Electromyographic biofeedback training in a cerebral palsy patient undergoing pronator teres rerouting and brachioradialis to extensor carpi radialis brevis tendon transfer surgery: A case report.

Several surgical procedures are used to treat dynamic pronation position of the forearm and flexion deformity of the wrist in cerebral palsy. Postoperative results of pronator teres rerouting were explored, while specially designed postoperative physiotherapy and its outcomes were limited. Herein, we present a case in whom the outcomes of electromyographic biofeedback (EMG-BF) training were assessed after pronator teres rerouting and brachioradialis tendon to extensor carpi radialis brevis tendon transfer combined with derotation osteotomy. The peak value increased, while the resting value decreased for the muscles after the intervention. Range of motion, hand function, manual ability, functional independence, and quality of life levels were improved. In conclusion, EMG biofeedback training may have a positive effect on neuromuscular control of pronator teres and brachioradialis. Free use of the upper extremity and improved manual ability positively affect the activity and quality of life of the patients.

Machine learning-empowered sleep staging classification using multi-modality signals.

The goal is to enhance an automated sleep staging system's performance by leveraging the diverse signals captured through multi-modal polysomnography recordings. Three modalities of PSG signals, namely electroencephalogram (EEG), electrooculogram (EOG), and electromyogram (EMG), were considered to obtain the optimal fusions of the PSG signals, where 63 features were extracted. These include frequency-based, time-based, statistical-based, entropy-based, and non-linear-based features. We adopted the ReliefF (ReF) feature selection algorithms to find the suitable parts for each signal and superposition of PSG signals. Twelve top features were selected while correlated with the extracted feature sets' sleep stages. The selected features were fed into the AdaBoost with Random Forest (ADB + RF) classifier to validate the chosen segments and classify the sleep stages. This study's experiments were investigated by obtaining two testing schemes: epoch-wise testing and subject-wise testing. The suggested research was conducted using three publicly available datasets: ISRUC-Sleep subgroup1 (ISRUC-SG1), sleep-EDF(S-EDF), Physio bank CAP sleep database (PB-CAPSDB), and S-EDF-78 respectively. This work demonstrated that the proposed fusion strategy overestimates the common individual usage of PSG signals.

Combining enhanced spectral resolution of EMG and a deep learning approach for knee pathology diagnosis.

Knee osteoarthritis (OA) is a prevalent, debilitating joint condition primarily affecting the elderly. This investigation aims to develop an electromyography (EMG)-based method for diagnosing knee pathologies. EMG signals of the muscles surrounding the knee joint were examined and recorded. The principal components of the proposed method were preprocessing, high-order spectral analysis (HOSA), and diagnosis/recognition through deep learning. EMG signals from individuals with normal and OA knees while walking were extracted from a publicly available database. This examination focused on the quadriceps femoris, the medial gastrocnemius, the rectus femoris, the semitendinosus, and the vastus medialis. Filtration and rectification were utilized beforehand to eradicate noise and smooth EMG signals. Signals' higher-order spectra were analyzed with HOSA to obtain information about nonlinear interactions and phase coupling. Initially, the bicoherence representation of EMG signals was devised. The resulting images were fed into a deep-learning system for identification and analysis. A deep learning algorithm using adapted ResNet101 CNN model examined the images to determine whether the EMG signals were conventional or indicative of knee osteoarthritis. The validated test results demonstrated high accuracy and robust metrics, indicating that the proposed method is effective. The medial gastrocnemius (MG) muscle was able to distinguish Knee osteoarthritis (KOA) patients from normal with 96.3±1.7% accuracy and 0.994±0.008 AUC. MG has the highest prediction accuracy of KOA and can be used as the muscle of interest in future analysis. Despite the proposed method's superiority, some limitations still require special consideration and will be addressed in future research.

Effects of static exercises on hip muscle fatigue and knee wobble assessed by surface electromyography and inertial measurement unit data.

Hip muscle weakness can be a precursor to or a result of lower limb injuries. Assessment of hip muscle strength and muscle motor fatigue in the clinic is important for diagnosing and treating hip-related impairments. Muscle motor fatigue can be assessed with surface electromyography (sEMG), however sEMG requires specialized equipment and training. Inertial measurement units (IMUs) are wearable devices used to measure human motion, yet it remains unclear if they can be used as a low-cost alternative method to measure hip muscle fatigue. The goals of this work were to (1) identify which of five pre-selected exercises most consistently and effectively elicited muscle fatigue in the gluteus maximus, gluteus medius, and rectus femoris muscles and (2) determine the relationship between muscle fatigue using sEMG sensors and knee wobble using an IMU device. This work suggests that a wall sit and single leg knee raise activity fatigue the gluteus medius, gluteus maximus, and rectus femoris muscles most reliably (p < 0.05) and that the gluteus medius and gluteus maximus muscles were fatigued to a greater extent than the rectus femoris (p = 0.031 and p = 0.0023, respectively). Additionally, while acceleration data from a single IMU placed on the knee suggested that more knee wobble may be an indicator of muscle fatigue, this single IMU is not capable of reliably assessing fatigue level. These results suggest the wall sit activity could be used as simple, static exercise to elicit hip muscle fatigue in the clinic, and that assessment of knee wobble in addition to other IMU measures could potentially be used to infer muscle fatigue under controlled conditions. Future work examining the relationship between IMU data, muscle fatigue, and multi-limb dynamics should be explored to develop an accessible, low-cost, fast and standardized method to measure fatiguability of the hip muscles in the clinic.

Clinical and genetic characteristics of myotonia congenita in Chinese population.

Myotonia congenita (MC) is a rare hereditary muscle disease caused by variants in the CLCN1 gene. Currently, the correlation of phenotype-genotype is still uncertain between dominant-type Thomsen (TMC) and recessive-type Becker (BMC). The clinical data and auxiliary examinations of MC patients in our clinic were retrospectively collected. Electromyography was performed in 11 patients and available family members. Whole exome sequencing was conducted in all patients. The clinical and laboratory data of Chinese MC patients reported from June 2004 to December 2022 were reviewed. A total of 11 MC patients were included in the study, with a mean onset age of 12.64 ± 2.73 years. The main symptom was muscle stiffness of limbs. Warm-up phenomenon and percussion myotonia were found in all patients. Electromyogram revealed significant myotonic charges in all patients and two asymptomatic carriers, while muscle MRI and biopsy showed normal or nonspecific changes. Fourteen genetic variants including 6 novel variants were found in CLCN1. Ninety-eight Chinese patients were re-analyzed and re-summarized in this study. There were no significant differences in the demographic data, clinical characteristics, and laboratory findings between 52 TMC and 46 BMC patients. Among the 145 variants in CLCN1, some variants, including the most common variant c.892 G>A, could cause TMC in some families and BMC in others. This study expanded the clinical and genetic spectrum of Chinese patients with MC. It was difficult to distinguish between TMC and BMC only based on the clinical, laboratory, and genetic characteristics.

Context-informed incremental learning improves both the performance and resilience of myoelectric control.

Despite its rich history of success in controlling powered prostheses and emerging commercial interests in ubiquitous computing, myoelectric control continues to suffer from a lack of robustness. In particular, EMG-based systems often degrade over prolonged use resulting in tedious recalibration sessions, user frustration, and device abandonment. Unsupervised adaptation is one proposed solution that updates a model's parameters over time based on its own predictions during real-time use to maintain robustness without requiring additional user input or dedicated recalibration. However, these strategies can actually accelerate performance deterioration when they begin to classify (and thus adapt) incorrectly, defeating their own purpose. To overcome these limitations, we propose a novel adaptive learning strategy, Context-Informed Incremental Learning (CIIL), that leverages in situ context to better inform the prediction of pseudo-labels. In this work, we evaluate these CIIL strategies in an online target acquisition task for two use cases: (1) when there is a lack of training data and (2) when a drastic and enduring alteration in the input space has occurred. A total of 32 participants were evaluated across the two experiments. The results show that the CIIL strategies significantly outperform the current state-of-the-art unsupervised high-confidence adaptation and outperform models trained with the conventional screen-guided training approach, even after a 45-degree electrode shift (p < 0.05). Consequently, CIIL has substantial implications for the future of myoelectric control, potentially reducing the training burden while bolstering model robustness, and leading to improved real-time control.

A comprehensive dataset on biomechanics and motor control during human walking with discrete mechanical perturbations.

Background: Humans have a remarkable capability to maintain balance while walking. There is, however, a lack of publicly available research data on reactive responses to destabilizing perturbations during gait. Methods: Here, we share a comprehensive dataset collected from 10 participants who experienced random perturbations while walking on an instrumented treadmill. Each participant performed six 5-min walking trials at a rate of 1.2 m/s, during which rapid belt speed perturbations could occur during the participant's stance phase. Each gait cycle had a 17% probability of being perturbed. The perturbations consisted of an increase of belt speed by 0.75 m/s, delivered with equal probability at 10%, 20%, 30%, 40%, 50%, 60%, 70%, or 80% of the stance phase. Data were recorded using motion capture with 25 markers, eight inertial measurement units (IMUs), and electromyography (EMG) from the tibialis anterior (TA), soleus (SOL), lateral gastrocnemius (LG), rectus femoris (RF), vastus lateralis (VL), vastus medialis (VM), biceps femoris (BF), and gluteus maximus (GM). The full protocol is described in detail. Results: We provide marker trajectories, force plate data, EMG data, and belt speed information for all trials and participants. IMU data is provided for most participants. This data can be useful for identifying neural feedback control in human gait, biologically inspired control systems for robots, and the development of clinical applications.

The role of electrodiagnosis in focal neuropathies.

Electrodiagnostic (EDX) testing plays an important role in confirming a mononeuropathy, localizing the site of nerve injury, defining the pathophysiology, and assessing the severity and prognosis. The combination of nerve conduction studies (NCS) and needle electromyography findings provides the necessary information to fully assess a nerve. The pattern of NCS abnormalities reflects the underlying pathophysiology, with focal slowing or conduction block in neuropraxic injuries and reduced amplitudes in axonotmetic injuries. Needle electromyography findings, including spontaneous activity and voluntary motor unit potential changes, complement the NCS findings and further characterize chronicity and degree of axon loss and reinnervation. EDX is used as an objective marker to follow the progression of a mononeuropathy over time.

Neurologic Approach to Radiculopathy, Back Pain, and Neck Pain.

Back pain and neck pain are common in clinical practice, but significant challenges and pitfalls exist in their diagnosis, treatment, and management. From the neurologic standpoint, cervical radiculopathy and lumbosacral radiculopathy are characterized by neck pain or back pain accompanied by sensory and motor symptoms in an arm or leg. The basic neurologic examination is vital, but testing like electromyography and MRI is often needed especially in cases that fail conservative management. Oral medications, injection-based therapies, physical therapy, and surgical evaluation all have a place in the comprehensive neurologic management of back and neck pain and associated radiculopathy.

Optimizing shoulder elevation assist rate in exoskeletal rehabilitation based on muscular activity indices: a clinical feasibility study.

BACKGROUND: Restoring shoulder function is critical for upper-extremity rehabilitation following a stroke. The complex musculoskeletal anatomy of the shoulder presents a challenge for safely assisting elevation movements through robotic interventions. The level of shoulder elevation assistance in rehabilitation is often based on clinical judgment. There is no standardized method for deriving an optimal level of assistance, underscoring the importance of addressing abnormal movements during shoulder elevation, such as abnormal synergies and compensatory actions. This study aimed to investigate the effectiveness and safety of a newly developed shoulder elevation exoskeleton robot by applying a novel optimization technique derived from the muscle synergy index. METHODS: Twelve chronic stroke participants underwent an intervention consisting of 100 robot-assisted shoulder elevation exercises (10 × 10 times, approximately 40 min) for 10 days (4-5 times/week). The optimal robot assist rate was derived by detecting the change points using the co-contraction index, calculated from electromyogram (EMG) data obtained from the anterior deltoid and biceps brachii muscles during shoulder elevation at the initial evaluation. The primary outcomes were the Fugl-Meyer assessment-upper extremity (FMA-UE) shoulder/elbow/forearm score, kinematic outcomes (maximum angle of voluntary shoulder flexion and elbow flexion ratio during shoulder elevation), and shoulder pain outcomes (pain-free passive shoulder flexion range of motion [ROM] and visual analogue scale for pain severity during shoulder flexion). The effectiveness and safety of robotic therapy were examined using the Wilcoxon signed-rank sum test. RESULTS: All 12 patients completed the procedure without any adverse events. Two participants were excluded from the analysis because the EMG of the biceps brachii was not obtained. Ten participants (five men and five women; mean age: 57.0 [5.5] years; mean FMA-UE total score: 18.7 [10.5] points) showed significant improvement in the FMA-UE shoulder/elbow/forearm score, kinematic outcomes, and pain-free passive shoulder flexion ROM (P < 0.05). The shoulder pain outcomes remained unchanged or improved in all patients. CONCLUSIONS: The study presents a method for deriving the optimal robotic assist rate. Rehabilitation using a shoulder robot based on this derived optimal assist rate showed the possibility of safely improving the upper-extremity function in patients with severe stroke in the chronic phase.

sEMG-based automatic characterization of swallowed materials.

Monitoring of ingestive activities is critically important for managing the health and wellness of individuals with various health conditions, including the elderly, diabetics, and individuals seeking better weight control. Monitoring swallowing events can be an ideal surrogate for developing streamlined methods for effective monitoring and quantification of eating or drinking events. Swallowing is an essential process for maintaining life. This seemingly simple process is the result of coordinated actions of several muscles and nerves in a complex fashion. In this study, we introduce automated methods for the detection and quantification of various eating and drinking activities. Wireless surface electromyography (sEMG) was used to detect chewing and swallowing from sEMG signals obtained from the sternocleidomastoid muscle, in addition to signals obtained from a wrist-mounted IMU sensor. A total of 4675 swallows were collected from 55 participants in the study. Multiple methods were employed to estimate bolus volumes in the case of fluid intake, including regression and classification models. Among the tested models, neural networks-based regression achieved an R2 of 0.88 and a root mean squared error of 0.2 (minimum bolus volume was 10 ml). Convolutional neural networks-based classification (when considering each bolus volume as a separate class) achieved an accuracy of over 99% using random cross-validation and around 66% using cross-subject validation. Multiple classification methods were also used for solid bolus type detection, including SVM and decision trees (DT), which achieved an accuracy above 99% with random validation and above 94% in cross-subject validation. Finally, regression models with both random and cross-subject validation were used for estimating the solid bolus volume with an R2 value that approached 1 and root mean squared error values as low as 0.00037 (minimum solid bolus weight was 3 gm). These reported results lay the foundation for a cost-effective and non-invasive method for monitoring swallowing activities which can be extremely beneficial in managing various chronic health conditions, such as diabetes and obesity.

Intermuscular coherence as an early biomarker for amyotrophic lateral sclerosis: The protocol for a prospective, multicenter study.

OBJECTIVE: To describe the protocol of a prospective study to test the validity of intermuscular coherence (IMC) as a diagnostic tool and biomarker of upper motor neuron degeneration in amyotrophic lateral sclerosis (ALS). METHODS: This is a multicenter, prospective study. IMC of muscle pairs in the upper and lower limbs is gathered in ∼650 subjects across three groups using surface electrodes and conventional electromyography (EMG) machines. The following subjects will be tested: 1) neurotypical controls; 2) patients with symptomatology suggestive for early ALS but not meeting probable or definite ALS by Awaji Criteria; 3) patients with a known ALS mimic. The recruitment period is between 3/31/2021 and 12/31/2025. Written consent will be sought from the subject or the subject's legally authorized representative during enrollment. RESULTS: The endpoints of this study include: 1) whether adding IMC to the Awaji ALS criteria improve its sensitivity in early ALS and can allow for diagnosis earlier; 2) constructing a database of IMC across different ages, genders, and ethnicities. SIGNIFICANCE: This study may validate a new inexpensive, painless, and widely available tool for the diagnosis of ALS.

Neurophysiological, balance and motion evidence in adolescent idiopathic scoliosis: A systematic review.

BACKGROUND: Adolescent idiopathic scoliosis (AIS) is a spinal deformity that affects approximately 4% of the world's population. Several hypotheses regarding the etiology of AIS have been investigated. In the last decades, impaired visual-spatial perception, alterations in spatial body orientation and sensory integration deficits have been documented. OBJECTIVE: We aimed to summarize the neurophysiological, balance, and motion evidence related to AIS published in the last fifteen years, between January 2008 and April 2023. Both observational and interventional studies were considered. Only studies using quantitative assessment methods, such as electroencephalography (EEG), electromyography (EMG), magnetic resonance imaging (MRI), somatosensory evoked potentials, force platform, or motion capture, were included. METHODS: 1250 eligible records identified from online database searching were filtered by duplicate removal, title and abstract screening, and qualitative analysis. 61 articles met the inclusion criteria (i.e., Cobb range 10°-35°, age range 10-18 years) and were summarized. RESULTS: We found significant evidence of impaired standing balance in individuals with AIS who greatly rely on visual and proprioceptive information to stay upright. EMG studies frequently reported an increased activity on the convex side of the intrinsic spinae muscles. EEG data show increased delta and theta power, higher alpha peak frequencies, and significant suppression in the alpha and beta bands in subjects with AIS during standing tasks. MRI studies report changes in white matter structures, differences in the vestibular system, and abnormal cortical activations over motor-related areas in subjects with AIS. Bracing appears to be an effective treatment for AIS, leading to improvements in static balance and gait. Methodological issues prevent reliable conclusions about the effects of other treatment options. CONCLUSIONS: This review underscores the importance of quantitative assessment methods to explore the etiology and pathophysiology of AIS. Further research is needed to measure the impact of physical therapy and orthotic treatments on the neurophysiological mechanisms of the disease.

Performance in myoelectric pattern recognition improves with transcranial direct current stimulation.

Sensorimotor impairments, resulting from conditions like stroke and amputations, can profoundly impact an individual's functional abilities and overall quality of life. Assistive and rehabilitation devices such as prostheses, exo-skeletons, and serious gaming in virtual environments can help to restore some degree of function and alleviate pain after sensorimotor impairments. Myoelectric pattern recognition (MPR) has gained popularity in the past decades as it provides superior control over said devices, and therefore efforts to facilitate and improve performance in MPR can result in better rehabilitation outcomes. One possibility to enhance MPR is to employ transcranial direct current stimulation (tDCS) to facilitate motor learning. Twelve healthy able-bodied individuals participated in this crossover study to determine the effect of tDCS on MPR performance. Baseline training was followed by two sessions of either sham or anodal tDCS using the dominant and non-dominant arms. Assignments were randomized, and the MPR task consisted of 11 different hand/wrist movements, including rest or no movement. Surface electrodes were used to record EMG and the MPR open-source platform, BioPatRec, was used for decoding motor volition in real-time. The motion test was used to evaluate performance. We hypothesized that using anodal tDCS to increase the excitability of the primary motor cortex associated with non-dominant side in able-bodied individuals, will improve motor learning and thus MPR performance. Overall, we found that tDCS enhanced MPR performance, particularly in the non-dominant side. We were able to reject the null hypothesis and improvements in the motion test's completion rate during tDCS (28% change, p-value: 0.023) indicate its potential as an adjunctive tool to enhance MPR and motor learning. tDCS appears promising as a tool to enhance the learning phase of using assistive devices using MPR, such as myoelectric prostheses.

Caffeine Expectancy Does Not Influence the Physical Working Capacity at the Fatigue Threshold.

ABSTRACT: Ambrozy, CA, Hawes, NE, Hayden, OL, Sortzi, I, and Malek, MH. Caffeine expectancy does not influence the physical working capacity at the fatigue threshold. J Strength Cond Res 38(6): 1056-1062, 2024-The placebo effect occurs when a desired outcome is experienced due to the belief that a treatment is effective, even in the absence of an active ingredient. One explanation for this effect is based on a person's expectations of a drug or supplement. Although caffeine's effects on sports performance have been studied, little is known about how expectations of caffeine affect neuromuscular fatigue during continuous muscle action. The physical working capacity at the fatigue threshold (PWCFT) can be used to assess neuromuscular fatigue noninvasively using surface electromyography. Thus, the purpose of this study was to investigate whether caffeine expectancy influences PWCFT. We hypothesized that regardless of expectancy, caffeine consumption would delay neuromuscular fatigue. The study involved 8 healthy college-aged men (mean ± SEM: age, 25.6 ± 1.0 years) who visited the laboratory on 4 occasions, each separated by 7 days. The subjects completed 4 experimental conditions, in random order, where they were told that they were consuming caffeine or placebo and either received caffeine or placebo. After consuming the drink, the subjects remained in the laboratory for an hour and then performed an incremental exercise test. The results showed that the condition where subjects were told that they were consuming caffeine and received caffeine had significantly higher mean values for maximal power output (F(3, 21) = 11.75; p < 0.001), PWCFT (F(3, 21) = 12.28; p < 0.001), PWCFT (%maximal power output; F(3, 21) = 8.75; p < 0.001), and heart rate at end exercise (%predicted; F(3, 21) = 3.83; p = 0.025) compared with the 2 conditions where placebo was received. However, no statistically significant mean differences were found from the condition where subjects were told that they were consuming placebo but consuming caffeine. This suggests that a person's expectancy and potential somatic response may serve as a cue for how an ergogenic aid or placebo could affect subsequent performance.

Relevant Biomechanical Variables in Skateboarding: A Literature Review.

Skateboarding, once regarded primarily as a means of transportation and entertainment for youth, has become a recognized professional sport, gaining global popularity. With its recent inclusion in the Olympics, a growing imperative exists to comprehensively understand biomechanics explaining skateboarding performance. This literature review seeks to consolidate knowledge within this domain, focusing on experimental and modeling studies about skateboard riding and tricks. The criteria for study selection encompassed content relevance and publication year, spanning from the last two decades and extending further back to 1980 following cross-referencing of seminal works. Peer-reviewed journal articles, conference proceedings, and books were considered, with comprehensive searches conducted on electronic databases, including SCOPUS, PubMed, Scielo, and Taylor & Francis. Comprehending the biomechanical facets of skateboarding is essential in promoting its use and ensuring safety among all practitioners. Insights into factors such as body kinetics, kinematics, and muscle activation represent a foundational step toward understanding the nuances of this sport with implications for both clinical and biomechanical research. Modern data collection systems such as inertial measurement units (IMU) and electromyography (EMG) offer unprecedented insights into human performance during skateboarding, such as joint range of motion, coordination, and muscle activation, whether in casual riding or executing complex tricks and maneuvers. Developing robust modeling approaches also holds promise for enhancing skateboarding training and performance. Crucially, these models can serve as the initial framework for understanding injury mechanisms and implementing strategies to improve performance and mitigate injury risks.

Clustering index analysis on EMG-Torque relation-based representation of complex neuromuscular changes after spinal cord injury.

Spinal cord injury (SCI) resulting in complex neuromuscular pathology is not sufficiently well understood. To better quantify neuromuscular changes after SCI, this study uses a clustering index (CI) method for surface electromyography (sEMG) clustering representation to investigate the relation between sEMG and torque in SCI survivors. The sEMG signals were recorded from 13 subjects with SCI and 13 gender-age matched able-bodied subjects during isometric contraction of the biceps brachii muscle at different torque levels using a linear electrode array. Two torque representations, maximum voluntary contraction (MVC%) and absolute torque, were used. CI values were calculated for sEMG. Regression analyses were performed on CI values and torque levels of elbow flexion, revealing a strong linear relationship. The slopes of regressions between SCI survivors and control subjects were compared. The findings indicated that the range of distribution of CI values and slopes was greater in subjects with SCI than in control subjects (p < 0.05). The increase or decrease in slope was also observed at the individual level. This suggests that the CI and its sEMG clustering-torque relation may serve as valuable quantitative indicators for determining neuromuscular lesions after SCI, contributing to the development of effective rehabilitation strategies for improving motor performance.

Orbicularis oculi muscle activity during computer reading under different degrees of artificially-induced aniseikonia.

Background: Aniseikonia is a binocular vision disorder that has been associated with asthenopic symptoms. However, asthenopia has been evaluated with subjective tests that make difficult to determine the level of aniseikonia. This study aims to objectively evaluate the impact of induced aniseikonia at different levels on visual fatigue by measuring the orbicularis oculi muscle activity in the dominant and non-dominant eyes while performing a reading task. Methods: Twenty-four collegiate students (24.00 ± 3.86 years) participated in this study. Participants read a passage for 7 minutes under four degrees of aniseikonia (0%, 3%, 5% and 10%) at 50 cm. Orbicularis oculi muscle activity of the dominant and non-dominant eye was recorded by surface electromyography. In addition, visual discomfort was assessed after each task by completing a questionnaire. Results: Orbicularis oculi muscle activity increased under induced aniseikonia (i.e., greater values for the 10% condition in comparison to 0%, and 3% conditions (p = 0.034 and p = 0.023, respectively)). No statistically significant differences were observed in orbicularis oculi muscle activity for the time on task and between the dominant and non-dominant eyes. Additionally, higher levels of subjective visual discomfort were observed for lower degrees of induced aniseikonia. Conclusion: Induced aniseikonia increases visual fatigue at high aniseikonia degrees as measured by the orbicularis oculi muscle activity, and at low degrees as measured with subjective questionnaires. These findings may be of relevance to better understand the visual symptomatology of aniseikonia.

Effect of a slump posture on pain, proprioception, and electrical activity of the muscles in office workers with chronic non-specific neck pain. A retrospective study.

BACKGROUND: The impact of computer typing in a slump posture on pain, proprioception and muscle recruitment has not been extensively investigated. Therefore, the purpose of this study was to evaluate the extent of pain, proprioception and muscle activity resulting from computer typing in a slump posture in women who already suffer from chronic neck pain. METHODS: This cross-sectional study was conducted between May 20 to July 10, 2021. A total of 15 female 42-(±4.96)-year-old office workers with chronic non-specific neck pain participated in this study. Before and after 60 min of computer typing in a slump posture, proprioception and pain were measured using an inclinometer and visual analog scale (VAS), respectively. The activity of the cervical erector spine (CES) and upper trapezius (UT) muscle was also measured before and after the slump-posture computer typing, in upright, forward, and slump postures. RESU: lts: Paired-samples t-tests showed that pain was increased and proprioception in all directions (flexion, extension, right and left lateral flexion, and right, and left rotation) was less accurate (P < 0.05) after 60 min computer typing. The CES and UT muscle activity were elevated more in the forward head and slump posture than in the upright posture (P < 0.05). CONCLUSION: Sixty minutes computer typing in a slump posture increased neck pain, resulted in a decreased proprioception in the neck and was accompanied by an increased activity of the neck musculature.

Acute responses of postural alignment and intermuscular coherence to anti-gravitational muscle engagement-A randomized crossover trial.

INTRODUCTION: Posture is a facet of clinical assessment in several rehabilitative disciplines. Despite extensive clinical focus, the precision with which posture can be evaluated and intervened upon is limited by the very general terms used to describe it. The purpose of this crossover trial was to quantify the effects of targeted postural intervention motivated by theoretical sagittal gravitational collapsing (SGC) tendencies on: 1) distance from SGC, 2) intermuscular coherence (iCOH), and 3) kinematic chain connectivity. METHODS: Ten healthy adults (24.50 ± 1.18 years, 172.72 ± 10.19 cm, 76.47 ± 14.60 kg) completed pre- and post-intervention testing on two occasions involving contrasting interventions: promote postural muscle (PPM) vs. reduce compensatory muscle (RCM) engagement. Distance from SGC, iCOH, and kinematic chain connectivity were quantified from electromyography and/or kinematic data acquired during tests administered before and after interventions. Effects of Treatment [PPM, RCM] and Time [Pre, Post] were tested with linear mixed models. RESULTS: A Treatment*Time interaction was observed for distance from SGC. Post-intervention distance from SGC was greater following PPM only (p < 0.01). A Treatment*Time interaction was observed for hi-frequency trunk muscle iCOH, with a post-intervention increase corresponding to the RCM intervention (p < 0.007). Additional iCOH effects did not differ by intervention. CONCLUSION: Distance from SGC is acutely modifiable and increases following exercises to facilitate anti-SGC muscles. Convergent findings related to kinematic chain connectivity and prescriptive neural binding were not observed. These observations suggest that it may be possible to describe, evaluate, and intervene upon posture in reference to a specific, mechanistic theory regarding the function of postural alignment.