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Low back pain (LBP) is a highly prevalent disease. Among the various causes of LBP, one of the most frequent is myofascial pain syndrome (MPS) which affects the spinal stabilizer muscles. The aims of this study were to compare the differences in muscular electrical activity and biomechanical properties between the painful and non-painful sides in patients with unilateral MPS and to verify the feasibility of surface electromyography (sEMG) and MyotonPRO for assisting in MPS assessment. Forty patients with unilateral lumbar MPS were recruited via the Department of Rehabilitation Medicine Center of West China Hospital Sichuan University from October 2022 to October 2023. The electrical properties of the bilateral erector spinae muscles were characterized by sEMG signals during a trunk extension task. The following four time-domain features of sEMG were extracted: root mean square (RMS), mean absolute value (MAV), integrated EMG (iEMG), and waveform length (WL). And two frequency domain features were extracted: the median frequency (MDF) and mean power frequency (MPF). The mechanical properties of the muscles were assessed by MyotonPRO at rest. The following biomechanical parameters were acquired: oscillation frequency [Hz], dynamic stiffness [N/m], logarithmic decrement, relaxation time [ms], and Creep. The visual analog scale (VAS) was used to evaluate the pain severity, and the Oswestry Disability Index (ODI) was used to evaluate the severity of disability and disruption to lifestyle activities caused by LBP pain. The outcome measures were obtained prior to the Platelet-rich plasma (PRP) treatment and repeated two weeks after treatment. (1) Prior to the PRP treatment, all sEMG time-domain features on the painful side were significantly higher than those on the non-painful side (RMS, p < 0.001; MAV, p < 0.001; iEMG, p < 0.001; WL, p = 0.001). However, there was no significant difference in the sEMG frequency-domain features (MPF, p = 0.478; MDF, p = 0.758). On the mechanical side, there were significant differences in oscillation frequency (p = 0.041) and logarithmic decrement (p = 0.022) between the painful side and non-painful side, but no significant differences in dynamic stiffness, relaxation time, and creep (both p > 0.05). (2) Two weeks after the PRP treatment, statistically significant decreases were observed in both post-treatment VAS (p < 0.001) and ODI scales (p < 0.001), indicating the PRP treatment clinically significantly reduced the level of. MPS. This change coincided with all sEMG time-domain features, in which the values at the painful side decreased significantly (RMS, p = 0.001; MAV, p = 0.001; iEMG, p = 0.001; WL, p = 0.001). However, no significant difference in the sEMG frequency-domain features (MPF, p = 0.620; MDF, p = 0.850) was found. On the mechanical side, only logarithmic decrement on the painful side increased significantly (p < 0.001). Our combined MyotonPRO and sEMG results indicated that MPS likely leads to increased muscle tone and decreased muscle elasticity, manifested by abnormal time-domain features of sEMG and biomechanical properties. The changes in these objective measurements were agreed with the changes in subjective outcome measures of pain and function currently assessed in the patients with MPS. A single PRP treatment may alleviate muscle dysfunction caused by MPS. These preliminary results demonstrated the potential feasibility of using sEMG and MyotonPRO as tools for assessing the neuromuscular function of MPS.

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OBJECTIVE: Accurate prediction of unmearsured muscle excitations can reduce the required wearable surface electromyography (sEMG) sensors, which is a critical factor in the study of physiological measurement. Synergy extrapolation uses synergy excitations as building blocks to reconstruct muscle excitations. However, the practical application of synergy extrapolation is still limited as the extrapolation process utilizes unmeasured muscle excitations it seeks to reconstruct. This paper aims to propose and derive methods to provide an avenue for the practical application of synergy extrapolation with non-negative matrix factorization (NMF) methods. APPROACH: Specifically, a tunable Gaussian-Laplacian mixture distribution NMF (GLD-NMF) method and related multiplicative update rules are derived to yield appropriate synergy excitations for extrapolation. Furthermore, a template-based extrapolation structure (TBES) is proposed to extrapolate unmeasured muscle excitations based on synergy weighting matrix templates totally extracted from measured sEMG datasets, improving the extrapolation performance. Moreover, we applied the proposed GLD-NMF method and TBES to selected muscle excitations acquired from a series of single-leg stance (SLS) tests, walking tests and upper limb reaching tests. MAIN RESULTS: Experimental results show that the proposed GLD-NMF and TBES could extrapolate unmeasured muscle excitations accurately. Moreover, introducing synergy weighting matrix templates could decrease the number of sEMG sensors in a series of experiments. In addition, verification results demonstrate the feasibility of applying synergy extrapolation with NMF methods. SIGNIFICANCE: With the TBES method, synergy extrapolation could play a significant role in reducing data dimensions of sEMG sensors, which will improve the portability of sEMG sensors-based systems and promotes applications of sEMG signals in human-machine interfaces scenarios.

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We examined the effect of prolonged tennis playing on lower limb muscles' activity during the execution of first and second tennis serves. Ten male competitive tennis players executed five first and second serves before (pretest) and after (posttest) a 3-h tennis match. Surface electromyographic (EMG) activity of four lower limb muscles (vastus lateralis, rectus femoris, gastrocnemius lateralis, and soleus muscles) on each leg was recorded along with maximum ball velocity measured by a radar gun and peak vertical forces recorded by a force platform. For the vastus lateralis, gastrocnemius lateralis, and soleus muscles of the left leg as well as the vastus lateralis muscle of the right leg, EMG amplitude decreased from pre- to posttests (p ≤ 0.033). These reductions in the EMG signal were generally more pronounced in the first serve (i.e., ranging from -10% to -40%) compared to the second serve (0% to -25%). Maximum ball velocity for both first (159 ± 12 vs. 154 ± 12 km/h) and second (126 ± 20 vs. 125 ± 15 km/h) serves remained unchanged from pre- to posttests (p = 0.638) Similarly, peak vertical forces did not differ between pretest and posttest for both first (1.78 ± 0.30 vs. 1.72 ± 0.29 body weight) and second (1.62 ± 0.25 vs. 1.75 ± 0.23 body weight) serves (p = 0.730). In conclusion, a 3-h tennis match led to decreased activation levels in various leg muscles during serves, particularly in first serves compared to second serves. Despite consistent maximum ball velocity and peak vertical forces, these reductions in EMG signals suggest that skilled tennis players may adopt compensatory strategies after prolonged play.

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BACKGROUND: Swallowing is a complex function that requires precise coordination between different muscles. Weakness in submental muscles can lead to complications such as pharyngeal residue and aspiration. Therefore, exercise interventions targeting these muscles, such as the Head-Lift Exercise (HLE), are clinically important but pose challenges. OBJECTIVE(S): This study aimed to compare the myoelectric activity of submental muscles during traditional Head-Lift Exercise (HLE), Tongue-Press Exercise (TPE) and Head Extension Tongue-Press Exercise (HETPE), providing potential alternatives to HLE. METHODS: Thirty healthy volunteers (22 females and 8 males, mean age 25.63 ± 5.27 years) participated in this cross-sectional study. Surface electromyography (sEMG) recorded activity of the submental muscles bilaterally during HLE, TPE and HETPE. Participants performed each manoeuvre for 14 s, repeated three times in a counterbalanced order. Statistical analyses assessed differences in mean, maximum and median frequency of the sEMG signals among manoeuvres using repeated-measures analysis of variance (RM-ANOVA). The experienced irritation levels by participants during manoeuvres were also compared by the Friedman test. RESULTS: HETPE exhibited significantly higher maximum sEMG activity compared to HLE and TPE (p < .05). Mean sEMG activity was significantly increased during HETPE compared to TPE. Median frequency was significantly lower during HETPE compared to the two other exercises, indicating greater muscle fatigue. Participants reported similar levels of irritation for HLE and HETPE, and significantly lower levels during TPE. CONCLUSION: These results indicate that HETPE is effective in activating and strengthening submental muscles, potentially serving as a viable alternative to HLE without added difficulty. Further research is recommended to assess the long-term impacts on swallowing physiology in patients with dysphagia.

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Surface electromyography (sEMG) offers a novel method in human-machine interactions (HMIs) since it is a distinct physiological electrical signal that conceals human movement intention and muscle information. Unfortunately, the nonlinear and non-smooth features of sEMG signals often make joint angle estimation difficult. This paper proposes a joint angle prediction model for the continuous estimation of wrist motion angle changes based on sEMG signals. The proposed model combines a temporal convolutional network (TCN) with a long short-term memory (LSTM) network, where the TCN can sense local information and mine the deeper information of the sEMG signals, while LSTM, with its excellent temporal memory capability, can make up for the lack of the ability of the TCN to capture the long-term dependence of the sEMG signals, resulting in a better prediction. We validated the proposed method in the publicly available Ninapro DB1 dataset by selecting the first eight subjects and picking three types of wrist-dependent movements: wrist flexion (WF), wrist ulnar deviation (WUD), and wrist extension and closed hand (WECH). Finally, the proposed TCN-LSTM model was compared with the TCN and LSTM models. The proposed TCN-LSTM outperformed the TCN and LSTM models in terms of the root mean square error (RMSE) and average coefficient of determination (R2). The TCN-LSTM model achieved an average RMSE of 0.064, representing a 41% reduction compared to the TCN model and a 52% reduction compared to the LSTM model. The TCN-LSTM also achieved an average R2 of 0.93, indicating an 11% improvement over the TCN model and an 18% improvement over the LSTM model.

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Elite athletes in speed roller skates perceive skating to be a more demanding exercise for the groin when compared to other cyclic disciplines, increasing their risk of injury. The objective of this study was to monitor the kinematic and electromyographic parameters of roller speed skaters, linearly, on a treadmill, and to compare different skating speeds, one at 20 km/h and one at 32 km/h, at a 1° inclination. The acquisition was carried out by placing an inertial sensor at the level of the first sacral vertebra, and eight surface electromyographic probes on both lower limbs. The kinematic and electromyographic analysis on the treadmill showed that a higher speed requires more muscle activation, in terms of maximum and average values and co-activation, as it not only increases the intrinsic muscle demand in the district, but also the athlete's ability to coordinate the skating technique. The present study allows us to indicate not only how individual muscle districts are activated during skating on a surface different from the road, but also how different speeds affect the overall district load distributions concerning effective force, which is essential for the physiotherapist and kinesiologist for preventive and conditional purposes, while also considering possible variations in the skating technique in linear advancement.

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Extreme postures and imbalances in neuromuscular activity may place classical ballet dancers at higher risk of injury. Dance studio mirrors provide visual feedback by which a dancer can self-correct their body position and alignment, but have been suggested to negatively impact kinesthetic abilities and decrease performance capabilities. Thus, we investigated the effects of a mirror on muscle activity of the quadriceps, heart rate (HR), rating of perceived exertion (RPE), and qualitative performance. A lack of visual feedback would increase muscle activity of the quadriceps, HR, and RPE, and decrease self-reported perception of technical quality. 10 female participants completed a single leg balance, an adagio, and a jump task twice - once in each condition. Muscle activity of the vastus lateralis (VL) and vastus medialis oblique (VMO), as well as HR and RPE were assessed during each combination. Qualitative performance was assessed with an exit survey. No significant differences were found between conditions for RPE or HR in all three tasks (RPE: Balance p = 0.468, Adagio p = 0.191, Jumps p = 0.769; HR: Balance p = 0.409, Adagio p = 0.424, Jumps p = 0.244). No significant differences were found between conditions/tasks for peak, mean, and RMS sEMG. Dancers significantly ranked their artistic expression lower in a non-mirror condition (p = 0.018, Cohen's d = 0.775). No differences in muscle activity of the VMO and VL or vital signs of fatigue were found. Psychological implications of visual feedback, including dancer's perceived decrease in artistic expression without a mirror present, should be further explored in future studies.

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In this paper, we propose an artificial intelligence (AI)-based sarcopenia diagnostic technique for stroke patients utilizing bio-signals from the neuromuscular system. Handgrip, skeletal muscle mass index, and gait speed are prerequisite components for sarcopenia diagnoses. However, measurement of these parameters is often challenging for most hemiplegic stroke patients. For these reasons, there is an imperative need to develop a sarcopenia diagnostic technique that requires minimal volitional participation but nevertheless still assesses the muscle changes related to sarcopenia. The proposed AI diagnostic technique collects motor unit responses from stroke patients in a resting state via stimulated muscle contraction signals (SMCSs) recorded from surface electromyography while applying electrical stimulation to the muscle. For this study, we extracted features from SMCS collected from stroke patients and trained our AI model for sarcopenia diagnosis. We validated the performance of the trained AI models for each gender against other diagnostic parameters. The accuracy of the AI sarcopenia model was 96%, and 95% for male and females, respectively. Through these results, we were able to provide preliminary proof that SMCS could be a potential surrogate biomarker to reflect sarcopenia in stroke patients.

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BACKGROUND: Knee osteoarthritis is a common degenerative joint disease where a single treatment method often fails to fully alleviate symptoms. Hence, finding effective non-invasive combined treatment approaches is particularly crucial. OBJECTIVE: The efficacy of treating knee osteoarthritis with hip abductors exercise training combined with repetitive transcranial magnetic stimulation was assessed through functional scales and objective evaluation methods. METHODS: In this four-week randomized clinical trial, 160 patients meeting inclusion criteria were randomly assigned 1:1 to group A to receive oral celecoxib and group B to receive a combination of hip abductors exercise training and repeated transcranial magnetic stimulation. The primary outcome was the western Ontario and McMaster universities osteoarthritis index. The secondary outcomes include Visual Analogue Scale, knee outcome survey activities of daily living scale, Active Range of Motion, and the Quadriceps Angle, the tibiofemoral angle, peak adductor moment, the integrated electromyography and root mean square of the surface electromyography of the lower extremity muscles. Paired sample t test was used for Within-Group comparison of outcome indicators, and independent sample t test was used for Between-Group comparison. RESULTS: Of the 160 randomly assigned patients, 150 completed the study. After 4 weeks, the WOMAC index decreased from 61 ± 10.83 to 40.55 ± 7.58 in the combined treatment group and from 60.97 ± 10.18 to 47.7 ± 10.13 in the celecoxib group. The effect of the combined treatment group was significantly higher than that in the celecoxib group (P< 0.001). In the combined treatment group, the score of knee joint daily living scale increased (P< 0.001), the active range of motion increased (P< 0.001), the quadriceps angle decreased (P< 0.001), the tibiofemoral angle increased (P< 0.001), and the peak adduction moment decreased (P< 0.001), integrated electromyography and root mean square increased (P< 0.001), and the effect was better than that of celecoxib group (P< 0.001). The visual analog scale score in celecoxib group was lower (P< 0.001) and knee outcome survey activities of daily living scale was higher (P< 0.001). The incidence of treatment-related adverse events was 10% in the celecoxib group and 2.5% in the combined treatment group, all of which were mild. CONCLUSIONS: Hip abductors exercise training combined with repetitive transcranial magnetic stimulation can enhance abduction muscle strength, improve mobility, reduce joint pain, and enhance quality of life. This combined approach shows superior clinical effectiveness compared to oral celecoxib.

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BACKGROUND: Preventing severe arthrogenic muscle inhibition (AMI) after knee injury is critical for better prognosis. The novel Sonnery-Cottet classification of AMI enables the evaluation of AMI severity but requires validation. This study aimed to investigate the electromyography (EMG) patterns of leg muscles in the examination position from the classification during isometric contraction to confirm its validity. We hypothesised that the AMI pattern, which is characterised by quadriceps inhibition and hamstring hypercontraction, would be detectable in the supine position during isometric contraction. METHODS: Patients with meniscal or knee ligament injuries were enrolled between August 2023 and May 2024. Surface EMG was assessed during submaximal voluntary isometric contractions (sMVIC) at 0° extension in the supine position for the vastus medialis (VM) and vastus lateralis (VL) muscles and at 20° flexion in the prone position for the semitendinosus (ST) and biceps femoris (BF) muscles. Reference values for normalisation were obtained from the EMG activity during the gait of the uninjured leg. The Kruskal-Wallis test was used to compare the activation patterns of the muscle groups within the same leg, and the post-hoc tests were conducted using the Mann-Whitney U test and Bonferroni correction. RESULTS: Electromyographic data of 40 patients with knee injuries were analyzed. During sMVIC, the extensor and flexor muscles of the injured leg showed distinct behaviours (P < 0.001), whereas the uninjured side did not (P = 0.144). In the injured leg, the VM differed significantly from the ST (P = 0.018), and the VL differed significantly from the ST and BF (P = 0.001 and P = 0.026, respectively). However, there were no statistically significant differences within the extensor muscle groups (VM and VL, P = 0.487) or flexor muscle groups (ST and BF, P = 0.377). CONCLUSION: AMI was detectable in the examination position suggested by the Sonnery-Cottet classification. The flexor and extensor muscles of the injured leg exhibited distinct activation behaviours, with inhibition predominantly occurring in the quadriceps muscles, whereas the hamstrings showed excitation.

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Facial expressions are important in pain recognition in horses, but current observation-based pain scales remain subjective. A promising technique to quantitatively measure subtle changes in expression patterns, including changes invisible to the human eye, is surface electromyography (sEMG). To achieve high-quality and reliable sEMG signals, unilateral placement of bipolar electrodes is required in relation to the motor endplates (MEP). We aimed to localize the nerve entry points (NEPs; where the nerve branch first pierced the muscle belly) and the direction of the terminal nerve endings to estimate MEP locations of the innervating nerves in five equine facial muscles involved in pain expression. Three cadaveric Dutch Warmblood horse heads were dissected to identify the NEPs in the musculi caninus, levator anguli oculi medialis, nasolabialis, masseter and zygomaticus. These points were marked with pins and measured in relation to a reference line between two anatomical landmarks near the origin and insertion of the respective muscle. Relative distances were calculated from the most caudally situated landmark. NEPs were located at 33%-38% (caninus), 69%-86% (levator anguli oculi medialis) and 0%-18% (zygomaticus) from the caudal landmark. The nasolabialis showed two innervations zones. Its NEPs were located at 47%-72% (dorsal muscle branch) and 52%-91% (ventral branch). All terminal nerve endings were found to run in rostral direction. The masseter showed numerous NEPs diffusely spread within the muscle belly. Therefore, calculation of relative positions was not performed. These results could form the basis for feasibility studies and standardization of bipolar electrode positioning in vivo to measure facial muscle activity patterns in horses.

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BACKGROUND: Myofascial tissue plays a critical role in shoulder joint mobility disorders. Myofascial release therapy (MFR) is frequently utilized to restore the extensibility of fascial tissue and is considered beneficial for various clinical conditions such as low back pain and ankle injuries. However, no studies have yet evaluated the effects of MFR on periscapular muscles activation and shoulder mobility in patients with subacromial pain syndrome(SAPS). OBJECTIVE: The purpose of this study was to compare the effectiveness of MFR combined with supervised exercise(SE) and SE alone in patients with SAPS. DESIGN: Assessor-blinded randomized controlled trial. SETTING: Sir Run Run Shaw Hospital, Zhejiang University School of Medicine. SUBJECTS: Subacromial pain syndrome patients. METHODS: Fifty participants were divided into two groups: SE group and MFR + SE group, each group 25 cases. Both treatment methods were performed 5 times a week for 4 weeks. MAIN MEASURES: Shoulder pain severity was assessed by visual analog scale (VAS); shoulder range of motion (ROM) by a goniometer; functionality by shoulder Pain and Disability Index (SPADI); and periscapular muscles activation by sEMG. All measurements were evaluated both pre- and post-treatment. RESULTS: An ANOVA analysis indicated no significant group by time interactions for flexion ROM and resting VAS (p > 0.05). However, significant group by time interactions were found for SPADI, abduction and external rotation ROM, and activity VAS (p < 0.05). Post-hoc tests revealed significant improvements in SPADI, abduction and external rotation ROM, and activity VAS in both groups compared to pre-treatment (p < 0.05). Additionally, there were significant group by time interactions for the sEMG values of the upper trapezius and serratus anterior (p < 0.05). Post-hoc tests showed that compared to pre-treatment, the MFR + SE group had decreased upper trapezius sEMG values and increased serratus anterior sEMG values(p < 0.05), while the SE group showed increased serratus anterior sEMG values(p < 0.05). After the 4-week intervention, there were significant between-group differences in SPADI, abduction and external rotation ROM, activity VAS, and sEMG values of the upper trapezius and serratus anterior(p < 0.05). CONCLUSION: Four weeks of MFR combined with SE can increase shoulder ROM, improve pain, and thus enhancing functional activities in patients with SAPS. Additionally, it can further improve the balance between the upper trapezius and serratus anterior to improve the dynamics of the periscapular muscles. TRIAL REGISTRY NUMBER: ChiCTR2200061054. Date of registration 15/06/2022.

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Background: Osteoarthritis (OA) is a highly prevalent global musculoskeletal disorder, and knee OA (KOA) accounts for four-fifths of the cases worldwide. It is a degenerative disorder that greatly affects the quality of life. Thus, it is managed through different methods, such as weight loss, physical therapy, and knee arthroplasty. Physical therapy aims to strengthen the knee periarticular muscles to improve joint stability. Methods: Pedobarographic data and pelvis and trunk motion of 56 adults are recorded. Among them, 28 subjects were healthy, and 28 subjects were suffering from varying degrees of KOA. Age, sex, BMI, and the recorded variables are used together to identify subjects with KOA using machine learning (ML) models, namely, logistic regression, SVM, decision tree, and random forest. Surface electromyography (sEMG) signals are also recorded bilaterally from two muscles, the rectus femoris and biceps femoris caput longus, bilaterally during various activities for two healthy and six KOA subjects. Cluster analysis is then performed using the principal components obtained from time-series features, frequency features, and time-frequency features. Results: KOA is successfully identified using the pedobarographic data and the pelvis and trunk motion with the highest accuracy and sensitivity of 89.3% and 85.7%, respectively, using a decision tree classifier. In addition, sEMG data have been successfully used to cluster healthy subjects from KOA subjects, with wavelet analysis features providing the best performance for the standing activity under different conditions. Conclusion: KOA is detected using gait variables not directly related to the knee, such as pedobarographic measurements and pelvis and trunk motion captured by pedobarography mats and wearable sensors, respectively. KOA subjects are also distinguished from healthy individuals through clustering analysis using sEMG data from knee periarticular muscles during walking and standing. Gait data and sEMG complement each other, aiding in KOA identification and rehabilitation monitoring. It is important because wearable sensors simplify data collection, require minimal sample preparation, and offer a non-radiographic, safe method suitable for both laboratory and real-world scenarios. The decision tree classifier, trained with stratified k-fold cross validation (SKCV) data, is observed to be the best for KOA identification using gait data.

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OBJECTIVES: Myofascial pain syndrome in the popliteus muscle may change motor control in the affected and related muscles due to changes in proprioceptive and nociceptive afferents, which can exacerbate patellofemoral pain syndrome. The primary purpose of the current study was to explore the electromyographic activity of the local and proximal muscles of the knee joint in patellofemoral pain syndrome accompanied by secondary myofascial pain syndrome specifically affecting the popliteus muscle following dry needling. METHODS: Myofascial pain syndrome in the popliteus muscle may change motor control in the affected and related muscles due to changes in proprioceptive and nociceptive afferents, which can exacerbate patellofemoral pain syndrome. The primary purpose of the current study was to explore the electromyographic activity of the local and proximal muscles of the knee joint in patellofemoral pain syndrome accompanied by secondary myofascial pain syndrome specifically affecting the popliteus muscle following dry needling. RESULTS: During step-up, the onset and offset latencies of the local and proximal muscles of the knee joint, except for the offset latency of the gluteus maximus muscle (p-value=0.162), significantly decreased in the intervention group compared to the control group (p-value<0.046). Additionally, there were no significant differences (p-value>0.116) between the groups in the amplitude ratio of the local and proximal muscles of the knee joint during both step-up and step-down. CONCLUSIONS: The present study revealed that dry needling of the popliteus muscle with secondary myofascial pain syndrome associated with patellofemoral pain syndrome constructively modified the local and proximal motor control of the knee joint during step-up.

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Surface electromyography (sEMG) is commonly used as an interface in human-machine interaction systems due to their high signal-to-noise ratio and easy acquisition. It can intuitively reflect motion intentions of users, thus is widely applied in gesture recognition systems. However, wearable sEMG-based gesture recognition systems are susceptible to changes in environmental noise, electrode placement, and physiological characteristics. This could result in significant performance degradation of the model in inter-session scenarios, bringing a poor experience to users. Currently, for noise from environmental changes and electrode shifting from wearing variety, numerous studies have proposed various data-augmentation methods and highly generalized networks to improve inter-session gesture recognition accuracy. However, few studies have considered the impact of individual physiological states. In this study, we assumed that user exercise could cause changes in muscle conditions, leading to variations in sEMG features and subsequently affecting the recognition accuracy of model. To verify our hypothesis, we collected sEMG data from 12 participants performing the same gesture tasks before and after exercise, and then used Linear Discriminant Analysis (LDA) for gesture classification. For the non-exercise group, the inter-session accuracy declined only by 2.86%, whereas that of the exercise group decreased by 13.53%. This finding proves that exercise is indeed a critical factor contributing to the decline in inter-session model performance.

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Tongue brushing improves respiratory function in older adults. Considering connection between the respiratory-related and suprahyoid muscles, this study aimed to investigate whether tongue-brushing interventions can improve myoelectric activity during respiration. A six-week randomized controlled trial was conducted in Kitakyushu, Japan, with 50 participants aged ≥ 65 years. The participants were allocated to the intervention (tongue brushing with routine oral hygiene) or control (routine oral hygiene alone) groups. Surface electromyography (sEMG) was used to assess the myoelectric activity of the suprahyoid muscles during inhalation, exhalation, and forced vital capacity (FVC). A survey was conducted at baseline and the end of the follow-up period. Thirty-six participants were recruited for the analysis. The root mean squares (RMS) of sEMG during exhalation increased significantly at the end of the follow-up period compared with that at baseline in the intervention group [48.7 (18.0-177.5) vs. 64.9 (21.6-163.0), p = 0.001], but not in the control group. The generalized linear model revealed that the ratio of change in FVC was correlated with the change in the RMS of sEMG of the suprahyoid muscles during exhalation after adjusting for potential confounders. Tongue brushing enhances the myoelectric activity of the suprahyoid muscle.

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Background: Chronic pelvic pain (CPP) in women is a critical challenge. Due to the complex etiology and difficulties in diagnosis, it has a greatly negative impact on women's physical and mental health and the healthcare system. At present, there is still a lack of research on the related factors and predictive models of chronic pelvic pain in women. Our study aims to identify risk factors associated with chronic pelvic pain in women and develop a predictive nomogram specifically tailored to high-risk women with CPP. Materials and methods: From May to October 2022, trained interviewers conducted face-to-face questionnaire surveys and pelvic floor surface electromyography assessments on women from community hospitals in Nanjing. We constructed a multivariate logistic regression-based predictive model using CPP-related factors to assess the risk of chronic pelvic pain and create a predictive nomogram. Both internal and external validations were conducted, affirming the model's performance through assessments of discrimination, calibration, and practical applicability using area under the curve, calibration plots, and decision curve analysis. Results: 1108 women were recruited in total (survey response rate:1108/1200), with 169 (15.3 %) being diagnosed as chronic pelvic pain. Factors contributing to CPP included weight, dysmenorrhea, sexual dysfunction, urinary incontinence, a history of pelvic inflammatory disease, and the surface electromyography value of post-baseline rest. In both the training and validation sets, the nomogram exhibited strong discrimination abilities with areas under the curve of 0.85 (95 % CI: 0.81-0.88) and 0.85 (95 % CI: 0.79-0.92), respectively. The examination of the decision curve and calibration plot showed that this model fit well and would be useful in clinical settings. Conclusions: Weight, dysmenorrhea, sexual dysfunction, history of urinary incontinence and pelvic inflammatory disease, and surface electromyography value of post-baseline rest are independent predictors of chronic pelvic pain. The nomogram developed in this study serves as a valuable and straightforward tool for predicting chronic pelvic pain in women.

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Taste sensation recognition is a core for taste-related queries. Most prior research has been devoted to recognizing the basic taste sensations using the Brain-Computer Interface (BCI), which includes EEG, MEG, EMG, and fMRI. This research aims to recognize electronic taste (E-Taste) sensations based on surface electromyography (sEMG). Silver electrodes with platinum plating of the E-Taste device were placed on the tongue's tip to stimulate various tastes and flavors. In contrast, the electrodes of the sEMG were placed on facial muscles to collect the data. The dataset was organized and preprocessed, and a random forest classifier was applied, giving a five-fold accuracy of 70.43%. The random forest classifier was used on each participant dataset individually and in groups, providing the highest accuracy of 84.79% for a single participant. Moreover, various feature combinations were extracted and acquired 72.56% accuracy after extracting eight features. For a future perspective, this research offers guidance for electronic taste recognition based on sEMG.

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Objective.To promote the development of objective and comprehensive motion function assessment for patients, based on high-density surface electromyography (HD-sEMG), this study investigates the temporal and spatial variations of neuromuscular activities related to upper limb motor dysfunction.Approach.Patients with unilateral upper limb motor dysfunction and healthy controls were enrolled in the study. HD-sEMG was collected from both arms while they were performing eight hand and wrist movements. Muscle synergies were extracted from the HD-sEMG. Symmetry of bilateral upper limb synergies and synergy differences between motions were proposed as spatial indicators to measure alterations in synergy spatial distribution. Additionally, as a temporal characteristic, the correlation of bilateral upper limb activation coefficient was proposed to describe the coordination control of the central nervous system. All temporal and spatial indicators were compared between patients and healthy subjects.Main results.The patients showed a significant decrease (p< 0.05) in the symmetry of bilateral upper limb synergy spatial distribution and correlation of bilateral upper limb activation coefficient. Patients with motor dysfunction also showed an increase in synergy similarity between motions, indicating altered spatial distribution of muscle synergies.Significance.These findings provide valuable insights into specific patterns associated with motor dysfunction, informing motor function assessment, and guiding targeted interventions and rehabilitation strategies for neurologically disordered patients.

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OBJECTIVES: To overcome the limitations of traditional diagnosis of orbicularis oris muscle function in mouth-breathing patients, this study aims to propose a surface electromyographic (sEMG) based method for reliable and accurate quantitative assessment of lip closure ability. METHODS: A total of 21 volunteers (16 patients and 5 healthy subjects, aged 8-16) were included in the study. Three nonlinear onset detection algorithms - Teager-Kaiser Energy (TKE) operator, Sample Entropy (SampEn), and Fuzzy Entropy (FuzzyEn) - were compared for their ability to identify lip closure in sEMG signals. Lip Closure EMG Activity Index (LCEAI) was proposed based on the action segments detected by the best performing algorithm for the quantitative assessment of lip closure. RESULTS: The results indicated that FuzzyEn had the highest lip closure identification rate at 93.78 %, the lowest average onset delay of 47.50 ms, the lowest average endpoint delay of 73.10 ms, and the minimal time error of 111.61 ms, exhibiting superior performance. The calculation results of the LCEAI closely corresponded with the actual degree of lip closure in patients. CONCLUSIONS: The lip closure ability assessment method proposed in this study can provide a quantitative basis for the diagnosis of mouth breathing.