Surface Electromyography Research Articles

Predicting Continuous Locomotion Modes via Multidimensional Feature Learning From sEMG.

Walking-assistive devices require adaptive control methods to ensure smooth transitions between various modes of locomotion. For this purpose, detecting human locomotion modes (e.g., level walking or stair ascent) in advance is crucial for improving the intelligence and transparency of such robotic systems. This study proposes Deep-STF, a unified end-to-end deep learning model designed for integrated feature extraction in spatial, temporal, and frequency dimensions from surface electromyography (sEMG) signals. Our model enables accurate and robust continuous prediction of nine locomotion modes and 15 transitions at varying prediction time intervals, ranging from 100 to 500 ms. Experimental results showcased Deep-STP's cutting-edge prediction performance across diverse locomotion modes and transitions, relying solely on sEMG data. When forecasting 100 ms ahead, Deep-STF achieved an improved average prediction accuracy of 96.60%, outperforming seven benchmark models. Even with an extended 500ms prediction horizon, the accuracy only marginally decreased to 93.22%. The averaged stable prediction times for detecting next upcoming transitions spanned from 31.47 to 371.58 ms across the 100-500 ms time advances. Although the prediction accuracy of the trained Deep-STF initially dropped to 71.12% when tested on four new terrains, it achieved a satisfactory accuracy of 92.51% after fine-tuning with just 5 trials and further improved to 96.27% with 15 calibration trials. These results demonstrate the remarkable prediction ability and adaptability of Deep-STF, showing great potential for integration with walking-assistive devices and leading to smoother, more intuitive user interactions.

Effects of Kitchen Cooking Height on Upper Limb Muscle Activation, Posture, and Perceived Discomfort of Chinese Older and Young Women.

Inappropriate kitchen cooking height may lead to uncomfortable and muscle fatigue. This study aims to compare the effects of kitchen cooking height on upper limb muscle activation, posture, and perceived discomfort among different age groups. Fifteen older women and fifteen young Chinese women each completed three consecutive 20 s simulated cooking tasks at five different heights. Surface electromyography, motion capture, and Borg CR10 scale were used to measure muscle loading. Results showed that the main power muscles of the cooking task were the anterior deltoid, brachioradialis, and biceps brachii. The higher muscle contribution rate of biceps brachii and triceps brachii was found in the younger group compared to the older group (p < 0.05). Muscle activation of the anterior deltoid (different in 1.28-2.87%), pectoralis major (different in 1.43-1.69%), and erector spinae (different in 0.6-1.21%), as well as right shoulder abduction (different in 5.91°-7.96°), were significantly higher in older group than in young group (p < 0.05). Muscle activation of the anterior deltoid and right shoulder abduction decreased significantly with decreasing height (p < 0.05). A height of 200-250 mm below the elbow was considered a more comfortable cooking height for both age groups. This provides data to support the design of cabinet sizes.

Correlations Between Mandibular Kinematics and Electromyography During the Masticatory Cycle: An Observational Study by Digital Analysis

The analysis of the masticatory cycle plays a fundamental role in studying the functions of the stomatognathic system and evaluating temporomandibular dysfunctions (TMD). The primary objective of this study is to investigate the complex interplay between mandibular kinematics and surface electromyography (sEMG) activity during the masticatory cycle using advanced 4D dentistry technology in 22 healthy subjects (without TMD). By employing electromyography, it becomes feasible to capture the electrical activity of the masticatory muscles throughout the chewing process. The BTS TMJOINT (© 2023 BTS Bioengineering, Garbagnate Milanese, MI, Italy) electromyograph was utilized in this study. Mandibular tracking, on the other hand, allows for recording the movements of the mandible during chewing and condylar slopes. This latest technology (ModJaw®, Tech in motion™, Villeurbanne, France) utilizes motion sensors placed on the jaw to accurately track three-dimensional movements, including jaw opening, closing, and lateral movements. Nowadays, in clinical gnathology, it is common practice to examine masticatory function by analyzing mandibular kinematics and muscle contraction as distinct entities. Similarly, the results obtained from these analyses are typically assessed independently. The investigation of a correlation between electromyography data and mandibular kinematics during the masticatory cycle could provide several advantages for clinicians in diagnosis and lead to a combined analysis of muscle activities and intraarticular dynamics. In conclusion, it can be inferred from the results obtained in the present study that the chewing cycle with a greater vertical movement results in increased masseter muscular activity, and condylar slopes are positively correlated to an increase in temporalis muscle activation. This comprehensive approach can provide valuable insights into the relationship between muscle activity and mandibular movement, enabling clinicians to gain a deeper understanding of the functional dynamics of the stomatognathic system.

Recruitment of the diaphragm and sternocleidomastoid muscle during increasing inspiratory pressure loads in healthy young adults

BackgroundInspiratory muscle training (IMT) is often employed to enhance improvement in inspiratory muscle strength. However, the relationship between inspiratory muscle recruitment patterns and increasing inspiratory load remains unclear. Furthermore, the effect of breathing instructions on diaphragm activity at various inspiratory loads is unknown. ObjectiveTo investigate the recruitment activity of the diaphragm and sternocleidomastoid (SCM) muscles under increased inspiratory pressure loading, with and without diaphragmatic breathing instructions, in healthy young adults. MethodsParticipants were invited to breathe, in random order, 6 sets of 10 breaths at inspiratory loads of 30% to 80% maximal inspiratory pressure (MIP), in 10% increments. The measurement process was repeated with a specific focus of diaphragmatic descent during inspiration. Concurrent recorded surface electromyography of the right SCM muscle and right hemi-diaphragm thickness measured by ultrasonography during each targeted breath. ResultsSixty-two adults (31 males, age: 23±3 years) participated in the study. Irrespective of breathing instructions, computed diaphragm thickening fraction (DTf) increased with increasing inspiratory load but peaked at 50%MIP and declined with increasing load to 80%MIP. SCM recruitment increased with increasing inspiratory load to 80%MIP. Forced inspiration with diaphragmatic breathing was associated with a higher DTf and lower SCM muscle activity. The above pattern was similar for both male and female participants. Female participants produced higher SCM activity compared with males but only at inspiration loads below 50%MIP. ConclusionsIn a cohort of young healthy adults, magnitude of diaphragmatic effort was greatest at 50% MIP but declined with increasing inspiratory load to 80%MIP. Forced inspiration combined with focused diaphragmatic breathing accentuated diaphragm contraction and reduced SCM muscle contribution. Our findings show that diaphragmatic muscle recruitment is non-linear and that the generic clinical prescription of an IMT program may need to be reconfigured.

Comparison of muscle activation during quadrupedal movement training and traditional bodyweight exercises

Quadrupedal movement training (QMT) is a unique form of bodyweight training shown to improve flexibility, FMS scores, and proprioception, however, little is known about its muscle activation characteristics. Therefore, the purpose of this study was to compare surface EMG (sEMG) activity of muscles of the trunk, upper, and lower extremity during QMT movements and common traditional bodyweight exercises (TRA). Twenty (males n = 9) participants (age: 27.5 ± 10.8 yrs, height: 169.0 ± 7.0 cm, mass: 66.6 ± 10.9 kg) were prepped and fitted with sEMG electrodes on their right-side bicep brachii, medial deltoid, triceps brachii, pectoralis major, latissimus dorsi, rectus abdominus, rectus femoris and bicep femoris. Following completion of maximal voluntary isometric contraction (MVIC) tests for normalization, participants performed 4 repetitions of 8 QMT exercises (from the Animal Flow™ system) and 3 TRA exercises (pushup, squat and forearm plank) in random order. The pooled peak muscle activations of all QMT exercises resulted in moderate (21–40% MVIC) to very high (>60% MVIC) peak muscle activation levels for each muscle group with significantly higher (p > 0.05) muscle activation for the biceps (47.72 ± 21.41%), deltoid (66.58 ± 11.39%), and latissimus dorsi (62.81 ± 18.14%) than the pushup (23.31 ± 16.95, 45.63 ± 18.59, 29.17 ± 20.58% respectively) and significantly higher activation of the bicep femoris (41.89 ± 13.83%) than the squat (17.79 ± 11.12%). TRA (pushup) showed significantly higher activation of the triceps and pectoralis. There were no differences in rectus femoris or rectus abdominus. Muscle activation levels during QMT are comparable to or higher than common traditional bodyweight exercises and therefore may be an appealing strategy for training multiple muscle groups simultaneously.

Analysis of Conducting Waves Using Multi-channel Surface EMG Depends on Electrodes in Multiple Directions

Analysis of Conducting Waves Using Multi-channel Surface EMG Depends on Electrodes in Multiple Directions

Comparison of SEMG-Based Hand Gesture Classifiers

Machine learning techniques have shown success in classifying hand gestures. As the prevalence of prosthetic devices continues to rise, the adoption of non-invasive technologies, such as surface electromyography (sEMG), becomes paramount. This study systematically assesses the isolated influence of classification algorithms within hand gesture recognition (HGR) systems using sEMG data and dynamic time warping (DTW) based features. This approach effectively handles temporal variations in sEMG signals by leveraging DTW, ensuring input features are invariant to gesture speed. Six supervised learning classifiers were evaluated: the multilayer perceptron, support vector machine, logistic regression, linear discriminant analysis, k-nearest neighbors, and decision tree. Cross-validation was employed to fine-tune the segmentation hyperparameters, significantly improving results. To ensure reproducibility, the source code has been made available, the proposed system design has been detailed, and the evaluation protocols have been described. Our findings indicate that logistic regression outperformed other classifiers in this setup, achieving 95.2% accuracy in classifying six hand movements from ten healthy individuals, representing a 1.6% improvement over the best previously reported performance using the same publicly available dataset. Future research will assess the proposed HGR system’s generalization capability on larger datasets suitable for training more complex classifiers, including deep learning models.

Effects of robot-assisted hand function therapy on brain functional mechanisms: a synchronized study using fNIRS and sEMG.

Robot-assisted hand function therapy is pivotal in the rehabilitation of patients with stroke; however, its therapeutic mechanism remains elusive. Currently, research examining the impact of robot-assisted hand function therapy on brain function in patients with stroke is scarce, and there is a lack of studies investigating the correlation between muscle activity and alterations in brain function. This study aimed to investigate the correlation between forearm muscle movement and brain functional activation by employing the synchronized use of functional near-infrared spectroscopy and surface electromyography methods. Moreover, it sought to compare neural activity patterns during different rehabilitation tasks and refine the mechanism of robot-assisted hand function therapy for post-stroke hand function impairments. Stroke patients with hand dysfunction underwent three sessions of robot-assisted hand function therapy within 2 weeks to 3 months of onset. The fNIRS-sEMG synchronous technique was used to observe brain function and forearm muscle activation. Ten participants were randomly assigned to receive mirror, resistance, or passive rehabilitation training. During the intervention, cortical and muscle activation information was obtained using fNIRS and electromyographic signals. The primary outcomes included changes in oxyhemoglobin concentration and root mean square of surface electromyography. Compared to the resting state, the Oxy-Hb concentration in the brain regions involved in three rehabilitation tasks with robot-assisted hand function therapy significantly increased (p < 0.05). Mirror therapy significantly enhanced the prefrontal cortex and the superior frontal cortex activation levels. In contrast, resistance therapy significantly promoted the activation of the supplementary motor area and the premotor cortex. Passive rehabilitation tasks showed some activation in the target brain area premotor cortex region. Robot-assisted hand function therapy has shown that forearm muscle movement is closely related to oxygenated hemoglobin concentration activity in specific brain regions during different rehabilitation tasks. The simultaneous sEMG-fNIRS study found a significant correlation between muscle movement and brain activity after stroke, which provides an important basis for understanding the treatment mechanism of hand function impairment.

Characteristics of Human Postactivation Effect of Skeletal Muscles Using Spectral and Non-Linear Parameters of the Surface Electromyogram

Postactivation effect (PAE, postactivation phenomenon) is a specific type of involuntary muscle tone (tonic automatism) which is generated in the “tonogenic” structures of the brain, presumably without the “sensory copy” and “motor command” mechanisms. In this regard, the electromyogram (EMG) signal of PAE may have a simpler temporal signal structure compared to PAE-inducing voluntary activity. The purpose of this work is to characterize the temporal structure and complexity of surface EMG (sEMG) of the human deltoid and biceps brachii muscles using fractal (D) and correlation dimensions (Dc). It was found that in deltoid muscles the value of D was 1.78–1.81 both during PAE and voluntary effort (p 0.05). Dc (approximately 4.0–4.2) also did not differ between PAE and voluntary effort, although the average frequency of the sEMG spectrum during PAE was 15–16 Hz (p 0.05) higher compared to voluntary effort. In biceps brachii muscles, the D value was 1.8 during PAE and 1.62 during voluntary effort (p 0.05). Dc values did not differ between PAE and voluntary contraction (4–4.8). Thus, despite the supposed difference in the central organization of PAE and voluntary effort, the temporal structure of their sEMG did not differ, indicating that isometric voluntary effort and involuntary tone in the form of PAE share a common principle of sEMG signal generation. At the same time, the differences in the frequency of the sEMG spectrum indicate that the organization of sEMG signal during PAE is specific on the level of the motoneuron pool.

Analysis of anticipatory and compensatory postural adjustment in women of different age groups using surface electromyography.

Postural balance is crucial for daily activities, relying on the coordination of sensory systems. Balance impairment, common in the elderly, is a leading cause of mortality in this population. To analyze balance, methods like postural adjustment analysis using electromyography (EMG) have been developed. With age, women tend to experience reduced mobility and greater muscle loss compared to men. However, few studies have focused on postural adjustments in women of different ages using EMG of the lower limbs during laterolateral and anteroposterior movements. This gap could reveal a decrease in muscle activation time with aging, as activation time is vital for postural adjustments. This study aimed to analyze muscle activation times in women of different ages during postural adjustments. Thirty women were divided into two groups: young and older women. A controlled biaxial force platform was used for static and dynamic balance tests while recording lower limb muscle activity using EMG. Data analysis focused on identifying muscle activation points and analyzing postural adjustment times. Results showed significant differences in muscle activation times between the two groups across various muscles and platform tilt conditions. Younger women had longer muscle activation times than older women, particularly during laterolateral platform inclinations. In anteroposterior movements, older women exhibited longer activation times compared to their laterolateral performance, with fewer differences between the groups. Overall, older women had shorter muscle activation times than younger women, suggesting a potential indicator of imbalance and increased fall risk.

AUTOMATED GESTURE RECOGNITION USING APPLIED LINGUISTICS WITH DATA-DRIVEN DEEP LEARNING FOR ARABIC SPEECH TRANSLATION

Gesture recognition for Arabic speech translation includes developing advanced technologies that correctly translate body and hand movements corresponding to Arabic sign language (ArSL) into spoken Arabic. This leverages machine learning and computer vision techniques in complex systems simulation platforms to scrutinize the gestures utilized in ArSL, detecting mild differences in facial expressions, hand shapes, and movements. Sign Language Recognition (SLR) is paramount in assisting communication for the Deaf and Hard-of-Hearing communities. It includes using vision-based methods and Surface Electromyography (sEMG) signals. The sEMG signal is crucial for recognizing hand gestures and capturing muscular activities in sign language. Researchers have comprehensively shown the capability of EMG signals to approach specific details, mainly in classifying hand gestures. This progression is a stimulating feature in extracting the interpretation and recognition of sign languages and investigating the phonology of signed language. Leveraging machine learning algorithms and signal processing techniques in complex systems simulation platforms, researchers aim to extract relevant traits from the sEMG signals that correspond to different ArSL gestures. This study introduces an Enhanced Dwarf Mongoose Algorithm with a Deep Learning-Driven Arabic Sign Language Detection (EDMODL-ASLD) technique on sEMG data. In the initial phase, the presented EDMODL-ASLD model is subjected to data preprocessing to change the input sEMG data into an attuned format. In the next stage, feature extraction with fractal theories is used to gather relevant and nonredundant data from the EMG window to construct a feature vector. In this study, the absolute envelope (AE), energy (E), root-mean square (RMS), standard deviation (STD), and mean absolute value (MAV) are the five time-domain extracted features for the EMG window observation. Meanwhile, the dilated convolutional long short-term memory (ConvLSTM) technique is used to identify distinct sign languages. To improve the results of the dilated ConvLSTM model, the hyperparameter selection process is executed using the EDMO model. To illustrate the significance of the EDMODL-ASLD technique, a brief experimental validation is made on the Arabic SLR database. The experimental validation of the EDMODL-ASLD technique portrayed a superior accuracy value of 96.47% over recent DL approaches.

Spinal muscle characteristics during three different types of locomotion activities among college students with idiopathic scoliosis

Background contextPhysical activities such as walking and climbing stairs are pervasive in human daily life. Individuals with scoliosis frequently encounter dysfunction in their muscle recruitment. Multiple studies have corroborated the presence of muscle dysfunction in individuals diagnosed with scoliosis. However, there is currently a noteworthy research gap regarding the exploration of changes in muscle characteristics and disparities from those observed in individuals without scoliosis during everyday activities, specifically stair climbing.PurposeThis study aims to examine the unique patterns of muscle activity during daily life in individuals with scoliosis and distinguish the specific differences between scoliosis patients and the healthy controls. The findings of this study are significantly important for the future accurate assessment of scoliosis and the development of rehabilitation treatment plans.Study designCase–control study.Sample sizeTwenty eight idiopathic scoliosis patients and twenty eight controls.Outcome measuresRoot Mean Square(RMS), Maximum Voluntary Isometric Contraction(MVIC)%, RMS ratio(RMS convex / RMS concave).MethodsThe surface electromyography (sEMG) device used in this study was the Delsys Trigno, with a sampling frequency of 1500 Hz. It recorded the activation level, peak contraction, and average activation level of the erector spinae (at T6, T10, and L3 levels), gluteus maximus, gluteus medius, external oblique, and rectus abdominis muscles during three different types of locomotion for both the 28 individuals with idiopathic scoliosis and the 28 control participants.ResultsThe movement patterns of the idiopathic scoliosis patients significantly differ from those of the normal population during level walking and ascending or descending stairs. In level walking, there is an asymmetry in the activation levels of the T6 and L3 erector spinae muscles, with lower activation on the convex side compared to the concave side. Similarly, during stair ascent, the activation of the T6 and T10 erector spinae muscles is asymmetric, with higher activation on the convex side than the concave side. Moreover, during stair descent, the activation of the T6 erector spinae muscle is asymmetric, with higher activation on the convex side than the concave side.ConclusionsDuring level walking and stair activities, idiopathic scoliosis patients exhibit pronounced abnormal movement patterns that significantly differ from those of the control group. Under different activity conditions such as level walking, ascending and descending stairs, idiopathic scoliosis patients demonstrate abnormal muscle activation in different segments of the spine. It is crucial for clinicians to prioritize the symmetry of muscle activation in the spinal region of idiopathic scoliosis patients and consider incorporating symmetry training for these muscles.

Changes in motor unit firing pattern are associated with post-exercise blood pressure response in older untreated but not treated hypertensive adults.

This study aimed to determine the difference in motor unit (MU) firing pattern between hypertensive and normotensive individuals, and the relationship between MU firing pattern and post-exercise blood pressure (BP) response in older individuals. Fourteen older untreated (systolic/diastolic BP (SBP/DBP)≥130/80mmHg, 76 (5) years), 11 treated hypertensive (78 (4) years) and 14 normotensive (SBP/DBP<130/80mmHg, 71 (4) years) individuals were studied. Participants performed ramp-up exercises until 50% of maximal voluntary contraction (MVC) of knee extension and five MVCs. During the ramp-up exercise, high-density surface electromyography signals were recorded and each MU firing rate (FR) and recruitment threshold was assessed. The slope of the linear regression between MUFRs and recruitment thresholds was calculated to assess the MU firing pattern. Pre- and post-exercise blood pressure was measured. Change in (∆)SBP from pre- to post-exercise was greater in treated hypertensive than untreated hypertensive individuals (P=0.026). MUFR was lower in treated hypertensive than untreated hypertensive and normotensive individuals (P<0.001). Although the slope was not significantly different between groups (P=0.294), FRs of larger MUs were lower than those of smaller MUs in treated hypertensive and normotensive individuals (P<0.05) but sustained in untreated hypertensive individuals. The FRs of larger MUs and slope were positively correlated with the ∆SBP only in hypertensive individuals (r=0.768 and 0.715; P=0.044 and 0.020). MUFR was lower in treated hypertensive than untreated hypertensive and normotensive individuals. Furthermore, MU firing patterns were associated with the ∆SBP after exercise in older untreated hypertensive individuals, but this relationship was not observed in treated hypertensive and normotensive individuals.

Supraspinal contributions to defective antagonistic inhibition and freezing of gait in Parkinson's disease.

The neuromuscular circuit mechanisms of freezing of gait in Parkinson's disease have received little study. Technological progress enables researchers chronically to sense local field potential activity of the basal ganglia in patients while walking. To study subthalamic activity and the circuit processes of supraspinal contributions to spinal motor integration, we recorded local field potentials, surface EMG of antagonistic leg muscles and gait kinematics in patients while walking and freezing. To evaluate the specificity of our findings, we controlled our findings to internally generated volitional stops. We found specific activation-deactivation abnormalities of oscillatory activity of the subthalamic nucleus both before and during a freeze. Furthermore, we were able to show with synchronization analyses that subthalamo-spinal circuits entrain the spinal motor neurons to a defective timing and activation pattern. The main neuromuscular correlates when turning into freezing were as follows: (i) disturbed reciprocity between antagonistic muscles; (ii) increased co-contraction of the antagonists; (iii) defective activation and time pattern of the gastrocnemius muscle; and (iv) increased subthalamo-muscular coherence with the gastrocnemius muscles before the freeze. Beyond the pathophysiological insights into the supraspinal mechanisms contributing to freezing of gait, our findings have potential to inform the conceptualization of future neurorestorative therapies.

Comparison Between InterCriteria and Correlation Analyses over sEMG Data from Arm Movements in the Horizontal Plane

InterCriteria analysis (ICrA) and two kinds of correlation analyses, Pearson (PCA) and Spearman (SCA), were applied to surface electromyography (sEMG) signals obtained from human arm movements in the horizontal plane. Ten healthy participants performed ten movements, eight of which were cyclic. Each cyclic movement (CM) consisted of flexion and extension phases with equal duration (10 s, 6 s, 2 s, and 1 s) and two 5 s rest poses between them. The CMs were performed with and without an added load of 0.5 kg on the wrists of the participants. The sEMG signals from six different muscles or separate muscle heads (m. deltoideus pars clavicularis, m. deltoideus pars spinata, m. brachialis, m. anconeus, m. biceps brachii, and m. triceps brachii long head) were recorded and used to compare the results of the ICrA, PCA, and SCA. All three methods found identical consonance pairs for the flexion and extension CM phases. Additionally, PCA detected two more consonance pairs in the extension phases. In this investigation, ICrA, PCA, and SCA were proven to be reliable tools when applied separately or in combination for sEMG data. These three methods are appropriate for researching arm movements in the horizontal plane and experimental protocol revision.

Compliant Grasp Control Method for the Underactuated Prosthetic Hand Based on the Estimation of Grasping Force and Muscle Stiffness with sEMG

Human muscles can generate force and stiffness during contraction. When in contact with objects, human hands can achieve compliant grasping by adjusting the grasping force and the muscle stiffness based on the object’s characteristics. To realize humanoid-compliant grasping, most prosthetic hands obtain the stiffness parameter of the compliant controller according to the environmental stiffness, which may be inconsistent with the amputee’s intention. To address this issue, this paper proposes a compliant grasp control method for an underactuated prosthetic hand that can directly obtain the control signals for compliant grasping from surface electromyography (sEMG) signals. First, an estimation method of the grasping force is established based on the Huxley muscle model. Then, muscle stiffness is estimated based on the muscle contraction principle. Subsequently, a relationship between the muscle stiffness of the human hand and the stiffness parameters of the prosthetic hand controller is established based on fuzzy logic to realize compliant grasp control for the underactuated prosthetic hand. Experimental results indicate that the prosthetic hand can adjust the desired force and stiffness parameters of the impedance controller based on sEMG, achieving a quick and stable grasp as well as a slow and gentle grasp on different objects.

Effect of integrated manual and verbal cueing on functional transfers in chronic stroke survivors: a randomized controlled study

Purpose The profession of physical therapy has historically relied on manual facilitation to improve motor control strategies and performance in persons rehabilitating from a stroke, yet there is insufficient evidence to support its use during functional task training. The purpose of this study was to determine the effects of integrated cueing (verbal and manual) and verbal cueing approaches during sit-to-stand training on midline alignment & muscle activation in chronic stroke survivors. Methods Twenty-one chronic right-brained stroke survivors with hemiplegia were randomly assigned to the Integrated Cueing or Verbal Only group and outcome measures were recorded using an 18-Camera Motion Capture System, force plates, and surface electromyography (EMG). Results Both groups demonstrated a significant improvement in symmetry toward the midline after thirty training repetitions. Significant improvements in muscle activation were found in two muscle groups on the affected side of the body in the Integrated Cueing group, gastrocnemius and rectus femoris. Conclusion Both the Verbal Only and Integrated Cueing groups made significant progress toward more symmetrical movement, yet more significant changes in the activation of hemiparetic extensor muscles were seen in the Integrated Cueing group. These findings support the use of manual cueing in movement activation and performance during the training of functional tasks. IMPLICATIONS FOR REHAB Physical therapists commonly use manual tactile cues to facilitate movement performance but there is currently insufficient evidence to support this use with stroke survivors. In a relatively small sample size, both verbal cues and integrated cues (verbal plus manual) improved symmetry during sit to stand in chronic right brain stroke survivors. Integrated cueing enhanced motor activation and performance during sit to stand better than verbal cues alone. Manual tactile cueing should be considered during functional task retraining.

The probability density function of the surface electromyogram and its dependence on contraction force in the vastus lateralis

IntroductionThe probability density function (PDF) of the surface electromyogram (sEMG) depends on contraction force. This dependence, however, has so far been investigated by having the subject generate force at a few fixed percentages of MVC. Here, we examined how the shape of the sEMG PDF changes with contraction force when this force was gradually increased from zero.MethodsVoluntary surface EMG signals were recorded from the vastus lateralis of healthy subjects as force was increased in a continuous manner vs. in a step-wise fashion. The sEMG filling process was examined by measuring the EMG filling factor, computed from the non-central moments of the rectified sEMG signal.Results(1) In 84% of the subjects, as contraction force increased from 0 to 10% MVC, the sEMG PDF shape oscillated back and forth between the semi-degenerate and the Gaussian distribution.(2) The PDF–force relation varied greatly among subjects for forces between 0 and ~ 10% MVC, but this variability was largely reduced for forces above 10% MVC.(3) The pooled analysis showed that, as contraction force gradually increased, the sEMG PDF evolved rapidly from the semi-degenerate towards the Laplacian distribution from 0 to 5% MVC, and then more slowly from the Laplacian towards the Gaussian distribution for higher forces.ConclusionsThe study demonstrated that the dependence of the sEMG PDF shape on contraction force can only be reliably assessed by gradually increasing force from zero, and not by performing a few constant-force contractions. The study also showed that the PDF–force relation differed greatly among individuals for contraction forces below 10% MVC, but this variability was largely reduced when force increased above 10% MVC.

Clinical study on the effects of cluster needling at scalp points with needle retaining combined with the training of the upper-limb intelligent rehabilitation robot on shoulder function in stroke patients during convalescence

To explore the effects of cluster needling at scalp points with needle retaining combined with the training of the upper-limb intelligent rehabilitation robot on shoulder function in stroke patients during convalescence. Ninety stroke patients during convalescence were collected and randomized into scalp point group, robot training group and combined intervention group, with 30 cases each. In the scalp point group, the cluster needling was delivered at scalp points with the needles retained. In the robot training group, the patients were trained with the upper-limb intelligent rehabilitation robot. In the combined intervention group, the patients received both the cluster needling and the training of the upper-limb intelligent rehabilitation robot. In each group, the treatment was given once daily, 5 treatments a week with 2 days rest, for consecutive 4 weeks. Separately, before and after treatment, the score of Fugl-Meyer assessment upper extremity scale (FMA-UE) and the score of activity of daily living (ADL) were evaluated. Using the in-built assessment system of the upper-limb intelligent rehabilitation robot, the range of motion (ROM) of forward flexion, horizontal abduction and horizontal adduction of the affected shoulder joint were evaluated. With surface electromyogram (sEMG), the sEMG value of the deltoid muscle and the pectoralis major on the affected side were detected. Compared with the values before treatment, ADL score and FMA-UA score increased in patients of the three groups (P<0.05), and ROM of forward flexion, horizontal abduction and horizontal adduction of the affected shoulder joint was larger (P<0.05), the sEMG value of the fasciculi pectoralis major anterior of patients in the combined intervention group was reduced (P<0.05), and the sEMG of anterior deltoid tract was elevated in the three groups (P<0.05). When compared with the scalp point group and the robot group, in the combined intervention group, after treatment, ADL score and FMA-UA score were higher (P<0.05), ROM of forward flexion, horizontal abduction and horizontal adduction of the affected shoulder joint elevated (P<0.05) and sEMG value of the fasciculi pectoralis major anterior reduced (P<0.05), while which of the anterior deltoid tract was elevated (P<0.05). The cluster needling at scalp points with needle retaining, combined with the training of the upper-limb intelligent rehabilitation robot, improves the upper limb motor function and the range of motion of the shoulder joint in stroke patients during convalescence.

Dynamical network-based evaluation for neuromuscular dysfunction in stroke-induced hemiplegia during standing

BackgroundA given movement requires precise coordination of multiple muscles under the control of center nervous system. However, detailed knowledge about the changing characteristics of neuromuscular control for multi-muscle coordination in post-stroke hemiplegic patients during standing is still lacking. This study aimed to investigate the hemiplegia-linked neuromuscular dysfunction during standing from the perspective of multi-muscle dynamical coordination by utilizing a novel network approach – weighted recurrence network (WRN).MethodsTen male hemiplegic patients with first-ever stroke and 10 age-matched healthy male adults were instructed to stand on a platform quietly for 30 s with eyes opened and eyes closed, respectively. The WRN was constructed based on the surface electromyography signals of 16 muscles from trunk, hips, thighs and calves. Relevant topological parameters, including clustering coefficient (C) and average shortest path length (L), were extracted to evaluate the dynamical coordination of multiple muscles. A measure of node centrality in network theory, degree of centrality (DC), was innovatively introduced to assess the contribution of single muscle in the multi-muscle dynamical coordination. The standing-related assessment metric, center of pressure (COP), was provided by the platform directly.ResultsResults showed that the post-stroke hemiplegic patients stood with remarkably higher similarity of muscle activation and more coupled intermuscular dynamics, characterized by higher C and lower L than the healthy subjects (p < 0.05). The DC values and rankings of back, hip and calf muscles on the affected side were significantly decreased, whereas those on the unaffected side were significantly increased in hemiplegia group compared with the healthy group (p < 0.05). Without visual feedback, subjects exhibited enhanced muscle coordination and increased muscle involvement (p < 0.05). A decrease in C and an increase in L of WRN were observed with decreased COP areas (p < 0.05).ConclusionsThese findings revealed that stroke-induced hemiplegia could significantly influence the neuromuscular control, which was manifested as more coupled intermuscular dynamics, abnormal deactivation of muscles on affected side and compensation of muscles on unaffected side from the perspective of multi-muscle coordination. Enhanced multi-muscle dynamical coordination was strongly associated with impaired postural control. This study provides a novel analytical tool for evaluation of neuromuscular dysfunction and specification of responsible muscles for impaired postural control in stroke-induced hemiplegic patients, and could be potentially applied in clinical practice.