Comparison of the forearm rotation restriction capacities of four upper-extremity immobilization methods: there is no difference between single and double sugar tong splinting.

BACKGROUND: The aim of this study was to compare the effects of four different immobilization methods [single sugar tong splint (SSTS), double sugar tong splint (DSTS), short arm cast (SAC), and long arm cast (LAC)] commonly used for restricting forearm rotation in the upper extremity. METHODS: Forty healthy volunteers were included in the study. Dominant extremities were used for measurements. Basal pronation and supination of the forearm were measured with a custom-made goniometer, and the total rotation arc was calculated without any immobilization. Next, the measurements were repeated with the SAC, LAC, SSTS and DSTS. Each measurement was compared to the baseline value, and the percentage of rotation restriction was calculated. RESULTS: The most superior restriction rates were observed for the LAC (p = 0.00). No statistically significant difference was detected between the SSTS and DSTS in terms of the restriction of supination, pronation or the rotation arc (p values, 1.00, 0.18, and 0.50, respectively). Statistically significant differences were not detected between the SAC and the SSTS in any of the three parameters (p values, 0.25; 1.00; 1.00, respectively). When the SAC and DSTS were compared, while there was no significant difference between the two methods in pronation (p = 0.50), a statistically significant difference was detected in supination (p = 0.01) and in the total rotation arc (p = 0.03). CONCLUSION: The LAC provides superior results in restricting forearm rotation. The SAC and SSTS had similar effects on forearm rotation. The DSTS, which contains, in addition to the SSTS, a sugar tong portion above the elbow, does not provide additional rotational stability.

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.

Impact of repetitive mouse clicking on forearm muscle fatigue and mouse aiming performance.

Exercise induced performance fatigue has been shown to impair many aspects of fine motor function in the distal upper limb. However, most fatiguing protocols do not reflect the conditions experienced with computer use. The purpose of this study was to determine how a prolonged, low-force mouse clicking fatigue protocol impacts performance fatigue of the distal upper limb for gamers and non-gamers. Participants completed a total of 1 h of mouse clicking at 5 clicks per second. Muscle fatigue and performance were intermittently assessed. RMS amplitude increased for the forearm flexors throughout the fatigue protocol. Accuracy decreased following the first bout of clicking and returned to baseline values after 40-min. EDC and ECU displayed the greatest muscle activity while aiming, producing 11.4% and 12.9% of MVC, respectively. These findings indicate that mouse clicking may not result in performance fatigue, however, high levels of extensor activity may explain common injuries among gamers.

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.

Exploratory analysis using machine learning algorithms to predict pinch strength by anthropometric and socio-demographic features.

Objectives. This study examines the role of different machine learning (ML) algorithms to determine which socio-demographic factors and hand-forearm anthropometric dimensions can be used to accurately predict hand function. Methods. The cross-sectional study was conducted with 7119 healthy Iranian participants (3525 males and 3594 females) aged 10-89 years. Seventeen hand-forearm anthropometric dimensions were measured by JEGS digital caliper and a measuring tape. Tip-to-tip, key and three-jaw chuck pinches were measured using a calibrated pinch gauge. Subsequently, 21 features pertinent to socio-demographic factors and hand-forearm anthropometric dimensions were used for classification. Furthermore, 12 well-known classifiers were implemented and evaluated to predict pinches. Results. Among the 21 features considered in this study, hand length, stature, age, thumb length and index finger length were found to be the most relevant and effective components for each of the three pinch predictions. The k-nearest neighbor, adaptive boosting (AdaBoost) and random forest classifiers achieved the highest classification accuracy of 96.75, 86.49 and 84.66% to predict three pinches, respectively. Conclusions. Predicting pinch strength and determining the predictive hand-forearm anthropometric and socio-demographic characteristics using ML may pave the way to designing an enhanced tool handle and reduce common musculoskeletal disorders of the hand.

In-Vivo Electrical Properties Estimation of Biological Tissues by Means of a Multi-Step Microwave Tomography Approach.

The accurate quantitative estimation of the electromagnetic properties of tissues can serve important diagnostic and therapeutic medical purposes. Quantitative microwave tomography is an imaging modality that can provide maps of the in-vivo electromagnetic properties of the imaged tissues, i.e. both the permittivity and the electric conductivity. A multi-step microwave tomography approach is proposed for the accurate retrieval of such spatial maps of biological tissues. The underlying idea behind the new imaging approach is to progressively add details to the maps in a step-wise fashion starting from single-frequency qualitative reconstructions. Multi-frequency microwave data is utilized strategically in the final stage. The approach results in improved accuracy of the reconstructions compared to inversion of the data in a single step. As a case study, the proposed workflow was tested on an experimental microwave data set collected for the imaging of the human forearm. The human forearm is a good test case as it contains several soft tissues as well as bone, exhibiting a wide range of values for the electrical properties.

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.

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.

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.

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.

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.

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).

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.

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.

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.