Muscle Activation Patterns Research Articles

Student physical education teaching achievement test incorporating biomechanics analysis via decision tree algorithm

In the context of China’s economic growth, building a “sports power” is crucial. With the Internet’s development, the nation focuses on physical education curriculum and students’ test results. Currently, Chinese students’ physical education achievements are mainly evaluated by storage, inquiry, and basic statistics. Digital mining is under - utilized, leaving much data unexplored. But digital education’s progress has brought educational data to the fore, enabling schools to find value and patterns for better teaching decisions. In this case, this paper delves into the integration of biomechanics analysis into the assessment of student physical education teaching achievements. Biomechanics offers invaluable insights into the mechanical aspects of human movement during physical activities. By examining biomechanical factors such as joint angles, muscle forces, and movement velocities during various sports, a more profound understanding of students’ physical capabilities and performance can be achieved. Taking the physical test results of students in a specific school as a case study, this research employs data mining technology to explore the rich dataset. The optimized decision tree algorithm is then utilized to analyze the biomechanics - related data. This algorithm enables the identification of key factors that influence students’ physical test outcomes. For instance, it can pinpoint how a student’s running gait mechanics, including stride length, frequency, and leg - muscle activation patterns, affect their performance in track - and - field events. Through this comprehensive approach, the paper not only aims to uncover hidden information within the physical test data but also to elucidate the intricate interplay between biomechanics and students’ overall physical education performance. By dissecting the factors that influence physical test results from a biomechanical perspective, this study provides actionable insights for enhancing physical education teaching methods. Educators can leverage these findings to design personalized teaching programs that cater to the unique biomechanical characteristics of each student, thereby optimizing the effectiveness of physical education and promoting students’ physical development and athletic performance.

Masticatory muscle activation patterns manifested by changes in index values

Relevance. Surface electromyography (sEMG) is a method used to record the bioelectrical activity of masticatory muscles both at rest and during movement. This method generates relative metrics (indices) that reflect the relationship between the biopotentials of individual muscles and muscle pairs. The objective of this study was to explore the activation patterns of the temporal and masseter muscles during different test movements, as expressed by variations in test index values, while accounting for correlations among relative metrics.Materials and methods. Surface electromyography was performed on the temporal and masseter muscles of 165 participants aged 18 to 25 years. The study involved the following tests: “Physiological rest”, “Habitual occlusion”, “Maximal voluntary clenching of the dental arches”, and “Maximal voluntary clenching on cotton rolls”. Indices were calculated to characterize the distribution of bioelectrical activity between homologous muscles (symmetry indices) and muscle pairs (the static stabilizing occlusal index and the mandibular lateral displacement index). Initially, participants were divided into three groups of 20 individuals each based on the mandibular lateral displacement index (TORS) values recorded during the “Physiological rest” test. Data were compared across these groups. Subsequently, the same 165 participants were divided again into three groups of 20 individuals each, based on the TORS values obtained during the “Habitual occlusion” test, and the calculated results were compared across these groups. This procedure was repeated for TORS indices derived from the “Maximal voluntary clenching of the dental arches” and “Maximal voluntary clenching on cotton rolls” tests. The study ultimately examined 12 groups of 20 participants each, categorized by TORS index values (%) calculated for the four tests: ≤80% (groups 1, 4, 7, 10), 95–105% (groups 2, 5, 8, 11), and ≥120% (groups 3, 6, 9, 12). The mean values of the measured indices were compared between groups to determine statistically significant differences. Correlations were evaluated for their presence, strength, and direction both within indices recorded during the same test and across indices obtained from different tests.Results. The analysis identified a positive correlation between the TORS index and the temporal muscle symmetry index in the “Physiological rest” test, ranging from moderate to strong: groups 1 and 2 (rs = 0.6, p < 0.001), groups 2 and 3 (rs = 0.6, p < 0.001), and groups 1 and 3 (rs = 0.8, p < 0.001. In the same test, the TORS index also correlated with the masseter muscle symmetry index, displaying a moderate to strong negative association: groups 1 and 2 а (rs = -0.57, p < 0.001), groups 2 and 3 (rs = -0.49, p < 0.001), groups 2 and 3 (rs = -0.7, p < 0.001). The relationship between TORS index values during dental arch clenching without masticatory muscle tension and temporal muscle symmetry index was characterized as moderate to strong and positive: groups 4 and 5 (rs = 0.81, p < 0.001), groups 5 and 6 (rs = 0.41, p = 0.002), groups 4 and 6 (rs = 0.65, p < 0.001). A strong negative correlation was observed between the TORS index and the masseter muscle symmetry index during the “Maximal voluntary clenching of the dental arches” test: groups 7 and 8 (rs = -0.7, p < 0.001), groups 8 and 9 (rs = -0.67, p < 0.001), groups 4 and 6 (rs = -0.8, p < 0.001. Similarly, a strong negative correlation was found between the TORS index and the masseter muscle symmetry index in the "Maximal Voluntary Clenching on cotton Rolls" test. Further analysis revealed a positive correlation between the TORS indices of the "Maximal Voluntary Dental Arch Clenching" and “Maximal voluntary clenching on cotton rolls” tests.Conclusion. This study established that the strongest correlations occurred between parameters recorded within the same test. In the “Physiological rest” test, the TORS index was influenced by the symmetrical activity of both the temporal and masseter muscles within the same test. Variations in the TORS index during the “Habitual occlusion” test were predominantly driven by the temporal muscle symmetry index, indicating a symmetrical distribution of bioelectrical activity between the left and right temporal muscles. In static tests involving maximal masticatory muscle contraction, the symmetry index of the masseter muscles strongly influenced the occurrence of torsional (lateral) mandibular movements, both in the "Maximal Voluntary Dental Arch Clenching" test and the “Maximal voluntary clenching on cotton rolls” test.

Impact of backpack load during walking: an EMG and biomechanical analysis.

This study aims to understand the impact of backpack carriage, a regular activity for many, on back muscles and joint mobility during walking so that clinicians can develop strategies or products to ensure individuals' safety and well-being. Surface electromyography (EMG) and XSENS Awinda motion capture systems were used to analyze the effects of carrying a backpack (12% of body weight) on erector spinae and multifidus muscles, as well as spinal, hip, knee, and ankle joints. Subjects walked at 4km/h on flat and inclined surfaces. Paired t-tests compared backpack loads to baseline measurements. Carrying a backpack reduced activation levels in erector spinae and multifidus muscles and restricted spinal joint range of motion (axial and lateral bending, ). Hip joint rotation increased ( ). Moderate to strong correlations were observed between muscle activity and spinal joint ROM, notably with left erector spinae and L5-S1 lateral bending ( ). Backpack carriage decreases back muscle activation and alters the joint range of motion. Asymmetric correlations show that the subjects adapt muscle activity and gait patterns asymmetrically to manage external loads.

Effect of fatigue on neuromuscular and biomechanical variables after anterior cruciate ligament reconstruction: a systematic review.

This systematic review is aimed to evaluate the outcomes of published studies on the topic of fatigue-induced neuromuscular and biomechanical changes after anterior cruciate ligament (ACL) reconstruction. The identification of studies involved a search across three databases - PubMed, Scopus, and Sportdiscus - until July 2023. The key terms utilized were fatigue, anterior cruciate ligament, biomechanics, electromyography, and landing. Included in the analysis were studies that examined the impact of fatigue on neuromuscular or biomechanical variables in individuals with ACLR, with comparisons drawn to either the contralateral side or healthy controls. Fourteen studies, involving 396 athletes (245 males, 151 females; mean age 23.43 years) met the inclusion criteria. Among these studies, eleven employed general fatigue protocols, and three used peripheral protocols. The tasks varied across the studies, including single-leg landing tasks, maximum voluntary isometric contraction tests, forward jump, and squat. Despite differing tasks, the findings regarding the impact of fatigue on lower limb kinematics, kinetics, and surface electromyography muscle activation patterns were inconsistent. However, in the majority of cases, the response to fatigue was similar between individuals who had undergone ACL reconstruction (ACLR) and healthy. The main finding of this systematic review was that fatigue changed things sometimes, however, fatigue did not change biomechanics and activity patterns differently in patients after ACLR vs. controls. General fatigue protocols did not produce enough stimulation to show deference between ACLRs and controls. Future studies should focus on different fatigue protocols (such as sport-specific protocols) and more challenging landing tasks.

Selective direct motor cortical influence during naturalistic climbing in mice.

It remains poorly resolved when and how motor cortical output directly influences limb muscle activity through descending projections, which impedes mechanistic understanding of cortical movement control. Here we addressed this in mice performing an ethologically inspired all-limb climbing behavior. We quantified the direct influence of forelimb primary motor cortex (caudal forelimb area, CFA) on muscle activity across the muscle activity states that occur during climbing. We found that CFA instructs muscle activity pattern, mainly by selectively activating certain muscles while exerting much smaller, bidirectional effects on their antagonists. From Neuropixel recordings, we identified linear combinations (components) of motor cortical activity that covary with these effects, finding that these components differ partially from those that covary with muscle activity and differ almost completely from those that covary with kinematics. Collectively, our results reveal an instructive direct motor cortical influence on limb muscles that is selective within a motor behavior and reliant on a distinct neural activity subspace.

The use of deep learning in intelligent athlete motion recognition: Integrating biological mechanisms

This work explores the effective application of deep learning for recognizing athletes’ movements, aiming to enhance precision in competitive sports. Traditional motion analysis methods primarily rely on manual observation, which can introduce subjective bias and limit accuracy. To address these limitations, we propose an automated method based on deep learning for recognizing and classifying athletes’ technical movements while evaluating their performance. A hybrid model, combining Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks, is utilized to extract key frames from video data. The CNN is responsible for feature extraction, capturing the intricate details of movement, while the LSTM captures the temporal sequence characteristics, providing context to the actions. To further strengthen our approach, we delve into the biological mechanisms underlying athletic movements. Understanding the biomechanics of motion—such as joint angles, muscle activation patterns, and energy expenditure—can enhance the accuracy of deep learning models. By integrating these biological insights into our model, we improve the recognition process, allowing for a more nuanced understanding of how movements impact performance. Through experiments, we demonstrate that the model achieves high accuracy across multiple benchmark datasets (UCF-101, HMDB-51, Kinetics-400, and Sports-1M), with a particularly high accuracy of 93.5% on the UCF-101 dataset. These results indicate that the proposed method is both accurate and reliable, making it suitable for athlete training and competition analysis. The findings of this research have significant implications for sports science, training evaluation, and injury prevention. By providing coaches and athletes with precise feedback based on deep learning analysis, we can facilitate targeted training interventions that enhance performance while reducing injury risks. This work aims to offer a powerful tool for athletes, coaches, and researchers, contributing to the advancement of competitive sports through a deeper understanding of movement dynamics and their biological underpinnings.

Neural Network for Enhancing Robot-Assisted Rehabilitation: A Systematic Review

The integration of neural networks into robotic exoskeletons for physical rehabilitation has become popular due to their ability to interpret complex physiological signals. Surface electromyography (sEMG), electromyography (EMG), electroencephalography (EEG), and other physiological signals enable communication between the human body and robotic systems. Utilizing physiological signals for communicating with robots plays a crucial role in robot-assisted neurorehabilitation. This systematic review synthesizes 44 peer-reviewed studies, exploring how neural networks can improve exoskeleton robot-assisted rehabilitation for individuals with impaired upper limbs. By categorizing the studies based on robot-assisted joints, sensor systems, and control methodologies, we offer a comprehensive overview of neural network applications in this field. Our findings demonstrate that neural networks, such as Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM), Radial Basis Function Neural Networks (RBFNNs), and other forms of neural networks significantly contribute to patient-specific rehabilitation by enabling adaptive learning and personalized therapy. CNNs improve motion intention estimation and control accuracy, while LSTM networks capture temporal muscle activity patterns for real-time rehabilitation. RBFNNs improve human–robot interaction by adapting to individual movement patterns, leading to more personalized and efficient therapy. This review highlights the potential of neural networks to revolutionize upper limb rehabilitation, improving motor recovery and patient outcomes in both clinical and home-based settings. It also recommends the future direction of customizing existing neural networks for robot-assisted rehabilitation applications.

Spatially ordered recruitment of fast muscles in accordance with movement strengths in larval zebrafish

In vertebrates, skeletal muscle comprises fast and slow fibers. Slow and fast muscle cells in fish are spatially segregated; slow muscle cells are located only in a superficial region, and comprise a small fraction of the total muscle cell mass. Slow muscles support low-speed, low-force movements, while fast muscles are responsible for high-speed, high-force movements. However, speed and strength of movement are not binary states, but rather fall on a continuum. This raises the question of whether any recruitment patterns exist within fast muscles, which constitute the majority of muscle cell mass. In the present study, we investigated activation patterns of trunk fast muscles during movements of varying speeds and strengths using larval zebrafish. We employed two complementary methods: calcium imaging and electrophysiology. The results obtained from both methods supported the conclusion that there are spatially-ordered recruitment patterns in fast muscle cells. During weaker/slower movements, only the lateral portion of fast muscle cells is recruited. As the speed or strength of the movements increases, more fast muscle cells are recruited in a spatially-ordered manner, progressively from lateral to medial. We also conducted anatomical studies to examine muscle fiber size. The results of those experiments indicated that muscle fiber size increases systematically from lateral to medial. Therefore, the spatially ordered recruitment of fast muscle fibers, progressing from lateral to medial, correlates with an increase in fiber size. These findings provide significant insights into the organization and function of fast muscles in larval zebrafish, illustrating how spatial recruitment and fiber size interact to optimize movement performance.

Gait pattern differences in unilaterally affected children with cerebral palsy and children with acquired brain insult.

Children with cerebral palsy (CP) or acquired brain insult (ABI) present with motor disorders affecting movement, muscle tone, and posture. While CP is commonly a consequence of perinatal brain insult (PBI), pediatric ABI can occur between birth and adolescence, with movement patterns that may not be consistent with CP. Are gait patterns associated with CP different from those with pediatric ABI? Children with unilateral motor impairment and history of ABI at ≥18 months of age were identified from gait lab records and matched with children with CP having a history of PBI at ≤ 1 year old. Matching was by GMFM-D, age at Instrumented Gait Analysis (IGA), and sex. Kinematic and temporospatial data from the earliest IGA were analyzed. The primary outcome measurement was average knee flexion in stance, as children with CP tend to walk with a more flexed knee and individuals with a brain insult as older children, youth and adults tend to walk with a more extended knee. Secondary variables were temporospatial parameters and lower limb kinematics in stance and swing. Wilcoxon or T-Tests were used. Twenty-six unilaterally affected children with CP (age: 10.8±3.3 years; f:6/m:20; GMFCS I:14, II:38), and 26 unilateral children with ABI (age:11.1±4.3 years; f:6/m:20) were included in each group. Significantly lower knee flexion angles during stance and swing, and shorter single support duration on the affected side were found in the ABI group as compared to CP (p<0.05). In children with ABI, there was a negative correlation between age of insult and severity of internal hip rotation (p<0.05). Children with ABI tend to walk with less stability on the affected side as reflected by the more extended knee and reduced single support compared with children with CP. The age at which the brain insult occurs has a significant effect on the hip rotational profile in children with ABI. Further studies on muscle activation patterns, kinetic data and response to treatment are warranted to gain insight on how the stage of brain and musculoskeletal system development at the time of injury affect gait patterns.

Gluteus medius muscle activation patterns during gait with Cerebral Palsy (CP): A hierarchical clustering analysis.

Duchenne gait, characterized by an ipsilateral trunk lean towards the affected stance limb, compensates for weak hip abductor muscles, notably the gluteus medius (GM). This study aims to investigate how electromyographic (EMG) cluster analysis of GM contributes to a better understanding of Duchenne gait in patients with cerebral palsy (CP). We analyzed retrospective gait data from 845 patients with CP and 65 typically developed individuals. EMG activity of GM in envelope format were collected and examined with gait kinematics and kinetics parameters in frontal plane and hip abductor strength, and hip abduction passive range of motion. Six key EMG envelope features during ten gait phases were extracted and normalized. A hybrid K-means-PSO clustering algorithm was employed, followed by hierarchical clustering. The identified clusters were characterized by having a low (cluster_1), medium (cluster_2), and high (cluster_3) activity of GM during loading response. The patients in cluster_1 also exhibited pathological gait characteristics, including increased trunk lateral lean and weak hip abductor, which are associated with Duchenne gait. The patients in this cluster were subclustered according to their response to the intervention: SUB_1 with a significant improvement in trunk obliquity, pelvic obliquity, and hip abduction after intervention, and SUB_2 without such improvement. Comparing pre-treatment EMG and clinical exam of the sub_clusters, SUB_1 had significantly higher activity of GM during 50-87% of the gait cycle with a greater passive range of hip abduction compared to SUB_2. This study established a relationship between EMG of GM and frontal plane gait abnormalities in patients with CP, highlighting potential improvement in Duchenne gait with prolonged GM activity during swing after the intervention.

Electromyogram in Fine Motor Training Assessment: A Review

Fine motor skills are essential for daily activities, especially those requiring precision, such as grasping objects or writing. This review explores the role of electromyography (EMG), particularly surface EMG (sEMG), in assessing fine motor skills across various populations, including typically developing children, children with motor disabilities, young adults, and elders. These groups were selected due to their unique challenges and needs in motor skill development and rehabilitation. For instance, young children may require early intervention to address developmental delays, while individuals with motor disabilities, such as those with autism or cerebral palsy, benefit from tailored therapeutic approaches. The elderly population faces age-related motor decline, making EMG a valuable tool for maintaining or improving muscle function in this group. By capturing muscle activation patterns, EMG provides a comprehensive evaluation of muscle engagement during fine motor tasks. The paper also reviews the effectiveness of digital platforms and 3D-printed toys in fine motor training, demonstrating the potential of EMG as a tool for enhancing therapeutic interventions and refining motor assessments. Emerging technologies such as artificial intelligence and machine learning may further optimize EMG signal analysis, offering innovative solutions for both clinical and home-based motor skill training.

Effects of traditional Chinese medicine massage therapy on pain, functional activity, muscle activation patterns and proprioception in knee osteoarthritis: a randomised controlled trial protocol

IntroductionHealth education, weight control and exercise therapy are recognised treatment options for the non-surgical management of knee osteoarthritis (KOA); however, the pain and muscle fatigue associated with exercise make it...

The impact of lymphedema severity on shoulder joint function and muscle activation patterns in breast cancer survivors: a cross-sectional study

PurposeThis study aimed to investigate the impacts of breast cancer-related lymphedema (BCRL) severity on shoulder function including range of motion, strength, muscle activation patterns, and patient-reported disability.MethodsA cross-sectional, observational study design was utilized. Seventy-five women with unilateral BCRL were recruited and categorized into mild, moderate, and severe groups based on limb swelling severity. Outcomes included shoulder range of motion, isometric strength, Disabilities of Arm Shoulder and Hand (DASH) scores for disability, and surface electromyography (EMG) of shoulder muscles. Data were analyzed using parametric and nonparametric tests.ResultsIncreasing lymphedema severity was associated with progressive declines in shoulder mobility, strength, and function. Severe cases showed markedly reduced shoulder flexion, abduction, rotation, and extension range of motion along with decreased isometric flexor and abductor strength versus mild cases (p < 0.001). Higher pain levels (p < 0.001) and DASH disability scores (p < 0.001) were noted in severe BCRL. Surface EMG revealed impaired activation patterns including reduced amplitudes (p < 0.001) and delayed onsets (p < 0.001) in the deltoids, rotator cuff, and scapular muscles with greater impairment.ConclusionsAdvancing BCRL severity was associated with substantial declines in shoulder mobility, strength, neuromuscular activation, pain threshold, and upper limb functionality. These quantitative results demonstrate impaired shoulder joint control underlying disability in arm elevation and daily tasks. The progressive nature of these deficits highlights the relationship between lymphedema severity and shoulder dysfunction in breast cancer survivors.

How Does Induced Deceleration of One Treadmill’s Belt in the Pre-Swing Gait Phase Change Gait Pattern?

This study aimed to investigate how external perturbations caused by the treadmill belt’s deceleration during the pre-swing phase affect gait kinematics and kinetics in young adults. Twenty-one healthy young females walked on a treadmill in a virtual environment (GRAIL, Motek), where unexpected perturbations were applied to the left belt, mimicking a ‘trip-like’ effect at toe-off. The spatiotemporal, kinematic, and kinetic parameters were analyzed during two cycles. The first cycle involved the first perturbation and the response to it. The second included a gait cycle without the perturbation (treadmill gait). The perturbation resulted in an increased stride duration for both limbs when compared to the treadmill gait. The perturbed limb had a longer support phase, while the reactive limb had the longest double stance phase. The responding limb exhibited more than double the ankle plantarflexion compared to the normal treadmill gait and the perturbed limb. At the hip joint, both limbs showed significantly higher values, with a 40.8% increase in flexion and a 227% increase in extension for the perturbed limb, and a 24.5% increase in flexion and a 212% increase in extension for the responding limb, compared to the treadmill gait. Muscle torque was generally lower in most joints for both limbs, except for notably higher hip and knee extensor values for the perturbed limb. The responding limb exhibited lower values for the ankle, knee, and hip joints, indicating unexpected muscle activity patterns. Studying treadmill belt deceleration during pre-swing gait can provide valuable insights into biomechanical adaptations and motor control strategies.

Estimating descending activation patterns from EMG in fast and slow movements using a model of the stretch reflex.

Due to spinal reflex loops, descending activation from the brain is not the only source of muscle activation that ultimately generates movement. This study directly estimates descending activation patterns from measured patterns of muscle activation (EMG) during human arm movements. A simple model of the spinal stretch reflex is calibrated in a postural unloading task and then used to estimate descending activation patterns from muscle EMG patterns and kinematics during voluntary arm motion performed at different speeds. We observed three key features of the estimated descending activation patterns: (1) Within about the first 15% of movement duration, descending and muscle activations are temporally aligned. Thereafter, they diverge and develop qualitatively different temporal profiles. (2) The time course of descending activation is monotonic for slow movements, non-monotonic for fast movements. (3) Varying model parameters like the spinal reflex gain or the level of co-contraction does not qualitatively change the temporal pattern of estimated descending activation. Our findings highlight the substantial contribution of spinal reflex loops to movement generation, while at the same time providing evidence that the brain must generate qualitatively different descending activation patterns for movements that vary in their mechanical dynamics.

Assessment of Muscle Synergies in Chronic Ankle Instability Patients During Unanticipated and Anticipated Landing.

Ankle sprains are a common injury among athletes and the general population, with chronic ankle instability (CAI) being a frequent complication. CAI patients often display altered neuromuscular control adaptations. This study analyzed muscle synergy patterns in 20 CAI patients during anticipated and unanticipated landing tasks to understand their neuromuscular adaptation strategies. Using Nesterov non-negative matrix factorization and K-means clustering, the study identified distinct muscle activation patterns. Results indicated that during unanticipated landings, the gluteus maximus and vastus lateralis showed increased activation weight, while the medial gastrocnemius was more active in anticipated landings. This study highlights that CAI patients display unique muscle synergy patterns during unanticipated landings, relying more on proximal muscles such as the gluteus maximus and vastus lateralis. This adaptation reflects the proximal muscle strategy to enhance stability and compensate for impaired ankle function in unpredictable situations.

Enhancing ergonomics in E-waste disassembly: the impact of collaborative robotics on muscle activation and coordination

Disassembly, as a part of the electronic waste (e-waste) management process, is a labour-intensive task. The emergence of collaborative robots (cobots) provides a robotic solution to reduce the human efforts during disassembly. This study evaluated muscle activation patterns during cobot-assisted e-waste disassembly using surface electromyography (EMG). Twenty-two participants were recruited to perform disassembly tasks with and without cobot assistance. EMG signals from biceps brachii (BB), brachioradialis (BR), upper trapezius (UT), and erector spinae (ES) were collected simultaneously. Six features were then calculated to determine muscle activation patterns. Additionally, EMG-EMG coherence analysis was conducted for BR and ES muscles. Results showed a significant reduction in muscle activity with cobot assistance, particularly in the left ES muscle (46.4% decrease). Moreover, coherence between BR and ES muscles significantly increased. These findings indicate the proposed collaboration strategy not only reduces the muscle activity but also sheds light on enhancing muscle coordination during e-waste disassembly.

Exploring the Relationship Between Foot Position and Reduced Risk of Knee-Related Injuries in Side-Cutting Movements

Background: Knee-related injuries often result from poor movement patterns that destabilize the joint and increase stress on knee structures. Understanding the influence of foot positioning on knee biomechanics is critical for identifying high-risk movement patterns and preventing injuries. Methods: Twenty healthy male participants performed side-cutting movements at three different foot progression angles. One participant’s data were used to develop and validate a knee finite element model with high-speed dual fluoroscopic imaging (DFIS). Combined with a musculoskeletal analysis, the model simulated internal knee loads under various foot-positioning conditions. Results: The analysis revealed that, as the external foot progression angle increased, the ankle plantarflexion decreased, while the ankle internal rotation and knee valgus moments increased. Higher stress concentrations were observed on the ACL, lateral meniscus, lateral tibial cartilage, and medial collateral ligament, particularly at the femoral–tibial ACL attachments. Conclusion: The findings suggest that a toe-out foot position elevates the risk of knee injuries by increasing stress on key structures, whereas a toe-in position may enhance joint stability, reduce the ACL injury risk, and promote favorable muscle activation patterns.

Predicting Upper body Muscle Activation Patterns in Paralympic Cross-Country Skiing Using Neural Networks and Accelerometer Data

Abstract Paralympic cross-country skiing is a competitive and physically demanding sport developed for individuals with physical disabilities. In addition to good training and endurance, sports equipment is a key factor in achieving success. The design of sports equipment must be customized to accommodate specific impairments. Furthermore, biomechanical and neurophysiological factors need to be considered when designing equipment such as ski sledges. Among other neurophysiological factors, muscle activity, typically measured using electromyography (EMG), plays a crucial role. However, due to the high level of dynamic movement in the sport, EMG measurements are not always feasible. This study explores the possibility of estimating EMG data using neural networks and acceleration data. A feedforward neural network model was created and trained to predict upper body muscle activation from acceleration data. Validation of the model using statistical metrics yielded promising results, suggesting its effective use in predicting muscle activity. This research sets the stage for enhancing understanding and optimizing equipment in Paralympic cross-country skiing, ultimately enhancing the performance of para-athletes.

Comparison of Writing Speed, Letter Size, and Upper Extremity Muscle Activation in Stroke Patients Using Two Writing Aids: Evaluation with the Jebsen–Taylor Hand Function Test

Currently, writing aids for upper extremity rehabilitation in stroke patients are not developed with consideration of biomechanical characteristics, making it difficult to achieve proper support effects. Therefore, in this study, we conducted a comparative analysis to examine how the use of two types of writing aids affects writing speed, letter size, and upper extremity muscle activation based on hand function and electromyography assessments in 12 stroke patients. Hand function was assessed using the Jebsen–Taylor hand function test, while writing ability (writing speed and letter size) was measured using the Korean alphabet writing test. Muscle activity was recorded using surface electromyography from both the paralyzed side (PS) and nonparalyzed side (NPS). The results showed that writing speed was significantly slower and horizontal letter sizes were larger on the PS. Additionally, muscle activation patterns on the PS were significantly influenced by the design of the writing aids, suggesting that the aids’ design affects compensatory movements and muscle function. These findings emphasize the importance of personalized rehabilitation tools that cater to the individual needs of stroke patients. Future research will focus on developing customized writing aids based on biomechanical data to better support rehabilitation goals.