The Effects of Anchoring a Fatiguing Forearm Flexion Task to a High vs. Low Rating of Perceived Exertion on Torque and Neuromuscular Responses.

ABSTRACT: Ortega, DG, Housh, TJ, Smith, RW, Arnett, JE, Neltner, TJ, Schmidt, RJ, and Johnson, GO. The effects of anchoring a fatiguing forearm flexion task to a high versus low rating of perceived exertion on torque and neuromuscular responses. J Strength Cond Res 38(5): e219-e225, 2024-This study examined the torque and neuromuscular responses following sustained, isometric, forearm flexion tasks anchored to 2 ratings of perceived exertion (RPE). Nine men (mean ± SD: age = 21.0 ± 2.4 years; height = 179.5 ± 5.1 cm; body mass = 79.6 ± 11.4 kg) completed maximal voluntary isometric contractions (MVIC) before and after sustained, isometric, forearm flexion tasks to failure anchored to RPE = 2 and RPE = 8. The amplitude (AMP) and mean power frequency (MPF) of the electromyographic (EMG) signal were recorded from the biceps brachii. Normalized torque was divided by normalized EMG AMP to calculate neuromuscular efficiency (NME). A dependent t-test was used to assess the mean difference for time to task failure (TTF). Repeated-measures analysis of variances was used to compare mean differences for MVIC and normalized neuromuscular parameters. There was no significant difference in TTF between RPE = 2 and RPE = 8 (p = 0.713). The MVIC decreased from pretest to posttest at RPE = 2 (p = 0.009) and RPE = 8 (p = 0.003), and posttest MVIC at RPE = 8 was less than that at RPE = 2 (p < 0.001). In addition, NME decreased from pretest to posttest (p = 0.008). There was no change in normalized EMG AMP or EMG MPF (p > 0.05). The current findings indicated that torque responses were intensity specific, but TTF and neuromuscular responses were not. Furthermore, normalized EMG AMP and EMG MPF remained unchanged but NME decreased, likely due to peripheral fatigue and excitation-contraction coupling failure. Thus, this study provides information regarding the neuromuscular responses and mechanisms of fatigue associated with tasks anchored to RPE, which adds to the foundational understanding of the relationship between resistance exercise and the perception of fatigue.

Does Exerting Grasps Involve a Finite Set of Muscle Patterns? A Study of Intra- and Intersubject Variability of Forearm sEMG Signals in Seven Grasp Types.

Surface Electromyography (sEMG) signals are widely used as input to control robotic devices, prosthetic limbs, exoskeletons, among other devices, and provide information about someone's intention to perform a particular movement. However, the redundant action of 32 muscles in the forearm and hand means that the neuromotor system can select different combinations of muscular activities to perform the same grasp, and these combinations could differ among subjects, and even among the trials done by the same subject. In this work, 22 healthy subjects performed seven representative grasp types (the most commonly used). sEMG signals were recorded from seven representative forearm spots identified in a previous work. Intra- and intersubject variability are presented by using four sEMG characteristics: muscle activity, zero crossing, enhanced wavelength and enhanced mean absolute value. The results confirmed the presence of both intra- and intersubject variability, which evidences the existence of distinct, yet limited, muscle patterns while executing the same grasp. This work underscores the importance of utilizing diverse combinations of sEMG features or characteristics of various natures, such as time-domain or frequency-domain, and it is the first work to observe the effect of considering different muscular patterns during grasps execution. This approach is applicable for fine-tuning the control settings of current sEMG devices.

Location of the posterior interosseous nerve in relation to common lateral approaches to the elbow.

PURPOSE: The risk of posterior interosseous nerve (PIN) injury during surgical approaches to the lateral elbow varies depending on the chosen approach, level of dissection, and rotational position of the forearm. Previous studies evaluated the trajectory of the PIN in specific surgical applications to reduce iatrogenic nerve injuries. The goal of this study is to examine the location of the PIN using common lateral approaches with varying forearm rotation. METHODS: The Kaplan, extensor digitorum communis (EDC) split, and Kocher approaches were performed on 18 cadaveric upper extremity specimens. Measurements were recorded with a digital caliper from the radiocapitellar (RC) joint and the lateral epicondyle to the point where the PIN crosses the approach in full supination, neutral, and full pronation with the elbow at 90°. The ratio of the nerve's location in relation to the entire length of the radius was also evaluated to account for different-sized specimens. RESULTS: The PIN was not encountered in the Kocher interval. For Kaplan and EDC split, with the forearm in full supination, the mean distance from the lateral epicondyle to the PIN was 52.0 ± 6.1 mm and 59.1 ± 5.5 mm, respectively, and the mean distance from the RC joint to the PIN was 34.7 ± 5.5 mm and 39.3 ± 4.7 mm, respectively; with the forearm in full pronation, the mean distance from the lateral epicondyle to the PIN was 63.3 ± 9.7 mm and 71.4 ± 8.3 mm, respectively, and the mean distance from the RC joint to the PIN was 44.2 ± 7.7 mm and 51.1 ± 8.7 mm, respectively. CONCLUSIONS: The PIN is closer to the lateral epicondyle and RC joint in the Kaplan than EDC split approach and is not encountered during the Kocher approach. The PIN was not encountered within 26 mm from the RC joint and 39 mm from the lateral epicondyle in any approach and forearm position and is generally safe from iatrogenic injury within these distances.

Developing RPC-Net: Leveraging High-Density Electromyography and Machine Learning for Improved Hand Position Estimation.

OBJECTIVE: The purpose of this study was to develop and evaluate the performance of RPC-Net (Recursive Prosthetic Control Network), a novel method using simple neural network architectures to translate electromyographic activity into hand position with high accuracy and computational efficiency. METHODS: RPC-Net uses a regression-based approach to convert forearm electromyographic signals into hand kinematics. We tested the adaptability of the algorithm to different conditions and compared its performance with that of solutions from the academic literature. RESULTS: RPC-Net demonstrated a high degree of accuracy in predicting hand position from electromyographic activity, outperforming other solutions with the same computational cost. Including previous position data consistently improved results across subjects and conditions. RPC-Net showed robustness against a reduction in the number of electromyography electrodes used and shorter input signals, indicating potential for further reduction in computational cost. CONCLUSION: The results demonstrate that RPC-Net is capable of accurately translating forearm electromyographic activity into hand position, offering a practical and adaptable tool that may be accessible in clinical settings. SIGNIFICANCE: The development of RPC-Net represents a significant advancement. In clinical settings, its application could enable prosthetic devices to be controlled in a way that feels more natural, improving the quality of life for individuals with limb loss.

Comparison of finger flexion strength and muscular recovery of male lead sport climbers across climbing classes.

BACKGROUND/OBJECTIVE: The purpose of this study was to compare finger flexor strength (FS), finger flexor muscle recovery (FR), and forearm circumference (FC) across three different climbing classes in male lead sport climbers. METHODS: A total of 37 male lead sport climbers were classified into low (LC), intermediate (IC), and advanced classes (AC) categories according to the International Rock Climbing Research Association (IRCRA) Scale. All participants measured FS three times for both open grip (OG) and crimp grip (CG). Following FS measurement, the FR was observed immediately after the all-out training. The FC was measured twice using an inelastic tape. RESULTS: The FS differed significantly across climbing classes for both grip styles and hands, regardless of dominant hand, with the higher classes showing greater FS (all, p ≤ 0.001). FR was significantly higher in AC compared to IC and LC at 5 min (all, p ≤ 0.001), 10 min (all, p ≤ 0.005) and 15 min (all, p ≤ 0.005). The FC showed significant differences with climbing classes for both forearms. CONCLUSION: Climbing classes are associated with differences in FS, with higher class corresponding to greater FS. Similarly, climbing classes are linked to FR and FC, with higher classes being associated with faster recovery and larger FC.

Development of the Biomech-Wrist: A 3-DOF Exoskeleton for Rehabilitation and Training of Human Wrist.

This work describes a three-degrees-of-freedom rehabilitation exoskeleton robot for wrist articulation movement: the Biomech-Wrist. The proposed development includes the design requirements based on the biomechanics and anthropometric features of the upper limb, the mechanical design, electronic instrumentation, software design, manufacturing, control algorithm implementation, and the experimental setup to validate the functionality of the system. The design requirements were set to achieve human wrist-like movements: ulnar-radial deviation, flexion-extension, and pronation-supination. Then, the mechanical design considers the human range of motion with proper torques, velocities, and geometry. The manufacturing consists of 3D-printed elements and tubular aluminum sections resulting in lightweight components with modifiable distances. The central aspect of the instrumentation is the actuation system consisting of three brushless motors and a microcontroller for the control implementation. The proposed device was evaluated by considering two control schemes to regulate the trajectory tracking on each joint. The first scheme was the conventional proportional-derivative controller, whereas the second was proposed as a first-order sliding mode. The results show that the Biomech-Wrist exoskeleton can perform trajectory tracking with high precision ( RMSEmax = 0.0556 rad) when implementing the sliding mode controller.

Multipoint surface electromyography measurement using bull's-eye electrodes for wide-area topographic analysis.

BACKGROUND: Surface electromyography (sEMG) is primarily used to analyze individual and neighboring muscle activity. However, using a broader approach can enable simultaneous measurement of multiple muscles, which is essential for understanding muscular coordination. Using the "bull's-eye electrode," which allows bipolar derivation without directional dependence, enables wide-area multipoint sEMG measurements. This study aims to establish a multipoint measurement system and demonstrate its effectiveness and evaluates forearm fatigue and created topographic maps during a grasping task. METHODS: Nine healthy adults with no recent arm injuries or illnesses participated in this study. They performed grasping tasks using their dominant hand, while bull's-eye electrodes recorded their muscle activity. To validate the effectiveness of the system, we calculated the root mean squares of muscle activity and entropy, an indicator of muscle activity distribution, and compared them over time. RESULTS: The entropy analysis demonstrated a significant time-course effect with increased entropy over time, suggesting increased forearm muscle uniformity, which is possibly indicative of fatigue. Topographic maps visually displayed muscle activity, revealing notable intersubject variations. DISCUSSION: Bull's-eye electrodes facilitated the capture of nine homogeneous muscle activity points, enabling the creation of topographic images. The entropy increased progressively, suggesting an adaptive muscle coordination response to fatigue. Despite some limitations, such as inadequate measurement of the forearm muscles' belly, the system is an unconventional measurement method. CONCLUSION: This study established a robust system for wide-area multipoint sEMG measurements using a bull's-eye electrode setup. This system effectively evaluates muscle fatigue and provides a comprehensive topographic view of muscle activity. These results mark a significant step towards developing a future multichannel sEMG system with enhanced measurement points and improved wearability. TRIAL REGISTRATION: This study was approved by the Ethics Committee of Chiba University Graduate School of Engineering (acceptance number: R4-12, Acceptance date: November 04, 2022).

A Wireless 2-Channel Layered EMG/NIRS Sensor System for Local Muscular Activity Evaluation.

A wireless 2-channel layered sensor system that enables electromyography (EMG) and near-infrared spectroscopy (NIRS) measurements at two local positions was developed. The layered sensor consists of a thin silver electrode and a photosensor consisting of a photoemitting diode (LED) or photodiode (PD). The EMG and NIRS signals were simultaneously measured using a pair of electrodes and photosensors for the LED and PD, respectively. Two local muscular activities are presented in detail using layered sensors. In the experiments, EMG and NIRS signals were measured for isometric constant and ramp contractions at each forearm using layered sensors. The results showed that local muscle activity analysis is possible using simultaneous EMG and NIRS signals at each local position.

Elasticity of the Forearm Flexor-Pronator Muscles as a Risk Factor for Medial Elbow Injuries in Young Baseball Players: A Prospective Cohort Study of 314 Players.

BACKGROUND: Young baseball players with medial elbow injuries are known to have high forearm flexor-pronator muscle elasticity; however, the causal relationship between forearm muscle elasticity and the occurrence of medial elbow injuries remains unclear. PURPOSE/HYPOTHESIS: The purpose of this study was to determine whether the forearm flexor-pronator muscle elasticity is a risk factor for medial elbow injury in young baseball players. It was hypothesized that high flexor carpi ulnaris (FCU) elasticity would be a risk factor for medial elbow injuries. STUDY DESIGN: Cohort study; Level of evidence, 2. METHODS: Young baseball players (aged 9-12 years) with no history of elbow injuries underwent examination during which the strain ratios (SRs) of the pronator teres, flexor digitorum superficialis, and FCU muscles were measured using ultrasound strain elastography as an index of elasticity. Additionally, the participants completed a questionnaire assessing age, height, weight, months of experience as a baseball player, position in baseball, number of training days per week, number of throws per day, and elbow pain during throwing; then the range of motion of the shoulder and hip internal/external rotation were measured. One year after the baseline measurements, the occurrence of new medial elbow injuries was evaluated. Multivariate logistic regression analysis was subsequently conducted to determine risk factors for medial elbow injuries. Cutoff points for significant SR values obtained from the multivariate logistic regression analysis were calculated using the receiver operating characteristic curve. RESULTS: Of the 314 players, 76 (24.2%) were diagnosed with medial elbow injury. Multivariate logistic regression analysis showed that a 0.1 increase in the SR of the FCU muscle (odds ratio [OR], 1.211; 95% CI, 1.116-1.314) and number of throws per day (OR, 1.012; 95% CI, 1.001-1.022) were significantly associated with medial elbow injuries. Receiver operating characteristic curve analyses revealed that the optimal cutoff for the SR of the FCU muscle was 0.920 (area under the curve, 0.694; sensitivity, 75.0%; specificity, 56.7%). CONCLUSION: Increased FCU elasticity is a risk factor for medial elbow injury. Evaluation of the FCU elasticity may be useful in identifying young baseball players at high risk of medial elbow injuries and may facilitate prevention of medial elbow injury. As shown by the results of multivariate logistic regression analysis, FCU elasticity itself may be useful in identifying young baseball players at high risk of elbow injuries. However, we believe that other factors, such as the number of pitches per day, need to be considered to improve its accuracy.

Effect of Forearm Postures and Elbow Joint Angles on Elbow Flexion Torque and Mechanomyography in Neuromuscular Electrical Stimulation of the Biceps Brachii.

Neuromuscular electrical stimulation plays a pivotal role in rehabilitating muscle function among individuals with neurological impairment. However, there remains uncertainty regarding whether the muscle's response to electrical excitation is affected by forearm posture, joint angle, or a combination of both factors. This study aimed to investigate the effects of forearm postures and elbow joint angles on the muscle torque and MMG signals. Measurements of the torque around the elbow and MMG of the biceps brachii (BB) muscle were conducted in 36 healthy subjects (age, 22.24 ± 2.94 years; height, 172 ± 0.5 cm; and weight, 67.01 ± 7.22 kg) using an in-house elbow flexion testbed and neuromuscular electrical stimulation (NMES) of the BB muscle. The BB muscle was stimulated while the forearm was positioned in the neutral, pronation, or supination positions. The elbow was flexed at angles of 10°, 30°, 60°, and 90°. The study analyzed the impact of the forearm posture(s) and elbow joint angle(s) on the root-mean-square value of the torque (TQRMS). Subsequently, various MMG parameters, such as the root-mean-square value (MMGRMS), the mean power frequency (MMGMPF), and the median frequency (MMGMDF), were analyzed along the longitudinal, lateral, and transverse axes of the BB muscle fibers. The test-retest interclass correlation coefficient (ICC21) for the torque and MMG ranged from 0.522 to 0.828. Repeated-measure ANOVAs showed that the forearm posture and elbow flexion angle significantly influenced the TQRMS (p < 0.05). Similarly, the MMGRMS, MMGMPF, and MMGMDF showed significant differences among all the postures and angles (p < 0.05). However, the combined main effect of the forearm posture and elbow joint angle was insignificant along the longitudinal axis (p > 0.05). The study also found that the MMGRMS and TQRMS increased with increases in the joint angle from 10° to 60° and decreased at greater angles. However, during this investigation, the MMGMPF and MMGMDF exhibited a consistent decrease in response to increases in the joint angle for the lateral and transverse axes of the BB muscle. These findings suggest that the muscle contraction evoked by NMES may be influenced by the interplay between actin and myosin filaments, which are responsible for muscle contraction and are, in turn, influenced by the muscle length. Because restoring the function of limbs is a common goal in rehabilitation services, the use of MMG in the development of methods that may enable the real-time tracking of exact muscle dimensional changes and activation levels is imperative.

The Effects of Dental Hygiene Instrument Handles on Muscle Activity Production.

Purpose The objective of this study was to compare the effects of ten commercially available instrument handle designs' mass and diameter on forearm muscle activity during a simulated periodontal scaling experience.Methods A convenience sample of 25 registered dental hygienists were recruited for this IRB-approved study. Ten commercially available instruments were categorized into four groups based on their masses and diameters: large diameter/light mass, small diameter/light mass, large diameter/heavy mass, and small diameter/heavy mass. Participants were randomized to four instruments with one from each group. Participants scaled with each instrument in a simulated oral environment while muscle activity was collected using surface electromyography. Muscle activity was compared among the four instrument group types.Results Muscle activity of the flexor digitorum superficialis was not significantly influenced by instrument mass (p=0.60) or diameter (p=0.15). Flexor pollicis longus muscle activity was not significantly influenced by instrument mass (p=0.81); diameter had a significant effect (p=0.001) with smaller diameter instruments producing more muscle activity. For the extensor digitorum communis and extensor carpi radialis brevis, instrument mass did not significantly affect muscle activity (p=0.64, p=0.43), while diameter narrowly failed to reach significance for both muscles (p=0.08, p=0.08); muscle activity for both muscles increased with smaller diameter instruments.Conclusion Results from this study indicate instrument diameter is more influential than mass on muscle activity generation; small diameter instruments increased muscle activity generation when compared to large diameter instruments. Future research in real-world settings is needed to determine the clinical impact of these findings.

The effects of dental hygiene instrument handles on muscle activity production.

OBJECTIVE: The objective of this study was to compare the effects of 10 commercially available instrument handle designs' mass and diameter on forearm muscle activity during a simulated periodontal scaling experience. METHODS: A convenience sample of 25 registered dental hygienists was recruited for this IRB-approved study. Ten commercially available instruments were categorized into four groups based on their masses and diameters: large diameter/light mass, small diameter/light mass, large diameter/heavy mass and small diameter/heavy mass. Participants were randomized to four instruments, one from each group. Participants scaled with each instrument in a simulated oral environment while muscle activity was collected using surface electromyography. Muscle activity was compared among the four instrument group types. RESULTS: Muscle activity of the flexor digitorum superficialis was not significantly influenced by instrument mass (p = 0.60) or diameter (p = 0.15). Flexor pollicis longus muscle activity was not significantly influenced by instrument mass (p = 0.81); diameter had a significant effect (p = 0.001), with smaller diameter instruments producing more muscle activity. For the extensor digitorum communis and extensor carpi radialis brevis, instrument mass did not significantly affect muscle activity (p = 0.64, p = 0.43), while diameter narrowly failed to reach significance for both muscles (p = 0.08, p = 0.08); muscle activity for both muscles increased with smaller diameter instruments. CONCLUSION: Results from this study indicate instrument diameter is more influential than mass on muscle activity generation; small diameter instruments increased muscle activity generation when compared to large diameter instruments. Future research in real-world settings is needed to determine the clinical impact of these findings.

Novel Wearable HD-EMG Sensor With Shift-Robust Gesture Recognition Using Deep Learning.

In this work, we present a hardware-software solution to improve the robustness of hand gesture recognition to confounding factors in myoelectric control. The solution includes a novel, full-circumference, flexible, 64-channel high-density electromyography (HD-EMG) sensor called EMaGer. The stretchable, wearable sensor adapts to different forearm sizes while maintaining uniform electrode density around the limb. Leveraging this uniformity, we propose novel array barrel-shifting data augmentation (ABSDA) approach used with a convolutional neural network (CNN), and an anti-aliased CNN (AA-CNN), that provides shift invariance around the limb for improved classification robustness to electrode movement, forearm orientation, and inter-session variability. Signals are sampled from a 4×16 HD-EMG array of electrodes at a frequency of 1 kHz and 16-bit resolution. Using data from 12 non-amputated participants, the approach is tested in response to sensor rotation, forearm rotation, and inter-session scenarios. The proposed ABSDA-CNN method improves inter-session accuracy by 25.67% on average across users for 6 gesture classes compared to conventional CNN classification. A comparison with other devices shows that this benefit is enabled by the unique design of the EMaGer array. The AA-CNN yields improvements of up to 63.05% accuracy over non-augmented methods when tested with electrode displacements ranging from -45 ° to +45 ° around the limb. Overall, this article demonstrates the benefits of co-designing sensor systems, processing methods, and inference algorithms to leverage synergistic and interdependent properties to solve state-of-the-art problems.

sEMG-based prediction of human forearm movements utilizing a biomechanical model based on individual anatomical/ physiological measures and a reduced set of optimization parameters.

For assistive devices such as active orthoses, exoskeletons or other close-to-body robotic-systems, the immediate prediction of biological limb movements based on biosignals in the respective control system can be used to enable intuitive operation also by untrained users e.g. in healthcare, rehabilitation or industrial scenarios. Surface electromyography (sEMG) signals from the muscles that drive the limbs can be measured before the actual movement occurs and, hence, can be used as source for predicting limb movements. The aim of this work was to create a model that can be adapted to a new user or movement scenario with little measurement and computing effort. Therefore, a biomechanical model is presented that predicts limb movements of the human forearm based on easy to measure sEMG signals of the main muscles involved in forearm actuation (lateral and long head of triceps and short and long head of biceps). The model has 42 internal parameters of which 37 were attributed to 8 individually measured physiological measures (location of acromion at the shoulder, medial/lateral epicondyles as well as olecranon at the elbow, and styloid processes of radius/ulna at the wrist; maximum muscle forces of biceps and triceps). The remaining 5 parameters are adapted to specific movement conditions in an optimization process. The model was tested in an experimental study with 31 subjects in which the prediction quality of the model was assessed. The quality of the movement prediction was evaluated by using the normalized mean absolute error (nMAE) for two arm postures (lower, upper), two load conditions (2 kg, 4 kg) and two movement velocities (slow, fast). For the resulting 8 experimental combinations the nMAE varied between nMAE = 0.16 and nMAE = 0.21 (lower numbers better). An additional quality score (QS) was introduced that allows direct comparison between different movements. This score ranged from QS = 0.25 to QS = 0.40 (higher numbers better) for the experimental combinations. The above formulated aim was achieved with good prediction quality by using only 8 individual measurements (easy to collect body dimensions) and the subsequent optimization of only 5 parameters. At the same time, just easily accessible sEMG measurement locations are used to enable simple integration, e.g. in exoskeletons. This biomechanical model does not compete with models that measure all sEMG signals of the muscle heads involved in order to achieve the highest possible prediction quality.

Effects of the attachment method of the stimulating electrodes Nihon-Kohden NM-345Y™ and changes in forearm position on stimulus current values during calibration in electromyography-based neuromuscular monitoring: a single-center experimental study.

PURPOSE: The traditionally recommended method for attaching electromyography (EMG) electrodes (NM-345Y™) during EMG-based neuromuscular monitoring developed by Nihon-Kohden may decrease the monitoring accuracy when forearm limb position changes. This study investigated methods for attaching stimulating electrodes that maintained stable EMG-based neuromuscular monitoring accuracy, regardless of forearm limb position changes. METHODS: This single-center experimental study recruited 28 healthy adults from October 2022 to December 2022. The NM-345Y™ was attached to the forearm using three patterns: Pattern N, electrodes attached according to the attachment pattern recommended by Nihon-Kohden; Pattern U, electrodes attached along the ulnar nerve identified using an ultrasound device; Pattern C, electrodes attached where the ulnar nerve crosses the line connecting the centers of the anode and cathode of the stimulating electrodes. The stimulus current values during calibration were measured at three forearm positions for each attachment pattern: supination 90 degrees; pronation 0 degrees; pronation 90 degrees. The differences in stimulus current values caused by forearm position changes were calculated as the difference between values at supination 90 degrees and pronation 0 degrees and between values at supination 90 degrees and pronation 90 degrees. RESULTS: Pattern C showed significantly smaller differences than Pattern N between the stimulus current values at supination 90 degrees and pronation 0 degrees (p = 0.018) and between the stimulus current values at supination 90 degrees and pronation 90 degrees (p = 0.008). CONCLUSION: Crossing the ulnar nerve with the line connecting the anode and cathode of the stimulating electrodes may stabilize EMG-based neuromuscular monitoring accuracy.

Longitudinal changes of grip strength and forearm muscle thickness in young children.

Background: Grip strength is a marker of future health conditions and is mainly generated by the extrinsic flexor muscles of the fingers. Therefore, whether or not there is a relationship between grip strength and forearm muscle size is vital in considering strategies for grip strength development during growth. Thus, this study aimed to examine the association between changes in grip strength and forearm muscle thickness in young children. Methods: Two hundred eighteen young children (104 boys and 114 girls) performed maximum voluntary grip strength and ultrasound-measured muscle thickness measurements in the right hand. Two muscle thicknesses were measured as the perpendicular distance between the adipose tissue-muscle interface and muscle-bone interface of the radius (MT-radius) and ulna (MT-ulna). All participants completed the first measurement and underwent a second measurement one year after the first one. Results: There were significant (P < 0.001) within-subject correlations between MT-ulna and grip strength [r = 0.50 (0.40, 0.60)] and MT-radius and grip strength [r = 0.59 (0.49, 0.67)]. There was no significant between-subject correlation between MT-ulna and grip strength [r = 0.07 (-0.05, 0.20)], but there was a statistically significant (P < 0.001) between-subject relationship between MT-radius and grip strength [r = 0.27 (0.14, 0.39)]. Conclusion: Although we cannot infer causation from the present study, our findings suggest that as muscle size increases within a child, so does muscle strength. Our between-subject analysis, however, suggests that those who observed the greatest change in muscle size did not necessarily get the strongest.

Effect of Forearm and Elbow Joint Positions on Ulnar Nerve Conduction Velocity: A Study of Throwers, Archers, and Non-Athletes.

Background: The intensive physical regimen followed by throwers and archers can impose stress on the elbow and hand in particular positions, which may increase the risk of developing peripheral nerve disorders and symptoms like pain and numbness. Purpose: The purpose of the study is to investigate the effect of forearm and elbow joint positions on ulnar nerve conduction velocity in throwers, archers, and non-athletes. Method: Total 34 subjects both males and females were included with body mass index (BMI) between 18.5 and 24.9 kg/m2. Nerve conduction study (NeuroStim NS2 EMG/NCV/EP System) was used for measuring ulnar nerve conduction velocity (NCV) across elbow joint at different angles (0° elbow extension, 45°, 90°, and 120° elbow flexion) with different forearm positions. Result: Repeated Measure Analysis of Variance (RMANOVA) revealed that there was a statistically significant difference in mean values of ulnar NCV at different angles, forearm positions & groups (p < .05). Conclusion: The forearm and elbow positions can have a significant impact on ulnar NCV, especially in athletes who perform repetitive upper limb motions. Results showed that the archers had significantly slower NCV than throwers and non-athletes at 90° of elbow flexion and forearm pronation.

A Transformer-Based Multi-Task Learning Framework for Myoelectric Pattern Recognition Supporting Muscle Force Estimation.

Simultaneous implementation of myoelectric pattern recognition and muscle force estimation is highly demanded in building natural gestural interfaces but a challenging task due to the gesture classification accuracy degradation under varying muscle strengths. To address this problem, a novel method using transformer-based multi-task learning (MTL-Transformer) for the prediction of both myoelectric patterns and corresponding muscle strengths was proposed to describe the inherent characteristics of an individual gesture pattern under different force conditions, thereby improving the accuracy of myoelectric pattern recognition. In addition, the transformer model enabled the characterization of long-term temporal correlations to ensure precise and smooth estimation of the muscle force. The performance of the proposed MTL-Transformer framework was evaluated via experiments of classifying eleven hand gestures and estimating the corresponding muscle force simultaneously, using high-density surface electromyogram (HD-sEMG) recordings from forearm flexor muscles of eleven intact-limbed subjects. The MTL-Transformer framework yielded high classification accuracy (98.70±1.21%) and low root mean square deviation (12.59±2.76%), and outperformed other two common temporally modelling methods significantly ( ) in terms of both improved gesture recognition accuracies and reduced muscle force estimation errors. The MTL-Transformer framework is demonstrated as an effective solution for simultaneous implementation of myoelectric pattern recognition and muscle force estimation. This study promotes the development of robust and smooth myoelectric control systems, with wide applications in gestural interfaces, prosthetic and orthotic control.

The effect of local vibration applied to the forearm extensor muscles on hand function and muscle activation in stroke patients: a randomized controlled study.

OBJECTIVE: This study aims to reveal the effect of low-frequency local vibration applied to the forearm extensor muscles on stroke patients' muscle activation and hand functions. METHODS: Twenty-four stroke patients were randomized to the vibration group (n = 12) or control group (n = 12). The vibration was applied at a 30 Hz frequency to the forearm extensor muscles with a local vibration device three days a week after the routine, conventional physical therapy sessions for four weeks. Six vibration sets were applied, including one vibration for one minute and a rest for 2 min. Routine, traditional physical therapy was used for the control group in 60-min sessions for 4 weeks. Patients were assessed for muscle activation with surface electromyography (MVC) and The Wolf Motor Function Test (WMFT), Functional Independent Test (FIM) was applied to all patients before and after treatment. RESULTS: As a result of our study, MVC measurement, WMFT and FIM scores of the vibration group showed more improvement than the control group. Measurement results of vibration group; While MVC measurement increased from 10.21 to 13.79, WMFT-Functional Ability score increased from 42 to 50, WMFT-Performance Time duration increased from 68.78 to 61.83, and FIM score increased from 74.5 to 83. and the measurement results of the control group; MVC measurement increased from 12.28 to 12.22, WMFT-Functional Ability score increased from 48.5 to 51, WMFT-Performance Time duration increased from 70.39 to 70.61, and FIM score increased from 72.5 to 80.5. CONCLUSION: It was concluded that low-frequency local vibration applied to the forearm extensor muscles improve forearm extensor muscle activation and hand motor function. CLINICAL TRIAL REGISTRATION: NCT04562220.

Gender differences on effects of forearm rotation on compressive stiffness of flexor carpi ulnaris during submaximal handgrip contractions.

Little is known about gender differences in stiffness of forearm muscles during voluntary actions. This study aimed to investigate the effect of forearm rotation on flexor carpi ulnaris (FCU) stiffness in men and women during submaximal handgrip contractions. During a single session, measurements were made on 20 young participants (9 females). Two positions of the forearm were compared in random order with the elbow flexed 90 degrees: (i) neutral position and (ii) maximal supination. In each position, participants performed two submaximal handgrip contractions at 25% and 50% of maximal voluntary contraction, while compressive stiffness was collected using a hand myometer (MyotonPRO). A mixed repeated measurement ANOVA was applied to assess the interaction between gender, forearm position, and contraction intensity. The FCU stiffness is affected by handgrip contraction intensity (p < 0.001), gender (p < 0.001), BMI (p = 0.009), and forearm rotation (p = 0.007). Only the gender factor was found to have significant interaction with forearm rotation (p = 0.037). Men's FCU was stiffer than women's in both positions and contraction intensities (p < 0.05). Only in men a significant increase in FCU stiffness was observed when comparing contraction intensities at both forearm positions (p < 0.05), as well as when the forearm was rotated from neutral to supine at both intensities (p < 0.05). In conclusion, FCU stiffness during handgrip contraction differed significantly between men and women. Women have fewer stiffness changes in FCU when performing different levels of handgrip contraction. We also observed that only men increased FCU stiffness by changing the forearm position from neutral to supine position for both handgrip intensities.