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1.
J Neuroeng Rehabil ; 19(1): 86, 2022 Aug 09.
Artigo em Inglês | MEDLINE | ID: mdl-35945600

RESUMO

BACKGROUND: Improving the prediction ability of a human-machine interface (HMI) is critical to accomplish a bio-inspired or model-based control strategy for rehabilitation interventions, which are of increased interest to assist limb function post neurological injuries. A fundamental role of the HMI is to accurately predict human intent by mapping signals from a mechanical sensor or surface electromyography (sEMG) sensor. These sensors are limited to measuring the resulting limb force or movement or the neural signal evoking the force. As the intermediate mapping in the HMI also depends on muscle contractility, a motivation exists to include architectural features of the muscle as surrogates of dynamic muscle movement, thus further improving the HMI's prediction accuracy. OBJECTIVE: The purpose of this study is to investigate a non-invasive sEMG and ultrasound (US) imaging-driven Hill-type neuromuscular model (HNM) for net ankle joint plantarflexion moment prediction. We hypothesize that the fusion of signals from sEMG and US imaging results in a more accurate net plantarflexion moment prediction than sole sEMG or US imaging. METHODS: Ten young non-disabled participants walked on a treadmill at speeds of 0.50, 0.75, 1.00, 1.25, and 1.50 m/s. The proposed HNM consists of two muscle-tendon units. The muscle activation for each unit was calculated as a weighted summation of the normalized sEMG signal and normalized muscle thickness signal from US imaging. The HNM calibration was performed under both single-speed mode and inter-speed mode, and then the calibrated HNM was validated across all walking speeds. RESULTS: On average, the normalized moment prediction root mean square error was reduced by 14.58 % ([Formula: see text]) and 36.79 % ([Formula: see text]) with the proposed HNM when compared to sEMG-driven and US imaging-driven HNMs, respectively. Also, the calibrated models with data from the inter-speed mode were more robust than those from single-speed modes for the moment prediction. CONCLUSIONS: The proposed sEMG-US imaging-driven HNM can significantly improve the net plantarflexion moment prediction accuracy across multiple walking speeds. The findings imply that the proposed HNM can be potentially used in bio-inspired control strategies for rehabilitative devices due to its superior prediction.


Assuntos
Músculo Esquelético , Velocidade de Caminhada , Articulação do Tornozelo/fisiologia , Eletromiografia/métodos , Humanos , Músculo Esquelético/diagnóstico por imagem , Músculo Esquelético/fisiologia , Caminhada/fisiologia
2.
PLoS One ; 17(8): e0266731, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-35947818

RESUMO

Lifting tasks, among manual material handling activities, are those mainly associated with low back pain. In recent years, several instrumental-based tools were developed to quantitatively assess the biomechanical risk during lifting activities. In this study, parameters related to balance and extracted from the Centre of Pressure (CoP) data series are studied in fatiguing frequency-dependent lifting activities to: i) explore the possibility of classifying people with LBP and asymptomatic people during the execution of task; ii) examine the assessment of the risk levels associated with repetitive lifting activities, iii) enhance current understanding of postural control strategies during lifting tasks. Data were recorded from 14 asymptomatic participants and 7 participants with low back pain. The participants performed lifting tasks in three different lifting conditions (with increasing lifting frequency and risk levels) and kinetic and surface electromyography (sEMG) data were acquired. Kinetic data were used to calculated the CoP and parameters extracted from the latter show a discriminant capacity for the groups and the risk levels. Furthermore, sEMG parameters show a trend compatible with myoelectric manifestations of muscular fatigue. Correlation results between sEMG and CoP velocity parameters revealed a positive correlation between amplitude sEMG parameters and CoP velocity in both groups and a negative correlation between frequency sEMG parameters and CoP velocity. The current findings suggest that it is possible to quantitatively assess the risk level when monitoring fatiguing lifting tasks by using CoP parameters as well as identify different motor strategies between people with and without LBP.


Assuntos
Dor Lombar , Fadiga Muscular , Fenômenos Biomecânicos , Eletromiografia/métodos , Fadiga , Humanos , Remoção , Músculo Esquelético
3.
Med Eng Phys ; 106: 103833, 2022 08.
Artigo em Inglês | MEDLINE | ID: mdl-35926952

RESUMO

Different mechanisms of force transmission have been developed for the movement of wheelchairs, from the standard pushrim propulsion to the handbike. Contributing to this repertoire, we recently developed a system of propulsion based on a pulley-cable mechanism, the Handwheelchair.Q. In contrast to other propulsion systems, the Handwheelchair.Q requires users to extend the shoulders and flex the elbows to move the wheelchair forward, mimicking the rowing gesture. Whether however our proposed, propulsion system imposes a similar degree of shoulder muscles excitation with respect to the conventional, pushrim system is yet to be addressed. In this study we therefore assess whether the Handwheelchair.Q demands a similar degree and timing of muscle excitation with respect to the pushrim wheelchair, for a given travelled distance. We address this issue by sampling the angular speed of the two wheels and the surface EMGs from ten, shoulder muscles, while seven subjects use the two propulsion systems at constantly low and high speeds, one at a time. As expected, results revealed opposite muscle groups were excited when comparing the two mechanisms for wheelchair propulsion. ANOVA statistics indicated the amplitude of EMGs was greater for shoulder flexors and elbow extensors during the drive phase of pushrim propulsion, with the opposite being observed for the Handwheelchair.Q. Interestingly, from the angular speed we observed a significantly greater average displacement was achieved with the Handwheelchair.Q. Our results support therefore the notion that, with respect to pushrim propulsion, subjects were able to move faster without overloading the shoulder muscle with the Handwheelchair.Q.


Assuntos
Cadeiras de Rodas , Fenômenos Biomecânicos , Eletromiografia , Humanos , Músculo Esquelético , Ombro
4.
Med Eng Phys ; 106: 103832, 2022 08.
Artigo em Inglês | MEDLINE | ID: mdl-35926956

RESUMO

The cell membrane capacitance (Cm) and characteristic frequencies (fc) of tissues can be obtained using segmental bioelectrical impedance spectroscopy (S-BIS). Higher Cm and lower fc are associated with a larger surface area of skeletal muscle fibers with T-tubules in the tissues. Muscle fiber membrane is one of the major physiological factors that influence surface electromyograms (EMGs) as well as the number of recruited motor units so that the amplitude of surface EMG may be correlated with Cm and fc. The aim of the current study was to examine the association of fc or Cm in the lower leg with contractile and neuromuscular properties in the plantar flexors. We analyzed data from 59 participants (29 women) aged 21-83 years. The Cm, fc, and intracellular water (ICW) in the lower leg were obtained using S-BIS. We measured electrical-evoked torque, maximal voluntary contraction (MVC) torque, and amplitude of EMG normalized by the M wave during MVC contraction. The high Cm group had a significantly lower fc and significantly higher MVC torque, estimated maximum torque, twitch torque, and root mean square (RMS) of EMG normalized by the M wave (EMG:M) in the musculus triceps surae compared to the low Cm group (P < 0.05). Cm was positively and fc was negatively correlated with the nRMS of EMG:M in the triceps surae (P < 0.05). S-BIS recordings can be used to detect changes in skeletal muscle membrane capacitance, which may provide insights into the number of T-tubules. The muscle capacitance measured with S-BIS can be predictive of muscle force generation.


Assuntos
Contração Muscular , Músculo Esquelético , Estimulação Elétrica/métodos , Eletromiografia , Feminino , Humanos , Contração Isométrica/fisiologia , Contração Muscular/fisiologia , Músculo Esquelético/fisiologia , Torque
5.
Sci Rep ; 12(1): 13451, 2022 Aug 04.
Artigo em Inglês | MEDLINE | ID: mdl-35927291

RESUMO

This study aimed to investigate how facilitatory and inhibitory KT of the Vastus Medialis affected the activation and the fatigue indices of VM, Vastus Lateralis (VL) and Rectus Femoris (RF) throughout a dynamic fatigue protocol. Seventeen collegiate athletes (Ten males, seven females, age: 24.76 ± 3.99 years, height: 1.73 ± 0.10 m, mass: 68.11 ± 8.54 kg) voluntarily participated in four dynamic fatigue protocol sessions in which no-tape (control condition), inhibitory, facilitatory and sham KTs were applied to the Vastus Medialis in each session. The protocol included 100 dynamic maximum concentric knee extensions at 90°/s using an isokinetic dynamometry device. The knee extensor muscle activities were recorded using wireless surface electromyography. The average muscle activity (Root mean square) during the first three repetitions and the repetitions number of 51-100, respectively, were used to calculate the before and after exhaustion muscle activity. Furthermore, median frequency slope during all repetitions was reported as the fatigue rate of muscles during different KT conditions and for the control condition (no-tape). The results showed neither muscle activation (significance for the main effect of KT; VM = 0.82, VL = 0.72, RF = 0.19) nor fatigue rate (significance for the main effect of KT; VM = 0.11 VL = 0.71, RF = 0.53) of the superficial knee extensor muscles were affected in all four conditions. These findings suggest that the direction of KT cannot reduce, enhance muscle activity or cause changes in muscle exhaustion. Future studies should investigate the generalizability of current findings to other populations.


Assuntos
Fita Atlética , Fadiga Muscular , Músculo Quadríceps , Adulto , Eletromiografia/métodos , Feminino , Humanos , Masculino , Fadiga Muscular/fisiologia , Músculo Quadríceps/fisiologia , Adulto Jovem
6.
Sleep ; 45(4)2022 Apr 11.
Artigo em Inglês | MEDLINE | ID: mdl-35934508

RESUMO

STUDY OBJECTIVES: The present study investigated the hypothesis that subjects with primary sleep bruxism (SB) exhibit masseter and cortical hyperactivities during quiet sleep periods that are associated with a high frequency of rhythmic masticatory muscle activity (RMMA). METHODS: Fifteen SB and ten control participants underwent polysomnographic recordings. The frequencies of oromotor events and arousals and the percentage of arousals with oromotor events were assessed. Masseter muscle tone during sleep was quantified using a cluster analysis. Electroencephalography power and heart rate variability were quantified and then compared between the two groups and among sleep stages. RESULTS: The frequency of RMMA and percentage of arousals with RMMA were significantly higher in SB subjects than in controls in all stages, while these variables for nonrhythmic oromotor events did not significantly differ between the groups. In SB subjects, the frequency of RMMA was the highest in stage N1 and the lowest in stages N3 and R, while the percentage of arousals with RMMA was higher in stage N3 than stages N1 and R. The cluster analysis classified masseter activity during sleep into two clusters for masseter tone and contractions. Masseter muscle tone showed typical stage-dependent changes in both groups but did not significantly differ between the groups. Furthermore, no significant differences were observed in electroencephalography power or heart rate variability between the groups. CONCLUSION: Young SB subjects exhibited sleep stage-dependent increases in the responsiveness of RMMA to transient arousals, but did not show masseter or cortical hyperactivity during sleep.


Assuntos
Bruxismo do Sono , Eletromiografia , Humanos , Músculo Masseter , Músculos da Mastigação , Polissonografia , Fases do Sono/fisiologia
8.
Sensors (Basel) ; 22(15)2022 Jul 29.
Artigo em Inglês | MEDLINE | ID: mdl-35957243

RESUMO

Step length is a critical hallmark of health status. However, few studies have investigated the modifiable factors that may affect step length. An exploratory, cross-sectional study was performed to evaluate the surface electromyography (sEMG) and body impedance analysis (BIA) parameters, combined with individual demographic data, to predict the individual step length using the GAITRite® system. Healthy participants aged 40-80 years were prospectively recruited, and three models were built to predict individual step length. The first model was the best-fit model (R2 = 0.244, p < 0.001); the root mean square (RMS) values at maximal knee flexion and height were included as significant variables. The second model used all candidate variables, except sEMG variables, and revealed that age, height, and body fat mass (BFM) were significant variables for predicting the average step length (R2 = 0.198, p < 0.001). The third model, which was used to predict step length without sEMG and BIA, showed that only age and height remained significant (R2 = 0.158, p < 0.001). This study revealed that the RMS value at maximal strength knee flexion, height, age, and BFM are important predictors for individual step length, and possibly suggesting that strengthening knee flexor function and reducing BFM may help improve step length.


Assuntos
Nível de Saúde , Articulação do Joelho , Composição Corporal , Estudos Transversais , Impedância Elétrica , Eletromiografia , Humanos
9.
Sensors (Basel) ; 22(15)2022 Aug 03.
Artigo em Inglês | MEDLINE | ID: mdl-35957354

RESUMO

Electromyography (EMG) sensors have been used for measuring muscle signals and for diagnosing neuromuscular disease. Available commercial EMG sensor are expensive and not easily available for individuals. The aim of the study is to validate our designed low-cost sensor against a well-known commercial system for measuring muscle activity and fatigue assessment. The evaluation of the designed system was done through a series of dynamic exercises performed by volunteers. Our low-cost EMG sensor and the commercially available system were placed on the vastus lateralis muscle to concurrently record the signal in a maximum voluntary contraction (MVC). The signal analysis was done using two validation indicators: Spearman's correlation, and intra-class cross correlation on SPSS 26.0 version. For the muscle fatigue assessment, the root mean square (RMS), mean absolute value (MAV) and mean frequency (MNF) indicators were used. The results at the peak and mean level muscle contraction intensity were computed. The relative agreement for the two systems was excellent at peak level muscle contraction range (ICC 0.74-0.92), average 0.83 and mean level muscle contraction intensity range (ICC 0.65-0.85) with an average of 0.74. The Spearman's correlation average was 0.76 with the range of (0.71-0.85) at peak level contraction, whiles the mean level contraction average was 0.71 at a range of (0.62-0.81). In determining muscle fatigue, the RMS and MAV showed increasing values in the time domain, while the MEF decreased in the frequency domain. Overall, the results indicated a good to excellent agreement of the two systems and confirmed the reliability of our design. The low-cost sensor also proved to be suitable for muscle fatigue assessment. Our designed system can therefore be implemented for rehabilitation, sports science, and ergonomics.


Assuntos
Fadiga Muscular , Músculo Esquelético , Eletromiografia/métodos , Humanos , Contração Isométrica/fisiologia , Contração Muscular/fisiologia , Fadiga Muscular/fisiologia , Músculo Esquelético/fisiologia , Reprodutibilidade dos Testes
10.
Sensors (Basel) ; 22(15)2022 Aug 05.
Artigo em Inglês | MEDLINE | ID: mdl-35957417

RESUMO

Gesture recognition based on wearable devices is one of the vital components of human-computer interaction systems. Compared with skeleton-based recognition in computer vision, gesture recognition using wearable sensors has attracted wide attention for its robustness and convenience. Recently, many studies have proposed deep learning methods based on surface electromyography (sEMG) signals for gesture classification; however, most of the existing datasets are built for surface EMG signals, and there is a lack of datasets for multi-category gestures. Due to model limitations and inadequate classification data, the recognition accuracy of these methods cannot satisfy multi-gesture interaction scenarios. In this paper, a multi-category dataset containing 20 gestures is recorded with the help of a wearable device that can acquire surface electromyographic and inertial (IMU) signals. Various two-stream deep learning models are established and improved further. The basic convolutional neural network (CNN), recurrent neural network (RNN), and Transformer models are experimented on with our dataset as the classifier. The CNN and the RNN models' test accuracy is over 95%; however, the Transformer model has a lower test accuracy of 71.68%. After further improvements, the CNN model is introduced into the residual network and augmented to the CNN-Res model, achieving 98.24% accuracy; moreover, it has the shortest training and testing time. Then, after combining the RNN model and the CNN-Res model, the long short term memory (LSTM)-Res model and gate recurrent unit (GRU)-Res model achieve the highest classification accuracy of 99.67% and 99.49%, respectively. Finally, the fusion of the Transformer model and the CNN model enables the Transformer-CNN model to be constructed. Such improvement dramatically boosts the performance of the Transformer module, increasing the recognition accuracy from 71.86% to 98.96%.


Assuntos
Algoritmos , Gestos , Eletromiografia/métodos , Mãos , Humanos , Redes Neurais de Computação , Reconhecimento Psicológico
11.
Sensors (Basel) ; 22(15)2022 Aug 06.
Artigo em Inglês | MEDLINE | ID: mdl-35957442

RESUMO

Crew fatigue from standing posture motion, caused by ship motion, can lead to marine accidents. Therefore, the mechanism of fatigue in crew members ought to be elucidated. The standing posture of humans is maintained by postural state detection through the visual, vestibular, and somatosensory systems. Humans can adjust their posture through corrective postural reactions (CPR) generated after anticipatory postural adjustments (APAs) by using information from these sensory systems. APAs refer to skills acquired by learning from past motions and perturbations and are prepared by the central nervous system based on visual information before the actual perturbation occurs. We hypothesized that APAs would decrease fatigue in crew members by stabilizing their standing posture motions. We aimed to clarify the human standing posture control influenced by APAs based on visual information. To this end, we presented wave images with different wave directions to the participants using a visual simulator and analyzed their standing posture motion. We found that the participants stabilized their standing posture based on the projected wave directions. This showed that the participants predicted ship motion from the wave images and controlled their center of pressure (COP) through APAs. Individual differences in standing postural motion may indicate the subjective variation of APAs based on individual experiences. This study was limited to males aged 20-23 years. To generalize this study, randomized controlled trials should be performed with participants of multiple age groups, including men and women.


Assuntos
Músculo Esquelético , Postura , Eletromiografia/métodos , Fadiga , Feminino , Humanos , Masculino , Músculo Esquelético/fisiologia , Equilíbrio Postural/fisiologia , Postura/fisiologia
12.
Pain Res Manag ; 2022: 8717932, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-35958675

RESUMO

Background: The severity of the articular lesion is the single most essential element in investigating the extent of flexion that is required for activities. However, a prior study found no differences in muscle strength gains of quadriceps muscles at different knee angles in people with patellofemoral pain syndrome (PFPS). Objective: The effects of patellar taping and electromyographic biofeedback (EMG-BF)-guided isometric quadriceps strengthening at different knee angles (e.g., 30°, 60°, and 90° of knee flexion) on quadriceps strength and functional performance in people with PFPS were compared in this single-blind randomized controlled parallel trial. Methods: Sixty adult male athletes with PFPS (age: 26.9 ± 1.4 years) were randomly divided into two groups. The experimental group (n = 30) received patellar taping and EMG-BF-guided isometric contraction exercise at 30°, 60°, and 90° angles, and the control group (n = 30) received sham patellar taping without EMG-BF-guided exercises for six weeks. Pain intensity, knee function, muscle strength, and the single-leg triple hop (SLTH) test were assessed. Results: The pain intensity and SLTH scores between the groups were significantly different at the end of the trial (p ≤ 0.001). The EMG-BF and control groups had mean pain scores of 1.3 (0.8) and 4.5 (0.8), respectively. The EMG-BF and control groups had mean functional scores of 80.4 (5.1) and 69.1 (6.1), respectively. The mean SLTH score for the EMG-BF group was 540.7 (51.2) and for the control group it was 509.4 (49.8) after the trial. Quadriceps muscle strength was significantly higher in those who performed quadriceps strength training at 60° of knee flexion after six weeks than in those who performed strength training at 30° or 90° of knee flexion. Conclusion: The findings indicated that individuals who trained their quadriceps at a 60° knee angle had significantly stronger quadriceps muscles than individuals who trained at 30° or 90° of knee flexion. Trial Registration. This trial is registered at Clinical Trials.gov under the identifier NCT05055284.


Assuntos
Síndrome da Dor Patelofemoral , Adulto , Atletas , Biorretroalimentação Psicológica , Eletromiografia , Humanos , Masculino , Força Muscular/fisiologia , Síndrome da Dor Patelofemoral/terapia , Desempenho Físico Funcional , Músculo Quadríceps/fisiologia , Método Simples-Cego , Adulto Jovem
13.
Artigo em Inglês | MEDLINE | ID: mdl-35925857

RESUMO

To prevent lower back pain (LBP) in the industrial workplace, various powered back support exoskeletons (BSEs) have been developed. However, conventional kinematics-triggered assistance (KA) strategies induce latency, degrading assistance efficiency. Therefore, we proposed and experimentally evaluated a surface electromyography (sEMG)-triggered assistance (EA) strategy. Nine healthy subjects participated in the lifting experiments: 1) external loads test, 2) extra latency test, and 3) repetitive lifting test. In the external loads test, subject performed lifting with four different external loads (0 kg, 7.5 kg, 15 kg, and 22.5 kg). The assistance was triggered earlier by EA compared to KA from 114 ms to 202 ms, 163 ms to 269 ms for squat and stoop lifting respectively, as external loads increased from 0 kg to 22.5 kg. In the extra latency test, the effects of extra latency (manual switch, 0 ms, 100 ms and 200 ms) in EA on muscle activities were investigated. Muscle activities were minimized in the fast assistance (0 ms and 100 ms) condition and increased with extra latency. In the repetitive lifting test, the EA strategy significantly reduced L1 muscle fatigue by 70.4% in stoop lifting, compared to KA strategy. Based on the experimental results, we concluded that fast assistance triggered by sEMG improved assistance efficiency in BSE and was particularly beneficial in heavy external loads situations. The proposed assistive strategy can be used to prevent LBP by reducing back muscle fatigue and is easily applicable to various industrial exoskeleton applications.


Assuntos
Exoesqueleto Energizado , Dor Lombar , Dorso/fisiologia , Fenômenos Biomecânicos , Eletromiografia/métodos , Humanos , Remoção , Dor Lombar/prevenção & controle , Músculo Esquelético/fisiologia
14.
Artigo em Inglês | MEDLINE | ID: mdl-35930510

RESUMO

Electromyography (EMG) signals have been used in designing muscle-machine interfaces (MuMIs) for various applications, ranging from entertainment (EMG controlled games) to human assistance and human augmentation (EMG controlled prostheses and exoskeletons). For this, classical machine learning methods such as Random Forest (RF) models have been used to decode EMG signals. However, these methods depend on several stages of signal pre-processing and extraction of hand-crafted features so as to obtain the desired output. In this work, we propose EMG based frameworks for the decoding of object motions in the execution of dexterous, in-hand manipulation tasks using raw EMG signals input and two novel deep learning (DL) techniques called Temporal Multi-Channel Transformers and Vision Transformers. The results obtained are compared, in terms of accuracy and speed of decoding the motion, with RF-based models and Convolutional Neural Networks as a benchmark. The models are trained for 11 subjects in a motion-object specific and motion-object generic way, using the 10-fold cross-validation procedure. This study shows that the performance of MuMIs can be improved by employing DL-based models with raw myoelectric activations instead of developing DL or classic machine learning models with hand-crafted features.


Assuntos
Membros Artificiais , Mãos , Eletromiografia/métodos , Humanos , Movimento (Física) , Redes Neurais de Computação
15.
PLoS One ; 17(8): e0272118, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-35921380

RESUMO

In this paper, an aliasing noise restraint technique and a system identification-based surface electromyography (sEMG)-force prediction model are proposed to realize a type of robust sEMG and muscle force prediction. For signal denoising, a novel non-negative matrix factorization screening empirical mode decomposition (NMFSEMD) and a fast orthogonal search (FOS)-based muscle force prediction model are developed. First, the NMFSEMD model is used to screen the empirical mode decomposition (EMD) results into the noisy intrinsic mode functions (IMF). Then, the noise matrix is computed using IMF translation and superposition, and the matrix is used as the input of NMF to obtain the denoised IMF. Furthermore, the reconstruction outcome of the NMFSEMD method can be used to estimate the denoised sEMG. Finally, a new sEMG muscle force prediction model, which considers a kind of candidate function in derivative form, is constructed, and a data-training-based linear weighted model is obtained. Extensive experimental results validate the suggested method's correction: after the NMFSEMD denoising of raw sEMG signal, the signal-noise ratio (SNR) can be improved by about 15.0 dB, and the energy percentage (EP) can be greater than 90.0%. Comparing with the muscle force prediction models using the traditional pretreatment and LSSVM, and the NMFSEMD plus LSSVM-based method, the mean square error (MSE) of our approach can be reduced by at least 1.2%.


Assuntos
Algoritmos , Processamento de Sinais Assistido por Computador , Eletromiografia/métodos , Músculos , Razão Sinal-Ruído
16.
Sci Rep ; 12(1): 13387, 2022 Aug 04.
Artigo em Inglês | MEDLINE | ID: mdl-35927570

RESUMO

Perturbation exercises enhance lower limb and trunk muscles, and adding swing perturbation while loading during exercise might improve muscle activation or strength. This study aimed to check variations in trunk and lower limb muscle activity during conventional isometric squats, and whether it will change with or without swing using the Hammerobics-synchronized squat method. Twelve healthy men participated in this study. Activities for the abductor hallucis, tibialis anterior, tibialis posterior, peroneus longus, rectus femoris, biceps femoris long head, semitendinosus, gluteus maximus, multifidus, and internal oblique muscles were measured using surface electromyography during a Hammerobics-synchronized squat and conventional isometric squat. Muscle activities were statistically compared between squat methods. Hammerobics-synchronized squats significantly activated the abductor hallucis, tibialis anterior, tibialis posterior, peroneus longus, semitendinosus, and multifidus muscles, in both phases, compared with the conventional isometric squats. The Hammerobics-synchronized squat exercise can be considered for trunk and foot stability exercise.


Assuntos
Extremidade Inferior , Músculo Esquelético , Eletromiografia , Exercício Físico/fisiologia , Humanos , Extremidade Inferior/fisiologia , Masculino , Músculo Esquelético/fisiologia , Músculo Quadríceps/fisiologia
17.
J Neural Eng ; 19(4)2022 Aug 02.
Artigo em Inglês | MEDLINE | ID: mdl-35853438

RESUMO

Objective.High-density surface electromyography (HD-sEMG) allows the reliable identification of individual motor unit (MU) action potentials. Despite the accuracy in decomposition, there is a large variability in the number of identified MUs across individuals and exerted forces. Here we present a systematic investigation of the anatomical and neural factors that determine this variability.Approach. We investigated factors of influence on HD-sEMG decomposition, such as synchronization of MU discharges, distribution of MU territories, muscle-electrode distance (MED-subcutaneous adipose tissue thickness), maximum anatomical cross-sectional area (ACSAmax), and fiber cross-sectional area. For this purpose, we recorded HD-sEMG signals, ultrasound and magnetic resonance images, and took a muscle biopsy from the biceps brachii muscle from 30 male participants drawn from two groups to ensure variability within the factors-untrained-controls (UT = 14) and strength-trained individuals (ST = 16). Participants performed isometric ramp contractions with elbow flexors (at 15%, 35%, 50% and 70% maximum voluntary torque-MVT). We assessed the correlation between the number of accurately detected MUs by HD-sEMG decomposition and each measured parameter, for each target force level. Multiple regression analysis was then applied.Main results.ST subjects showed lower MED (UT = 5.1 ± 1.4 mm; ST = 3.8 ± 0.8 mm) and a greater number of identified MUs (UT: 21.3 ± 10.2 vs ST: 29.2 ± 11.8 MUs/subject across all force levels). The entire cohort showed a negative correlation between MED and the number of identified MUs at low forces (r= -0.6,p= 0.002 at 15% MVT). Moreover, the number of identified MUs was positively correlated to the distribution of MU territories (r= 0.56,p= 0.01) and ACSAmax(r= 0.48,p= 0.03) at 15% MVT. By accounting for all anatomical parameters, we were able to partly predict the number of decomposed MUs at low but not at high forces.Significance.Our results confirmed the influence of subcutaneous tissue on the quality of HD-sEMG signals and demonstrated that MU spatial distribution and ACSAmaxare also relevant parameters of influence for current decomposition algorithms.


Assuntos
Contração Isométrica , Músculo Esquelético , Braço/fisiologia , Eletromiografia/métodos , Humanos , Contração Isométrica/fisiologia , Masculino , Músculo Esquelético/fisiologia , Torque
18.
J Neural Eng ; 19(4)2022 Aug 11.
Artigo em Inglês | MEDLINE | ID: mdl-35901723

RESUMO

Objective.Exercise-induced muscle fatigue is a complex physiological phenomenon involving the central and peripheral nervous systems, and fatigue tolerance varies across individuals. Various studies have emphasized the close relationships between muscle fatigue and the brain. However, the relationships between the resting-state electroencephalogram (rsEEG) brain network and individual muscle fatigue tolerance remain unexplored.Approach.Eighteen elite water polo athletes took part in our experiment. Five-minute before- and after-fatigue-exercise rsEEG and fatiguing task (i.e. elbow flexion and extension) electromyography (EMG) data were recorded. Based on the graph theory, we constructed the before- and after-task rsEEG coherence network and compared the network differences between them. Then, the correlation between the before-fatigue rsEEG network properties and the EMG fatigue indexes when a subject cannot keep on exercising anymore was profiled. Finally, a prediction model based on the before-fatigue rsEEG network properties was established to predict fatigue tolerance.Main results. Results of this study revealed the significant differences between the before- and after-exercise rsEEG brain network and found significant high correlations between before-exercise rsEEG network properties in the beta band and individual muscle fatigue tolerance. Finally, an efficient support vector regression (SVR) model based on the before-exercise rsEEG network properties in the beta band was constructed and achieved the accurate prediction of individual fatigue tolerance. Similar results were also revealed on another 30 subject swimmer data set further demonstrating the reliability of predicting fatigue tolerance based on the rsEEG network.Significance.Our study investigates the relationship between the rsEEG brain network and individual muscle fatigue tolerance and provides a potential objective physiological biomarker for tolerance prediction and the regulation of muscle fatigue.


Assuntos
Eletroencefalografia , Fadiga Muscular , Encéfalo/fisiologia , Eletroencefalografia/métodos , Eletromiografia , Humanos , Fadiga Muscular/fisiologia , Músculo Esquelético/fisiologia , Reprodutibilidade dos Testes
19.
Sci Rep ; 12(1): 9842, 2022 07 07.
Artigo em Inglês | MEDLINE | ID: mdl-35798755

RESUMO

Humans typically coordinate their muscles to meet movement objectives like minimizing energy expenditure. In the presence of pathology, new objectives gain importance, like reducing loading in an osteoarthritic joint, but people often do not change their muscle coordination patterns to meet these new objectives. Here we use musculoskeletal simulations to identify simple changes in coordination that can be taught using electromyographic biofeedback, achieving the therapeutic goal of reducing joint loading. Our simulations predicted that changing the relative activation of two redundant ankle plantarflexor muscles-the gastrocnemius and soleus-could reduce knee contact force during walking, but it was unclear whether humans could re-coordinate redundant muscles during a complex task like walking. Our experiments showed that after a single session of walking with biofeedback of summary measures of plantarflexor muscle activation, healthy individuals reduced the ratio of gastrocnemius-to-soleus muscle activation by 25 ± 15% (p = 0.004, paired t test, n = 10). Participants who walked with this "gastrocnemius avoidance" gait pattern reduced late-stance knee contact force by 12 ± 12% (p = 0.029, paired t test, n = 8). Simulation-informed coordination retraining could be a promising treatment for knee osteoarthritis and a powerful tool for optimizing coordination for a variety of rehabilitation and performance applications.


Assuntos
Biorretroalimentação Psicológica , Articulação do Joelho , Fenômenos Biomecânicos , Eletromiografia , Marcha/fisiologia , Humanos , Articulação do Joelho/fisiologia , Músculo Esquelético/fisiologia , Caminhada/fisiologia
20.
Pain Physician ; 25(5): E749-E757, 2022 08.
Artigo em Inglês | MEDLINE | ID: mdl-35901486

RESUMO

BACKGROUND: There are differences in the clinical treatment schemes for patients with different severities of herpes zoster (HZ). Therefore, effective and accurate evaluation of disease severity is of great significance for the formulation of treatment plans. Postherpetic neuralgia (PHN) with long-term chronic pain leads to anxiety, depression, and even suicidal thoughts, which place a heavy burden on society and the family. Therefore, identifying risk factors and taking early intervention to reduce the occurrence of PHN is meaningful. Electromyography (EMG) can provide technical support for the early diagnosis of peripheral neuropathy. However, the application of EMG in HZ and PHN has rarely been reported. The purpose of this study was to compare the detection indices of EMG in patients with different severities and prognoses of HZ and to analyze the application of EMG in severity and prognosis of HZ. OBJECTIVE: This study aimed to explore the relationship between EMG and severity and prognosis of upper limb HZ. STUDY DESIGN: A retrospective, observational study. SETTING: The study was carried out in the Pain Department of the affiliated Hospital of Jiaxing College in Jiaxing, China. METHODS: A total of 91 patients with upper limb HZ at the First Hospital of Jiaxing between January 2015 and August 2021 were enrolled. The patients were divided into mild, moderate, and severe HZ groups according to their numeric rating scale (NRS) scores. The occurrence of PHN was defined as a poor prognosis. The patients were divided into non-PHN and PHN groups according to the occurrence of PHN. Motor and sensory conduction indices of the median nerve were measured in each group. Spearman's correlation analysis was used to analyze the relationship between the EMG-related data of the median nerve and the NRS score and muscle strength. Univariate and multivariate logistic regression analyses were used to determine the independent influencing factors of PHN in patients with upper limb HZ, and the receiver operating characteristic (ROC) curve was drawn to evaluate the predictive value of EMG-related data in patients with upper limb HZ. RESULTS: Among 91 patients, there were 29 patients in the mild HZ group, 31 in the moderate HZ group, and 31 in the severe HZ group. The sensory nerve action potential (SNAP) amplitude of the median nerve in the severe and moderate HZ groups was lower than that in the mild HZ group, and that in the severe HZ group was lower than that in the moderate HZ group (F = 22.192, P < 0.05). Through Spearman's correlation analysis, it was found that the compound muscle action potential (CMAP) and SNAP amplitudes of the median nerve on the affected limb were negatively correlated with the NRS score (r = -0.266, P = 0.011; r = -0.778, P < 0.001), and there was no significant correlation between each index and muscle strength (P > 0.05). Among 91 patients, 44 and 47 were in the non-PHN and PHN groups, respectively. Univariate and multivariate logistic regression analyses showed that the CMAP amplitude of the median nerve on the affected limb (OR = 0.241, 95% CI: 0.098-0.567, P = 0.001) and SNAP amplitude (OR = 0.268, 95% CI: 0.110-0.628, P = 0.002) were independent influencing factors of PHN. Through the analysis of the ROC curve, it was found that the CMAP and SNAP amplitudes of the median nerve on the affected limb had a high predictive value for PHN (AUC = 0.657, P = 0.010; AUC = 0.773, P < 0.001). The cutoff values were 5.45 mV and 10.80 mV, respectively; and the predictive value of the 2 indices combined was the highest (AUC = 0.785, P < 0.001). LIMITATIONS: The nonrandomized, single-center, small sample size, and retrospective design are major limitations of this study. CONCLUSION: The CMAP and SNAP amplitudes of the median nerve on the affected limb were related to the degree of pain in patients with upper limb HZ. The CMAP and SNAP amplitudes of the median nerve on the affected limb can be used as prognostic factors for patients with upper limb HZ, and CMAP amplitude combined with SNAP amplitude is more valuable in predicting prognosis.


Assuntos
Herpes Zoster , Neuralgia Pós-Herpética , Eletromiografia/efeitos adversos , Herpes Zoster/complicações , Herpes Zoster/diagnóstico , Humanos , Neuralgia Pós-Herpética/diagnóstico , Neuralgia Pós-Herpética/etiologia , Prognóstico , Estudos Retrospectivos , Extremidade Superior
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