction, such as exercise, nutrition, and trophic factors.