High-density Surface and Intramuscular EMG Data from the Tibialis Anterior During Dynamic Contractions.

Valid approaches for interfacing with and deciphering neural commands related to movement are critical to understanding muscular coordination and developing viable prostheses and wearable robotics. While electromyography (EMG) has been an established approach for mapping neural input to mechanical output, there is a lack of adaptability to dynamic environments due to a lack of data from dynamic movements. This report presents data consisting of simultaneously recorded high density surface EMG, intramuscular EMG, and joint dynamics from the tibialis anterior during static and dynamic muscle contractions. The dataset comes from seven subjects performing three to five trials each of different types of muscle contractions, both static (isometric) and dynamic (isotonic and isokinetic). Each subject was seated in an isokinetic dynamometer such that ankle movement was isolated and instrumented with four fine wire electrodes and a 126-electrode surface EMG grid. This data set can be used to (i) validate methods for extracting neural signals from surface EMG, (ii) develop models for predicting torque output, or (iii) develop classifiers for movement intent.

Torque Estimation Using Neural Drive for a Concentric Contraction.

The scope and relevance of wearable robotics spans across a number of research fields with a variety of applications. A challenge across these research areas is improving user-interface control. One established approach is using neural control interfaces derived from surface electromyography (sEMG). Although there has been some success with sEMG controlled prosthetics, the coarse nature of traditional sEMG processing has limited the development of fully functional prosthetics and wearable robotics. To solve this problem, blind source separation (BSS) techniques have been implemented to extract the user's movement intent from high-density sEMG (HDsEMG) measurements; however, current methods have only been well validated during static, low-level muscle contractions, and it is unclear how they will perform during movement. In this paper we present a neural drive based method for predicting output torque during a constant force, concentric contraction. This was achieved by modifying an existing HDsEMG decomposition algorithm to decompose 1 sec. overlapping windows. The neural drive profile was computed using both rate coding and kernel smoothing. Neither rate coding nor kernel smoothing performed as well as HDsEMG amplitude estimation, indicating that there are still significant limitations in adapting current methods to decompose dynamic contractions, and that sEMG amplitude estimation methods still remain highly reliable estimators.

Response Complexity Reduces Errors on a Response Inhibition Task.

OBJECTIVE: The purpose of this investigation was to elucidate the role of button-response complexity to targets in a response inhibition task. BACKGROUND: Response inhibition is the ability to correctly inhibit an overt response to a target. The U.S. military is actively pursuing development of armed, combat robots as a force multiplier, which may present challenges to operators of combat robots in the form of response inhibition errors. METHOD: A total of 15 participants completed two 51-min versions of a modified sustained attention to response task (SART). Participants were outfitted with an electrocardiogram to index heart-rate variability and completed the NASA-Task Load Index (NASA-TLX) to index workload. RESULTS: The results demonstrated that the complex SART reduced errors of commission (4%) and slowed response times (874 ms) to correct Go targets relative to the simple SART (14%, 739 ms). The NASA-TLX did not show differences between the modified SARTs; however, heart-rate variability did demonstrate that Soldiers had an increased autonomic stress response to the complex SART. CONCLUSION: Increasing the behavioral response requirement during a response inhibition task can decrease errors of commission; however, it comes at the cost of slower response times to target stimuli. Heart-rate variability may provide better insight into objective workload relative to subjective measures. APPLICATION: The use of complex behavioral responses may provide a viable option to reduce potential "friendly fire" or collateral damage by Soldiers remotely engaging a target-rich environment.

motoRneuron: an open-source R toolbox for time-domain motor unit analyses.

Motor unit synchronization is the tendency of motor neurons and their associated muscle fibers to discharge near-simultaneously. It has been theorized as a control mechanism for force generation by common excitatory inputs to these motor neurons. Magnitude of synchronization is calculated from peaks in cross-correlation histograms between motor unit discharge trains. However, there are many different methods for detecting these peaks and even more indices for calculating synchronization from them. Methodology is diverse, typically laboratory-specific and requires expensive software, like Matlab or LabView. This lack of standardization makes it difficult to draw definitive conclusions about motor unit synchronization. A free, open-source toolbox, "motoRneuron", for the R programming language, has been developed which contains functions for calculating time domain synchronization using different methods found in the literature. The objective of this paper is to detail the toolbox's functionality and present a case study showing how the same synchronization index can differ when different methods are used to compute it. A pair of motor unit action potential trains were collected from the forearm during a isometric finger flexion task using fine wire electromyography. The motoRneuron package was used to analyze the discharge time of the motor units for time-domain synchronization. The primary function "mu_synch" automatically performed the cross-correlation analysis using three different peak detection methods, the cumulative sum method, the z-score method, and a subjective visual method. As function parameters defined by the user, only first order recurrence intervals were calculated and a 1 ms bin width was used to create the cross correlation histogram. Output from the function were six common synchronization indices, the common input strength (CIS), k', k' - 1, E, S, and Synch Index. In general, there was a high degree of synchronization between the two motor units. However, there was a varying degree of synchronization between methods. For example, the widely used CIS index, which represents a rate of synchronized discharges, shows a 45% difference between the visual and z-score methods. This singular example demonstrates how a lack of consensus in motor unit synchronization methodologies may lead to substantially differing results between studies. The motoRneuron toolbox provides researchers with a standard interface and software to examine time-domain motor unit synchronization.

The effect of imperceptible Gaussian tendon vibration on the Hoffmann reflex.

Imperceptible vibratory Gaussian noise stimulation to the periphery is frequently being applied to humans to enhance motor performance. It is commonly theorized that this stimulation creates a Stochastic Resonance-like effect across both sensory and motor systems, but this idea has no empirical support. In contrast, there is substantial work showing that tendon vibration can be both excitatory and inhibitory on the lower motor neuron output. In this work, we demonstrate that delivery of imperceptible vibratory Gaussian noise stimulation to the wrist flexor tendons results in a 27% increase in excitability of the lower motor neuron pool in the median nerve, as evidenced by changes in the Hoffmann reflex. We argue that the well-documented tonic vibration reflex is a sufficient mechanistic explanation for the behavioral changes observed during the introduction of vibratory noise stimulation.

Differences in muscle contraction onset as determined by ultrasound and electromyography.

INTRODUCTION: We characterize the agreement between the timing of muscle contraction onset detected by surface electromyography (sEMG), fine wire EMG (fwEMG), and motion-mode (M-mode) ultrasound for improved interpretations of clinical outcomes. METHODS: Eighteen healthy adults participated. Differences in contraction onset were compared between sEMG, fwEMG, and M-mode ultrasound collected during concentric contractions of the vastus lateralis and biceps brachii. RESULTS: The mean difference of 13.1 ms (-33.3-59.9) between sEMG and fwEMG was non-significant (intraclass correlation [ICC] = 0.60). Ultrasound was significantly different from surface and fine wire EMG (ICC = 0.65 and ICC = 0.40, respectively), occurring 98.6 ms (72.3-124.9) and 111.7 (60.3-163.0) before sEMG and fwEMG, respectively. Nonparametric interquartile ranges were also wide. CONCLUSIONS: Due to high variability, comparisons between EMG methods should be interpreted with caution. Ultrasound detected onset before either EMG method, which may indicate motion from adjacent muscles during voluntary contractions. Muscle Nerve 59:494-500, 2019.

Relationships Between Neuromuscular Function and Functional Balance Performance in Firefighters.

The purpose of the present study was to examine the relationships between neuromuscular function and functional balance performance in firefighters. Fifty career firefighters (35.1 ± 7.5 yr) performed isometric leg extension and flexion muscle actions to examine peak torque (PT), and absolute (aTQ) and normalized (nTQ; %PT) rapid torque variables at 50, 100, 150, and 200 ms. A performance index (PI) was determined from the functional balance assessment completion time. Partial correlations were used to examine the relationship between the PI and the maximal and rapid TQ variables for each muscle and the composite value, while controlling for demographic data related to the PI. Multiple regression analyses examined the relative contributions of the maximal and rapid aTQ variables, and demographic data on the PI. After controlling for age and %BF, the majority of the later aTQ and nTQ variables (100-200 ms) and PT were associated with the PI (r = -0.501--0.315). Age, %BF, and aTQ100 explained 42-50% of the variance in the PI. Lower rapid strength, increased age, and poorer body composition were related to worse performance during the functional balance assessment. Strategies to improve rapid strength and %BF, especially in aging firefighters may impact dynamic balance abilities in firefighters.

The Influence of Habitual Protein Intake on Body Composition and Muscular Strength in Career Firefighters.

OBJECTIVE: The aim of this research was to determine the relationship among protein (PRO) intake, body composition, and muscle strength in overweight and obese firefighters. A secondary objective was to evaluate differences in body composition and muscle strength among overweight and obese firefighters with low (L; < 0.8 g·kg-1), moderate (M; 0.8-1.0 g·kg-1), and high (H; > 1.0 g·kg-1) PRO intake. METHODS: Relative PRO intake [r_PRO] was evaluated from 3-day dietary logs, self-reported by 43 overweight and obese male career firefighters (mean ± standard deviation; age = 37.3 ± 7.2 years; body mass index = 33.2 ± 5.0 kg·m-2; percent body fat [%BF] = 28.9 ± 4.0%). Body composition (fat mass [FM], %BF, lean mass [LM], percent LM [%LM]) and muscle strength (peak torque [PT], relative peak torque [r_PT] of the leg extensors) were measured using dual-energy x-ray absorptiometry and isokinetic dynamometry, respectively. RESULTS: Greater r_PRO was associated with less FM, %BF, LM (r = -0.498 to -0.363) and greater %LM (r = 0.363), but not muscle strength (p > 0.05). Fat mass (r = -0.373) and %BF (r = -0.369) were associated with lower r_PT; %LM was associated with greater r_PT (r = 0.373). Individuals with L r_PRO had greater FM (mean difference ± standard error: L-H = 10.08 ± 3.18 kg), %BF (L-H = 3.8% ± 1.4%) and lower %LM (L-H = -3.7% ± 1.3%) than those with H r_PRO (p < 0.05) but no significant differences in muscle strength (p > 0.05). CONCLUSIONS: Protein intake > 0.8 g·kg-1 was associated with more favorable body composition in male career firefighters.

Prior Mental Fatigue Impairs Marksmanship Decision Performance.

Purpose: Mental fatigue has been shown to impair subsequent physical performance in continuous and discontinuous exercise. However, its influence on subsequent fine-motor performance in an applied setting (e.g., marksmanship for trained soldiers) is relatively unknown. The purpose of this study was to investigate whether prior mental fatigue influences subsequent marksmanship performance as measured by shooting accuracy and judgment of soldiers in a live-fire scenario. Methods: Twenty trained infantry soldiers engaged targets after completing either a mental fatigue or control intervention in a repeated measure design. Heart rate variability and the NASA-TLX were used to gauge physiological and subjective effects of the interventions. Target hit proportion, projectile group accuracy, and precision were used to measure marksmanship accuracy. Marksmanship accuracy was assessed by measuring bullet group accuracy (i.e., how close a group of shots are relative to center of mass) and bullet group precision (i.e., how close are each individual shot to each other). Additionally, marksmanship decision accuracy (correctly shooting vs. correctly withholding shot) when engaging targets was used to examine marksmanship performance. Results: Soldiers rated the mentally fatiguing task (59.88 ± 23.7) as having greater mental workload relative to the control intervention [31.29 ± 12.3, t(19) = 1.72, p < 0.001]. Additionally, soldiers completing the mental fatigue intervention (96.04 ± = 37.1) also had lower time-domain (standard deviation of normal to normal R-R intervals) heart rate variability relative to the control [134.39 ± 47.4, t(18) = 3.59, p < 0.001]. Projectile group accuracy and group precision failed to show differences between interventions [t(19) = 0.98, p = 0.34, t(19) = 0.18, p = 0.87, respectively]. Marksmanship decision errors significantly increased after soldiers completed the mental fatigue intervention (48% ± 22.4) relative to the control intervention [M = 32% ± 79.9, t(19) = 4.39, p < 0.001]. There was a significant negative correlation between shooting response time and errors of commission (r = -0.61; p = 0.004) when preceded by the mental fatigue intervention, but not the control (r = -0.31; p = 0.17). Conclusion: The mental fatigue intervention was successful in eliciting fatigue which was supported subjectively and objectively. Marksmanship judgment performance is significantly reduced when soldiers are mentally fatigued, although shot accuracy is not.

Consistency of a mobile body composition trailer: a novel portable laboratory assessment?

OBJECTIVE: The purpose of this investigation was to (i) assess the test-retest reliability and minimum difference (MD) values of air-displacement plethysmography (ADP) and the Siri 3-compartment (3-C) model in a mobile trailer, and (ii) identify any environmental fluctuations in the trailer. METHODS: percent body fat (%BF) was examined in 22 firefighters on two separate days in a climate-controlled mobile trailer using ADP. Total body water was examined in a subset of participants (n = 12) using bioelectrical impedance spectroscopy (BIS) to determine %BF using Siri's 3-C model. RESULTS: There were no differences in environmental measures (P≥0·138), %BF for ADP (P = 0·276), or %BF for the Siri 3-C model (P = 0·382) between day 1 and day 2. Intraclass correlation coefficient and standard error of measurement values for ADP and the Siri 3-C model were 0·978 and 1·3% and 0·986 and 0·6%, respectively. The MD values were 3·6% and 1·7%, respectively. CONCLUSIONS: These findings indicate that ADP can reliably determine %BF when transported in a climate-controlled mobile trailer. Additional accuracy is achievable with the Siri 3-C model, providing an attractive and promising method to measure body composition in larger scale community-based settings.

Iterative Assessment of Statistically-Oriented and Standard Algorithms for Determining Muscle Onset with Intramuscular Electromyography.

The onset of muscle activity, as measured by electromyography (EMG), is a commonly applied metric in biomechanics. Intramuscular EMG is often used to examine deep musculature and there are currently no studies examining the effectiveness of algorithms for intramuscular EMG onset. The present study examines standard surface EMG onset algorithms (linear envelope, Teager-Kaiser Energy Operator, and sample entropy) and novel algorithms (time series mean-variance analysis, sequential/batch processing with parametric and nonparametric methods, and Bayesian changepoint analysis). Thirteen male and 5 female subjects had intramuscular EMG collected during isolated biceps brachii and vastus lateralis contractions, resulting in 103 trials. EMG onset was visually determined twice by 3 blinded reviewers. Since the reliability of visual onset was high (ICC(1,1): 0.92), the mean of the 6 visual assessments was contrasted with the algorithmic approaches. Poorly performing algorithms were stepwise eliminated via (1) root mean square error analysis, (2) algorithm failure to identify onset/premature onset, (3) linear regression analysis, and (4) Bland-Altman plots. The top performing algorithms were all based on Bayesian changepoint analysis of rectified EMG and were statistically indistinguishable from visual analysis. Bayesian changepoint analysis has the potential to produce more reliable, accurate, and objective intramuscular EMG onset results than standard methodologies.

Analysis of statistical and standard algorithms for detecting muscle onset with surface electromyography.

The timing of muscle activity is a commonly applied analytic method to understand how the nervous system controls movement. This study systematically evaluates six classes of standard and statistical algorithms to determine muscle onset in both experimental surface electromyography (EMG) and simulated EMG with a known onset time. Eighteen participants had EMG collected from the biceps brachii and vastus lateralis while performing a biceps curl or knee extension, respectively. Three established methods and three statistical methods for EMG onset were evaluated. Linear envelope, Teager-Kaiser energy operator + linear envelope and sample entropy were the established methods evaluated while general time series mean/variance, sequential and batch processing of parametric and nonparametric tools, and Bayesian changepoint analysis were the statistical techniques used. Visual EMG onset (experimental data) and objective EMG onset (simulated data) were compared with algorithmic EMG onset via root mean square error and linear regression models for stepwise elimination of inferior algorithms. The top algorithms for both data types were analyzed for their mean agreement with the gold standard onset and evaluation of 95% confidence intervals. The top algorithms were all Bayesian changepoint analysis iterations where the parameter of the prior (p0) was zero. The best performing Bayesian algorithms were p0 = 0 and a posterior probability for onset determination at 60-90%. While existing algorithms performed reasonably, the Bayesian changepoint analysis methodology provides greater reliability and accuracy when determining the singular onset of EMG activity in a time series. Further research is needed to determine if this class of algorithms perform equally well when the time series has multiple bursts of muscle activity.

Computer-Based Algorithmic Determination of Muscle Movement Onset Using M-Mode Ultrasonography.

The study purpose was to evaluate the use of computer-automated algorithms as a replacement for subjective, visual determination of muscle contraction onset using M-mode ultrasonography. Biceps and quadriceps contraction images were analyzed visually and with three different classes of algorithms: pixel standard deviation (SD), high-pass filter and Teager Kaiser energy operator transformation. Algorithmic parameters and muscle onset threshold criteria were systematically varied within each class of algorithm. Linear relationships and agreements between computed and visual muscle onset were calculated. The top algorithms were high-pass filtered with a 30 Hz cutoff frequency and 20 SD above baseline, Teager Kaiser energy operator transformation with a 1200 absolute SD above baseline and SD at 10% pixel deviation with intra-class correlation coefficients (mean difference) of 0.74 (37.7 ms), 0.80 (61.8 ms) and 0.72 (109.8 ms), respectively. The results suggest that computer automated determination using high-pass filtering is a potential objective alternative to visual determination in human movement science.

The influence of subcutaneous fat on the relationship between body composition and ultrasound-derived muscle quality.

Ultrasound echo intensity (EI) values are a popular assessment of muscle quality. The relationship between EI and total (%fat) and regional (%fatlimb) body composition was examined in 40 men, prior to and after accounting for subcutaneous fat thickness. Uncorrected EI values suggest that muscle quality improves (r = -0.329 to -0.224; P = 0.038-0.165) with greater %fat and %fatlimb. However, corrected EI values indicated that muscle quality decreases (r = 0.711 to 0.798; P < 0.001) with greater %fat and %fatlimb.

Cognitive Fatigue Influences Time-On-Task during Bodyweight Resistance Training Exercise.

Prior investigations have shown measurable performance impairments on continuous physical performance tasks when preceded by a cognitively fatiguing task. However, the effect of cognitive fatigue on bodyweight resistance training exercise task performance is unknown. In the current investigation 18 amateur athletes completed a full body exercise task preceded by either a cognitive fatiguing or control intervention. In a randomized repeated measure design, each participant completed the same exercise task preceded by a 52 min cognitively fatiguing intervention (vigilance) or control intervention (video). Data collection sessions were separated by 1 week. Participants rated the fatigue intervention with a significantly higher workload compared to the control intervention (p < 0.001). Additionally, participants self-reported significantly greater energetic arousal for cognitively fatiguing task (p = 0.02). Cognitive fatigue did not significantly impact number of repetitions completed during the exercise task (p = 0.77); however, when cognitively fatigued, participants had decreased percent time-on-task (57%) relative to the no fatigue condition (60%; p = 0.04). RPE significantly changed over time (p < 0.001), but failed to show significant differences between the cognitive fatigue intervention and control intervention (p > 0.05). There was no statistical difference for heart rate or metabolic expenditure as a function of fatigue intervention during exercise. Cognitively fatigued athletes have decreased time-on-task in bodyweight resistance training exercise tasks.

The influence of ultrasound measurement techniques on the age-related differences in Achilles tendon size.

Achilles tendon (AT) properties change with age, however the extent to which aging influences the size of the AT may be influenced by the measurement technique. The purpose of this study was to 1) examine the age-related differences in AT size using measures of cross-sectional area (CSA) and thickness, and 2) to determine the test-retest reliability and minimum difference (MD) values of these measures. The size of the AT was examined in 19 young (19.79 ± 2.3 years) and 18 older (69.4 ± 3.1 years) healthy men on two separate occasions using an ultrasonography. The CSA and thickness of the AT were determined by separate transverse and longitudinal scans on the right leg at the same distance from the medial malleolus, respectively. Prior to and after accounting for body mass, AT CSA was larger (P ≤ 0.01) in the older men (64.49 ± 13.87 mm(2)) when compared to the younger men (44.12 ± 16.04 mm(2)), however there were no differences in AT thickness between age groups (P=0.96). In addition, there was no systematic error (P>0.05) between testing days, and the intraclass correlation coefficients, standard error of measurement (expressed as a % of the mean), and MD values for CSA and thickness ranged from 0.80-0.98, 5.46-8.68%, and 5.65-7.94 mm(2) and 0.51-0.86 mm, respectively between both groups. These findings suggest that the reliability of the CSA and thickness measurements were similar, however, CSA was a more sensitive measure to detect the age-related changes of AT size.

Influence of Lower Extremity Muscle Size and Quality on Stair-Climb Performance in Career Firefighters.

The purpose of this study was to examine the influence of lower extremity muscular size and quality on stair-climb performance (SCP) in career firefighters. Forty-six male career firefighters (age = 37.0 ± 7.2 years; stature = 180.2 ± 6.9 cm; body mass = 108.0 ± 19.8 kg) volunteered for this study. Panoramic ultrasound images of the vastus lateralis and rectus femoris were obtained to determine cross-sectional area (CSA) and echo intensity (EI) of each muscle. The CSA of each muscle was then summed together and normalized to body mass (CSA/BM [QCSA]). Additionally, EI was averaged across both muscles (QEI). Participants then performed a timed and weighted SCP assessment where they ascended and descended 26 stairs 4 times as quickly as possible while wearing a weighted vest (22.73 kg) to simulate the weight of their self-contained breathing apparatus and turnout gear. Bivariate correlations and stepwise regression analyses were used to examine the relationships among variables and the relative contributions of QCSA and QEI to SCP. Partial correlations were used to examine the relationship between QCSA and SCP and QEI and SCP while controlling for age and body mass index (BMI). The results indicated that QCSA and QEI were significantly related to SCP before (r = -0.492, p = 0.001; r = 0.363, p = 0.013, respectively) and after accounting for age and BMI (r = -0.324, p = 0.032; r = 0.413, p = 0.005, respectively). Both QCSA and QEI contributed significantly to the prediction of SCP (r = 0.560, p < 0.001). These findings indicate that lower extremity muscle size and quality are important contributors to critical firefighting tasks, which have been shown to be improved with resistance training.

Pennation angle does not influence the age-related differences in echo intensity of the medial gastrocnemius.

The reflection of an ultrasound (US) wave is strongest when the propagation direction of the wave is perpendicular to muscle fascicles. Thus, it is possible that muscle echo intensity (EI), a gray-scale US measure of muscle quality, may be influenced by the angulation of muscle fascicles. Therefore, the purpose of this study was to determine if age-related differences in muscle EI values are influenced by differences in pennation angle (PA). Medial gastrocnemius EI and PA were examined using panoramic US imaging in 24 young (19.8 ± 1.7 y) and 21 older (69.3 ± 3.3 y) men. The young men had lower EI values (young = 74.1 ± 6.3 a.u., older = 89.1 ± 8.8 a.u.) and a greater PA (young = 20.0 ± 2.9°; older = 17.2 ± 2.5°) compared with the older men (p < 0.01). In addition, there was a negative relationship (r = -0.473, p < 0.01) between PA and EI with both groups combined, but no significant relationship when the young (r = -0.334, p = 0.111) and older (r = -0.147, p = 0.525) men were examined separately. An analysis of covariance revealed that muscle EI values remained different (p < 0.01) between age groups after adjustment for differences in PA. Thus, after statistically adjusting the mean EI values for the differences in PA, there were still significant age-related differences in EI. These findings may provide further support that the age-related changes in muscle EI values reflect changes in tissue composition (i.e., increase in intramuscular fat and/or connective tissue) commonly reported in older adults.

Changes in resting heart rate variability across the menstrual cycle.

Heart rate variability (HRV) is a noninvasive indicator of autonomic control. This study examines HRV changes across a normal menstrual cycle and proposes a novel piecewise function controlling for the effects of breathing on HRV spectral parameters. A resting ECG was collected from 13 women at five points in their menstrual cycle. Both heart rate and breathing rate increased across the cycle (p < .01) while time-domain variability decreased (p = .04). Use of the piecewise function for breathing rate in HRV spectral analysis was confirmed by a substantial increase in model goodness-of-fit. HRV spectral parameters, controlled for breathing with the piecewise function, confirm that the decrease in variability is likely due to a parasympathetic withdrawal, since high frequency HRV decreases (p = .02).