Motor unit recruitment strategies investigated by surface EMG variables

Trunk extensor muscle endurance and its relationship to action potential conduction velocity and spectral parameters estimated using high-density electromyography

Trunk extensor muscle fatigue typically manifests as a decline in spectral content of surface electromyography. However, previous research on the relationship of this decline with trunk extensor muscle endurance have shown inconsistent results. The decline of spectral content mainly reflects the decrease in average motor unit action potential conduction velocity (CV). We evaluated whether the rate of change in CV, as well as two approaches employing the change in spectral content, are related to trunk extensor muscle endurance. Fourteen healthy male participants without a low-back pain history performed a non-strictly controlled static forward trunk bending trial until exhaustion while standing. For 13 participants, physiologically plausible CV estimates were obtained from high-density surface electromyography bilaterally from T6 to L5. Laterally between L1 and L2, the linear rate of CV change was strongly correlated to endurance time (R2 = 0.79), whereas analyses involving the linear rate of change in spectral measures showed a lower (R2 = 0.38) or no correlation. For medial electrode locations, estimating CV and its relationship with endurance time was less successful, while the linear rate of change in spectral measures correlated moderately to endurance time (R2 = 0.44; R2 = 0.56). This study provides guidance on monitoring trunk extensor muscle fatigue development using electromyography.

Characterization of Motor Unit Firing and Twitch Properties for Decoding Musculoskeletal Force in the Human Ankle Joint In Vivo

Understanding how motor units (MUs) contribute to skeletal mechanical force is crucial for unraveling the underlying mechanism of human movement. Alterations in MU firing, contractile and force-generating properties emerge in response to physical training, aging or injury. However, how changes in MU firing and twitch properties dictate skeletal muscle force generation in healthy and impaired individuals remains an open question. In this work, we present a MU-specific approach to identify firing and twitch properties of MU samples and employ them to decode musculoskeletal function in vivo. First, MU firing events were decomposed offline from high-density electromyography (HD-EMG) of six lower leg muscles involved in ankle plantar-dorsi flexion. We characterized their twitch responses based on the statistical distributions of their firing properties and employed them to compute MU-specific activation dynamics. Subsequently, we decoded ankle joint moments by linking our framework to a subject-specific musculoskeletal model. We validated our approach at different ankle positions and levels of activation and compared it with traditional EMG-driven models. Our proposed MU-specific formulation achieves higher generalization across conditions than the EMG-driven models, with significantly lower coefficients of variation in torque predictions. Furthermore, our approach shows distinct neural strategies across a large repertoire of contractile conditions in different muscles. Our proposed approach may open new avenues for characterizing the relationship between MU firing and twitch properties and their influence on force capacity. This can facilitate the development of targeted rehabilitation strategies tailored to individuals with specific neuromuscular conditions.

Evolution of surface electromyography: From muscle electrophysiology towards neural recording and interfacing

Surface electromyography (EMG) comprises a recording of electrical activity from the body surface generated by muscle fibres during muscle contractions. Its characteristics depend on the fibre membrane potentials and the neural activation signal sent from the motor neurons to the muscles. EMG has been classically used as the primary investigation tool in kinesiology studies in a variety of applications. More recently, surface EMG techniques have evolved from single-channel methods to high-density systems with hundreds of electrodes. High-density EMG recordings can be deconvolved to estimate the discharge times of spinal motor neurons innervating the recorded muscles, with algorithms that have been developed and validated in the last two decades. Within limits and with some variability across muscles, these techniques provide a non-invasive method to study relatively large populations of motor neurons in humans. Surface EMG is thus evolving from a peripheral measure of muscle electrical activity towards a neural recording and neural interfacing signal. These advances in technology have had a major impact on our fundamental understanding of the neural control of movement and have exposed new perspectives in neurotechnologies. Here we provide an overview and perspective of modern EMG technology, as derived from past achievements, and its impact in neurophysiology and neural engineering.

Investigating post-mild traumatic brain injury neuromuscular function and musculoskeletal injury risk: A protocol for a prospective, observational, case-controlled study in service members and active individuals

INTRODUCTION

Musculoskeletal injury (MSKI) risk is increased following mild traumatic brain injury (mTBI). Increased MSKI risk is present up to 2 years following post-mTBI return-to-duty/activity relative to both non-mTBI peers and to their pre-mTBI selves across a range of populations, including military service members, and professional, college and high school athletes. Despite the well documented increased post-mTBI MSKI risk, the underlying neuromuscular mechanisms contributing to this increased risk have yet to be definitively determined. A number of potential mechanisms have been suggested (eg, aberrant kinematics, dynamic balance impairments, lower voluntary muscle activation), but none have been confirmed with a comprehensive, prospective study. This study aims to: (1) elucidate the neuromuscular control mechanisms following mTBI that contribute to increased MSKI risk, and (2) prospectively track patient outcomes (up to 12 months; MSKI occurrences and patient-reported outcomes (PRO)).

METHODS AND ANALYSIS

This is a multicentre prospective, case-matched control observational study to identify deficiencies in neuromuscular function following mTBI that may contribute to increased MSKI risk. Participants (aim to recruit 148, complete data collection on 124) will be classified into two cohorts; mTBI and control. All participants will undergo longitudinal (initial, 6 weeks post-initial, 12 weeks post-initial) comprehensive three-dimensional biomechanical (jump-landing; single leg hop; cut; gait), neuromuscular (interpolated twitch technique, muscular ramp contraction) and sensory (joint repositioning; light touch sensation) assessments to elucidate the underlying neuromuscular control mechanisms post-mTBI that may contribute to increased MSKI. Occurrences of MSKI and PROs (National Institutes of Health Patient-Reported Outcome Measurement Information System: Physical Function, Pain Interference, Depression, Anxiety; Brief Resilience Scale; Tampa Scale of Kinesiophobia), will be tracked monthly (up to 1 year) via electronic data capture platforms.

ETHICS AND DISSEMINATION

The study received approval from the Walter Reed National Military Medical Center Institutional Review Board. Results will be made available to the associated funding agency and other researchers via conference proceedings and journal articles.

TRIAL REGISTRATION NUMBER

NCT05122728.

Energy metabolism and muscle activation heterogeneity explain V ̇ O 2 ${\dot{V}}_{{{\rm{O}}}_{\rm{2}}}$ slow component and muscle fatigue of cycling at different intensities

NEW FINDINGS

What is the central question of this study? What are the physiological mechanisms underlying muscle fatigue and the increase in the O2 cost per unit of work during high-intensity exercise? What is the main finding and its importance? Muscle fatigue happens before, and does not explain, theV ̇ O 2 ${\dot{V}}_{{{\rm{O}}}_{\rm{2}}}$ slow component (V ̇ O 2 sc ${\dot{V}}_{{{\rm{O}}}_{\rm{2}}{\rm{sc}}}$ ), but they share the same origin. Muscle activation heterogeneity is associated with muscle fatigue andV ̇ O 2 sc ${\dot{V}}_{{{\rm{O}}}_{\rm{2}}{\rm{sc}}}$ . Knowing this may improve training prescriptions for healthy people leading to improved public health outcomes.

ABSTRACT

This study aimed to explain theV ̇ O 2 ${\dot{V}}_{{{\rm{O}}}_{\rm{2}}}$ slow component (V ̇ O 2 sc ${\dot{V}}_{{{\rm{O}}}_{\rm{2}}{\rm{sc}}}$ ) and muscle fatigue during cycling at different intensities. The muscle fatigue of 16 participants was determined through maximal isokinetic effort lasting 3 s during constant work rate bouts of moderate (MOD), heavy (HVY) and very heavy intensity (VHI) exercise. Breath-by-breathV ̇ O 2 ${\dot{V}}_{{{\rm{O}}}_{\rm{2}}}$ , near-infrared spectroscopy signals and EMG activity were analysed (thigh muscles).V ̇ O 2 sc ${\dot{V}}_{{{\rm{O}}}_{\rm{2}}{\rm{sc}}}$ was higher during VHI exercise (∼70% vs. ∼28% ofV ̇ O 2 ${\dot{V}}_{{{\rm{O}}}_{\rm{2}}}$ reserve in HVY). The deoxygenated haemoglobin final value during VHI exercise was higher than during HVY and MOD exercise (∼90% of HHb physiological normalization, vs. ∼82% HVY and ∼45% MOD). The muscle fatigue was greater after VHI exercise (∼22% vs. HVY ∼5%). There was no muscle fatigue after MOD exercise. The greatest magnitude of muscle fatigue occurred within 2 min (VHI ∼17%; HVY ∼9%), after which it stabilized. No significant relationship betweenV ̇ O 2 sc ${\dot{V}}_{{{\rm{O}}}_{\rm{2}}{\rm{sc}}}$ and muscle force production was observed. The τ of muscleV ̇ O 2 ${\dot{V}}_{{{\rm{O}}}_{\rm{2}}}$ was significantly related (R2  = 0.47) with torque decrease for VHI. Type I and II muscle fibre recruitment mainly in the rectus femoris moderately explained the muscle fatigue (R2  = 0.30 and 0.31, respectively) and theV ̇ O 2 sc ${\dot{V}}_{{{\rm{O}}}_{\rm{2}}{\rm{sc}}}$ (R2  = 0.39 and 0.27, respectively). TheV ̇ O 2 sc ${\dot{V}}_{{{\rm{O}}}_{\rm{2}}{\rm{sc}}}$ is also partially explained by blood lactate accumulation (R2  = 0.42). In conclusion muscle fatigue and O2 cost seem to share the same physiological cause linked with a decrease in the muscleV ̇ O 2 ${\dot{V}}_{{{\rm{O}}}_{\rm{2}}}$ and a change in lactate accumulation. Muscle fatigue andV ̇ O 2 sc ${\dot{V}}_{{{\rm{O}}}_{\rm{2}}{\rm{sc}}}$ are associated with muscle activation heterogeneity and metabolism of different muscles activated during cycling.

EMG Amplitude-Force Relationship of Lumbar Back Muscles during Isometric Submaximal Tasks in Healthy Inactive, Endurance and Strength-Trained Subjects

Previous data suggest a correlation between the cross-sectional area of Type II muscle fibers and the degree of non-linearity of the EMG amplitude-force relationship (AFR). In this study we investigated whether the AFR of back muscles could be altered systematically by using different training modalities. We investigated 38 healthy male subjects (aged 19-31 years) who regularly performed either strength or endurance training (ST and ET, n = 13 each) or were physically inactive (controls (C), n = 12). Graded submaximal forces on the back were applied by defined forward tilts in a full-body training device. Surface EMG was measured utilizing a monopolar 4 × 4 quadratic electrode scheme in the lower back area. The polynomial AFR slopes were determined. Between-group tests revealed significant differences for ET vs. ST and C vs. ST comparisons at the medial and caudal electrode positions, but not for ET vs. C. Further, systematic main effects of the "electrode position" could be proven for ET and C groups with decreasing x² coefficients from cranial to caudal and lateral to medial. For ST, there was no systematic main effect of the "electrode position". The results point towards training-related changes to the fiber-type composition of muscles in the strength-trained participants, particularly for their paravertebral region.

Workload Assessment of Tractor Operations with Ergonomic Transducers and Machine Learning Techniques

Dynamic muscular workload assessments of tractor operators are rarely studied or documented, which is critical to improving their performance efficiency and safety. A study was conducted to assess and model dynamic load on muscles, physiological variations, and discomfort of the tractor operators arriving from the repeated clutch and brake operations using wearable non-invasive ergonomic transducers and data-run techniques. Nineteen licensed tractor operators operated three different tractor types of varying power ranges at three operating speeds (4-5 km/h), and on two common operating surfaces (tarmacadam and farm roads). During these operations, ergonomic transducers were utilized to capture the load on foot muscles (gastrocnemius right [GR] and soleus right [SR] for brake operation and gastrocnemius left [GL], and soleus left [SL] for clutch operation) using electromyography (EMG). Forces exerted by the feet during brake and clutch operations were measured using a custom-developed foot transducer. During the process, heart rate (HR) and oxygen consumption rates (OCR) were also measured using HR monitor and K4b2 systems, and energy expenditure rate (EER) was determined using empirical equation. Post-tractor operation cycle, an overall discomfort rating (ODR) for that operation was manually recorded on a 10-point psychophysical scale. EMG-based maximum volumetric contraction (%MVC) measurements revealed higher strain on GR (%MVC = 43%), GL (%MVC = 38%), and SR (%MVC = 41%) muscles which in normal conditions should be below 30%. The clutch and brake actuation forces were recorded in the ranges of 90-312 N and 105-332 N, respectively and were significantly affected by the operating speed, tractor type, and operating surface (p < 0.05). EERs of the operators were measured in the moderate-heavy to heavy ranges (9-24 kJ/min) during the course of trials, suggesting the need to refine existing clutch and brake system designs. Average operator ODR responses indicated 7.8% operations in light, 48.5% in light-moderate, 25.2% in moderate, 10.7% in moderate-high, and 4.9% operations in high discomfort categories. When evaluated for the possibility of minimizing the number of transducers for physical workload assessment, EER showed moderate-high correlations with the EMG signals (r_GR = 0.78, r_GL = 0.75, r_SR = 0.68, r_SL = 0.66). Similarly, actuation forces had higher correlations with EMG signals for all the selected muscles (r = 0.70-0.87), suggesting the use of simpler transducers for effective operator workload assessment. As a means to minimize subjectivity in ODR responses, machine learning algorithms, including K-nearest neighbor (KNN), random forest classifier (RFC), and support vector machine (SVM), predicted the ODR using body mass index (BMI), HR, EER, and EMG at high accuracies of 87-97%, with RFC being the most accurate. Such high-throughput and data-run ergonomic evaluations can be instrumental in reconsidering workplace designs and better fits for end-users in terms of agricultural tractors and machinery systems.

Coherence between electromyographic signals of anterior tibialis, soleus, and gastrocnemius during standing balance tasks

Introduction

Knowledge about the mechanics and physiological features of balance for healthy individuals enhances understanding of impairments of balance related to neuropathology secondary to aging, diseases of the central nervous system (CNS), and traumatic brain injury, such as concussion.

Methods

We examined the neural correlations during muscle activation related to quiet standing from the intermuscular coherence in different neural frequency bands. Electromyography (EMG) signals were recorded from six healthy participants (fs = 1,200 Hz for 30 s) from three different muscles bilaterally: anterior tibialis, medial gastrocnemius, and soleus. Data were collected for four different postural stability conditions. In decreasing order of stability these were feet together eyes open, feet together eyes closed, tandem eyes open, and tandem eyes closed. Wavelet decomposition was used to extract the neural frequency bands: gamma, beta, alpha, theta, and delta. Magnitude-squared-coherence (MSC) was computed between different muscle pairs for each of the stability conditions.

Results and discussion

There was greater coherence between muscle pairs in the same leg. Coherence was greater in lower frequency bands. For all frequency bands, the standard deviation of coherence between different muscle pairs was always higher in the less stable positions. Time-frequency coherence spectrograms also showed higher intermuscular coherence for muscle pairs in the same leg and in less stable positions. Our data suggest that coherence between EMG signals may be used as an independent indicator of the neural correlates for stability.

Spectral properties of physiological mirror activity: an investigation of frequency features and common input between homologous muscles

During unilateral contractions, muscular activation can be detected in both active and resting limbs. In healthy populations, the latter is referred to as physiological mirror activity (pMA). The study of pMA holds implications for clinical applications as well as the understanding of bilateral motor control. However, the underlying mechanisms of pMA remain to be fully resolved. A commonality of prevailing explanatory approaches is the concept of shared neural input. With this study, we, therefore, aimed to investigate neural input in the form of multiple analyses of surface electromyography (sEMG) recordings in the frequency domain. For this purpose, 14 healthy, right-handed males aged 18–35 years were recruited. All participants performed a pinch-force task with the dominant hand in a blockwise manner. In total, 9 blocks of 5 contractions each were completed at 80% of maximum force output. Muscle activity was recorded via sEMG of the first dorsal interosseous muscle of the active and resting hand. We analyzed (1) spectral features as well as (2) intermuscular coherence (IMC). Our results demonstrate a blockwise increase in median frequency, mean frequency, and peak frequency in both hands. Frequency ratio analyses revealed a higher low-frequency component in the resting hand. Although we were able to demonstrate IMC on an individual level, results varied greatly and grand-averaged IMC failed to reach significance. Taken together, our findings imply an overlap of spectral properties between active and passive hands during repeated unilateral contractions. Combined with evidence from previous studies, this suggests a common neural origin between active and resting hands during unilateral contractions possibly resulting from a reduction in interhemispheric inhibition due to high force demands. Nevertheless, the exploratory nature of this study necessitates the classification of our results through follow-up studies.

Hip and Knee Joint Angles Determine Fatigue Onset during Quadriceps Neuromuscular Electrical Stimulation

Neuromuscular electrical stimulation (NMES) has been used to increase muscle strength and physical function. However, NMES induces rapid fatigue, limiting its application. To date, the effect of quadriceps femoris (QF) muscle length by knee and hip joint manipulation on NMES-induced contraction fatigability is not clear. We aimed to quantify the effects of different muscle lengths on NMES-induced contraction fatigability, fatigue index, and electromyographic (EMG) activity for QF muscle. QF maximum evoked contraction (QMEC) was applied in a 26 min protocol (10 s on; 120 s off; 12 contractions) in 20 healthy participants (24.0 ± 4.6 years old), over 4 sessions on different days to test different conditions. The tested conditions were as follows: supine with knee flexion of 60° (SUP60), seated with knee flexion of 60° (SIT60), supine with knee flexion of 20° (SUP20), and seated with knee flexion of 20° (SIT20). Contraction fatigability (torque decline assessed by maximal voluntary contraction [MVC] and during NMES), fatigue index (percentage reduction in MVC), and EMG activity (root mean square [RMS] and median frequency) of the superficial QF' constituents were assessed. After NMES, all positions except SUP20 had an absolute reduction in MVC (p < .001). Fatigue index was greater in SIT20 than in SIT60 (p < .001) and SUP20 (p = .01). There was significant torque reduction across the 12 QMEC in SUP60 and SIT60, up to 10.5% (p < .001–.005) and 9.49% (p < .001–.033), respectively. There was no torque reduction during NMES in SUP20 and SIT20. Fatigue was accompanied by an increase in RMS (p = .032) and a decrease in median frequency for SUP60 (p < .001). Median frequency increased only in the SUP20 condition (p = .021). We concluded that QF NMES-induced contraction fatigability is greater when the knee is flexed at 60° compared to 20°. In addition, a supine position promotes earlier fatigue for a 60° knee flexion, but it delays fatigue onset for a 20° knee flexion compared to the seated position. These results provide a rationale for lower limb positioning during NMES, which depends on training objectives, e.g., strengthening or task-specific functionality training.

The influence of the reference electrode location on the M-wave characteristics in the quadriceps

INTRODUCTION

In the compound muscle action potential (M wave) recorded using the belly-tendon configuration, the contribution of the tendon electrode is assumed to be negligible compared to the belly electrode. We tested this assumption by placing the reference electrode at a distant (contralateral) site, which allowed separate recording of the belly and tendon contributions.

METHODS

M waves were recorded at multiple selected sites over the right quadriceps heads and lower leg using two different locations for the reference electrode: the ipsilateral (right) and contralateral (left) patellar tendon. The general parameters of the M wave (amplitude, area, duration, latency, and frequency) were measured.

RESULTS

(1) The tendon potential had a small amplitude (<30%) compared to the belly potential; (2) Changing the reference electrode from the ipsilateral to the contralateral patella produced moderate changes in the M wave recorded over the innervation zone, these changes affecting significantly the amplitude of the M-wave second phase (p = 0.006); (3) Using the contralateral reference system allowed recording of short-latency components occurring immediately after the stimulus artefact, which had the same latency and amplitude (p = 0.18 and 0.25, respectively) at all recording sites over the leg.

CONCLUSIONS

The potential recorded at the "tendon" site after femoral nerve stimulation is small (compared to the belly potential), but not negligible, and makes a significant contribution to the second phase of belly-tendon M wave. Adopting a distant (contralateral) reference allowed recording of far-field components that may aid in the understanding of the electrical formation of the M wave.

Selection of the Best Set of Features for sEMG-Based Hand Gesture Recognition Applying a CNN Architecture

The classification of surface myoelectric signals (sEMG) remains a great challenge when focused on its implementation in an electromechanical hand prosthesis, due to its nonlinear and stochastic nature, as well as the great difference between models applied offline and online. In this work, the selection of the set of the features that allowed us to obtain the best results for the classification of this type of signals is presented. In order to compare the results obtained, the Nina PRO DB2 and DB3 databases were used, which contain information on 50 different movements of 40 healthy subjects and 11 amputated subjects, respectively. The sEMG of each subject was acquired through 12 channels in a bipolar configuration. To carry out the classification, a convolutional neural network (CNN) was used and a comparison of four sets of features extracted in the time domain was made, three of which have shown good performance in previous works and one more that was used for the first time to train this type of network. Set one is composed of six features in the time domain (TD1), Set two has 10 features also in the time domain (TD2) including the autoregression model (AR), the third set has two features in the time domain derived from spectral moments (TD-PSD1), and finally, a set of five features also has information on the power spectrum of the signal obtained in the time domain (TD-PSD2). The selected features in each set were organized in four different ways for the formation of the training images. The results obtained show that the set of features TD-PSD2 obtained the best performance for all cases. With the set of features and the formation of images proposed, an increase in the accuracies of the models of 8.16% and 8.56% was obtained for the DB2 and DB3 databases, respectively, compared to the current state of the art that has used these databases.

Greater Neuromuscular Fatigue Following Low Load Blood Flow Restriction than Non Blood Flow Restriction Resistance Exercise Among Recreationally Active Men

PURPOSE

The purpose of this study was to examine the acute effects of low-load blood flow restriction (LLBFR) and low-load non-BFR (LL) on neuromuscular function following a bout of standardized, fatiguing leg extension muscle actions.

METHODS

Fourteen men (mean age ± SD = 23±4 yrs) volunteered to participate in this investigation and randomly performed LLBFR and LL on separate days. Resistance exercise consisted of 75 isotonic, unilateral leg extension muscle actions performed at 30% of one-repetition maximum. Prior to (pretest) and after (posttest) performing each bout of exercise, strength and neural assessments were determined.

RESULTS

There was no pretest to posttest differences between LLBFR and LL for maximal voluntary isometric contraction (MVIC) torque or V-wave/M-wave responses (muscle compound action potentials assessed during a superimposed MVIC muscle action) which exhibited decreases (collapsed across condition) of 41.2% and 26.2%, respectively. There were pretest to posttest decreases in peak twitch torque (36.0%) and sEMG (29.5%) for LLBFR but not LL, and larger decreases in voluntary activation for LLBFR (11.3%) than LL (4.5%).

CONCLUSIONS

These findings suggested that LLBFR elicited greater fatigue-induced decreases in several indices of neuromuscular function relative to LL. Despite this, both LLBFR and LL resulted in similar decrements in performance as assessed by maximal strength.

Advanced Energy Kernel-Based Feature Extraction Scheme for Improved EMG-PR-Based Prosthesis Control Against Force Variation

The EMG signal is a widely focused, clinically viable, and reliable source for controlling bionics and prosthesis devices with the aid of machine-learning algorithms. The decisive step in the EMG pattern recognition (EMG-PR)-based control scheme is to extract the features with minimum neural information loss. This article proposes a novel feature extraction method based on advanced energy kernel-based features (AEKFs). The proposed method is evaluated on a scientific dataset which contains six types of upper limb motion with three different force variations. Furthermore, the EMG signal is acquired for eight upper limb gestures for the testing algorithm on the DSP processor. The efficiency of the proposed feature set has been investigated using classification accuracy (CA), Davies-Bouldin (DB) index-based separability measurement, and time complexity as performance metrics. Moreover, the proposed AEKF features, along with the LDA classifier, have been implemented on the DSP processor (ARM cortex M4) for real-time viability. Offline metrics comparison with the existing approaches prove that AEKF features exhibit lower time complexity along with a higher CA of 97.33%. The algorithm is tested on the DSP processor and CA is reported ≈ 92 %. MATLAB 2015a has been deployed in Intel Core i7, 3.40-GHz RAM for all offline analyses.

Sarcolemmal Excitability, M-Wave Changes, and Conduction Velocity During a Sustained Low-Force Contraction

This study was undertaken to investigate whether sarcolemmal excitability is impaired during a sustained low-force contraction [10% maximal voluntary contraction (MVC)] by assessing muscle conduction velocity and also by analyzing separately the first and second phases of the muscle compound action potential (M wave). Twenty-one participants sustained an isometric knee extension of 10% MVC for 3min. M waves were evoked by supramaximal single shocks to the femoral nerve given at 10-s intervals. The amplitude, duration, and area of the first and second M-wave phases were computed. Muscle fiber conduction velocity, voluntary surface electromyographic (EMG), perceived effort, MVC force, peak twitch force, and temperature were also recorded. The main findings were: (1) During the sustained contraction, conduction velocity remained unchanged. (2) The amplitude of the M-wave first phase decreased for the first ~30s (−7%, p<0.05) and stabilized thereafter, whereas the second phase amplitude increased for the initial ~30s (+7%, p<0.05), before stabilizing. (3) Both duration and area decreased steeply during the first ~30s, and then more gradually for the rest of the contraction. (4) During the sustained contraction, perceived effort increased fivefold, whereas knee extension EMG increased by ~10%. (5) Maximal voluntary force and peak twitch force decreased (respectively, −9% and −10%, p<0.05) after the low-force contraction. Collectively, the present results indicate that sarcolemmal excitability is well preserved during a sustained 10% MVC task. A depression of the M-wave first phase during a low-force contraction can occur even in the absence of changes in membrane excitability. The development of fatigue during a low-force contraction can occur without alteration of membrane excitability.

INTELLIGENT UPPER-LIMB PROSTHETIC CONTROL (iULP) WITH NOVEL FEATURE EXTRACTION METHOD FOR PATTERN RECOGNITION USING EMG

EMG signal-based pattern recognition (EMG-PR) techniques have gained lots of focus to develop myoelectric prosthesis. The performance of the prosthesis control-based applications mainly depends on extraction of eminent features with minimum neural information loss. The machine learning algorithms have a significant role to play for the development of Intelligent upper-limb prosthetic control (iULP) using EMG signal. This paper proposes a new technique of extracting the features known as advanced time derivative moments (ATDM) for effective pattern recognition of amputees. Four heterogeneous datasets have been used for testing and validation of the proposed technique. Out of the four datasets, three datasets have been taken from the standard NinaPro database and the fourth dataset comprises data collected from three amputees. The efficiency of ATDM features is examined with the help of Davies–Bouldin (DB) index for separability, classification accuracy and computational complexity. Further, it has been compared with similar work and the results reveal that ATDM features have excellent classification accuracy of 98.32% with relatively lower time complexity. The lower values of DB criteria prove the good separation of features belonging to various classes. The results are carried out on 2.6[Formula: see text]GHz Intel core i7 processor with MATLAB 2015a platform.

Muscle fibre conduction velocity varies in opposite directions after short- vs. long-duration muscle contractions

INTRODUCTION

The effects of muscle contractions on muscle fibre conduction velocity have normally been investigated for contractions of a given duration and intensity, with most studies being focused on the decline on conduction velocity during/after prolonged contractions. Herein, we perform a systematic analysis of the changes in conduction velocity after voluntary contractions of different durations and intensities.

METHODS

Conduction velocity was estimated in the vastus lateralis before and after knee extensor isometric maximal voluntary contractions (MVCs) of 1, 3, 6, 10, 30 and 60 s, and after brief (3 s) contractions at 10, 30, 50, 70, and 90% of MVC force. Measurements were made during the 10-min period following each contraction.

RESULTS

(1) Conduction velocity was increased immediately after (1 s) the MVCs of brief (≤ 10 s) duration (12 ± 2%, P < 0.05), and then returned rapidly (within 15 s) to control levels; (2) the extent of the increase in conduction velocity was similar after the 3-s, 6-s, and 10-s MVCs (P > 0.05); (3) the magnitude of the increase in conduction velocity after a brief contraction augmented with the intensity of the contraction (increases of 4.6, 7.7, 11.4, 14.8, and 15.2% for contractions at 10, 30, 50, 70, and 90% of MVC force, respectively); (4) conduction velocity was not decreased immediately after the 30-s MVC (P > 0.05); and (5) conduction velocity did not reach its minimum 1 s after the long (≥ 30 s) MVCs.

CONCLUSIONS

Brief (≤ 10 s) muscle contractions induce a short-term increase in conduction velocity, lasting 15 s, while long (≥ 30 s) contractions produce a long-term decrease in conduction velocity, lasting more than 2 min.

The M waves of the biceps brachii have a stationary (shoulder-like) component in the first phase: implications and recommendations for M-wave analysis

OBJECTIVE

We recently documented that compound muscle action potentials (M waves) recorded over the 'pennate' vastus lateralis showed a sharp deflection (named as a shoulder) in the first phase. Here, we investigated whether such a shoulder was also present in M waves evoked in a muscle with different architecture, such as the biceps brachii, with the purpose of elucidating the electrical origin of such afeature.

APPROACH

M waves evoked by maximal single shocks to the brachial plexus were recorded in monopolar and bipolar configurations from 72 individuals using large (10 mm diameter) electrodes and from eight individuals using small (1 mm diameter) electrodes arranged in a linear array. The changes in M-wave features at different locations along the muscle fiber direction were examined.

MAIN RESULTS

The shoulder was recognizable in most (87%) monopolar M waves, whereas it was rarely observed (6%) in bipolar derivations. Recordings made along the fiber direction showed that the shoulder was a stationary (non-propagating) feature, with short duration (spiky), which had positive polarity at all locations along the fibers. The latency of the shoulder (9.5 ± 0.5 ms) was significantly shorter than the estimated time taken for the action potentials to reach the biceps tendon (12.8 ms).

SIGNIFICANCE

The shoulder must be generated by a dipole source, i.e. a source created at a fixed anatomical position, although the exact origin of this dipole is uncertain. Our results suggest that the shoulder may not be due to the end-of-fiber signals formed at the biceps brachii tendon. The shoulder is not related to any specific arrangement of muscle fibers, as it has been observed in both pennate and fusiform muscles. Being a stationary (non-propagating) component, the shoulder is not reliable for studying changes in sarcolemmal excitability, and thus should be excluded from the M-wave analysis.

EMG Signal Filtering Based on Variational Mode Decomposition and Sub-Band Thresholding

Surface electromyography (EMG) signals are inevitably contaminated by various noise components, including powerline interference (PLI), baseline wandering (BW), and white Gaussian noise (WGN). These noises directly degrade the efficiency of EMG processing and affect the accuracy and robustness of further applications. Currently, most of the EMG filters only target one category of noise. Here, we propose a novel filter to remove all three types of noise. The noisy EMG signal is first decomposed into an ensemble of band-limited modes using variational mode decomposition (VMD). Each category of noise is located within specific modes and is separately removed in sub-bands. In particular, WGN is suppressed by soft thresholding with a noise level-dependent threshold. The denoising performance was assessed from simulated and experimental signals using three performance metrics: the root mean square error ([Formula: see text]), the improvement in signal-to-noise ratio ([Formula: see text]), and the percentage reduction in the correlation coefficient ( η). Other methods, including traditional infinite impulse response (IIR) filters, empirical mode decomposition (EMD) method, and ensemble empirical mode decomposition (EEMD) method, were examined for comparison. The proposed method achieved the best performance to remove BW or WGN. It also effectively reduced PLI noise when the signal-to-noise ratio (SNR) was low. The SNR was improved by 18.6, 19.2, and 8.0 dB for EMG signals corrupted with PLI, BW, and WGN at -6 dB SNR, respectively. The experimental results illustrated that noise was completely removed from resting states, and obvious spikes were distinguished from action states. For two of the ten subjects, the improved SNR reached 20 dB. This study explores the special characteristics of VMD and demonstrates the feasibility of using the VMD-based filter to denoise EMG signals. The proposed filter is efficient at removing three categories of noise and can be used for any application that requires EMG signal filtering at the preprocessing stage, such as gesture recognition and EMG decomposition.

Mechanisms underlying performance impairments following prolonged static stretching without a comprehensive warm-up

Whereas a variety of pre-exercise activities have been incorporated as part of a "warm-up" prior to work, combat, and athletic activities for millennia, the inclusion of static stretching (SS) within a warm-up has lost favor in the last 25 years. Research emphasized the possibility of SS-induced impairments in subsequent performance following prolonged stretching without proper dynamic warm-up activities. Proposed mechanisms underlying stretch-induced deficits include both neural (i.e., decreased voluntary activation, persistent inward current effects on motoneuron excitability) and morphological (i.e., changes in the force-length relationship, decreased Ca²⁺ sensitivity, alterations in parallel elastic component) factors. Psychological influences such as a mental energy deficit and nocebo effects could also adversely affect performance. However, significant practical limitations exist within published studies, e.g., long-stretching durations, stretching exercises with little task specificity, lack of warm-up before/after stretching, testing performed immediately after stretch completion, and risk of investigator and participant bias. Recent research indicates that appropriate durations of static stretching performed within a full warm-up (i.e., aerobic activities before and task-specific dynamic stretching and intense physical activities after SS) have trivial effects on subsequent performance with some evidence of improved force output at longer muscle lengths. For conditions in which muscular force production is compromised by stretching, knowledge of the underlying mechanisms would aid development of mitigation strategies. However, these mechanisms are yet to be perfectly defined. More information is needed to better understand both the warm-up components and mechanisms that contribute to performance enhancements or impairments when SS is incorporated within a pre-activity warm-up.

Masked least-squares averaging in processing of scanning-EMG recordings with multiple discharges

Removing artifacts from nearby motor units is one of the main objectives when processing scanning-EMG recordings. Methods such as median filtering or masked least-squares smoothing (MLSS) can be used to eliminate artifacts in recordings with just one discharge of the motor unit potential (MUP) at each location. However, more effective artifact removal can be achieved if several discharges per position are recorded. In this case, processing usually involves averaging the discharges available at each position and then applying a median filter in the spatial dimension. The main drawback of this approach is that the median filter tends to distort the signal waveform. In this paper, we present a new algorithm that operates on multiple discharges simultaneously and in the spatial dimension. We refer to this algorithm as the multi-masked least-squares smoothing (MMLSS) algorithm: an extension of the MLSS algorithm for the case of multiple discharges. The algorithm is tested using simulated scanning-EMG signals in different recording conditions, i.e., at different levels of muscle contraction and for different numbers of discharges per position. The results demonstrate that the algorithm eliminates artifacts more effectively than any previously available method and does so without distorting the waveform of the signal. Graphical abstract The raw scanning-EMG signal, which can be composed by several discharges of the MU, is processed by the MMLSS algorithm so as to eliminate the artifact interference. Firstly, artifacts are detected for each discharge from the raw signal, obtaining a multi-discharge validity mask that indicates the samples that have been corrupted by artifacts. Secondly, a least-squares smoothing procedure simultaneously operating in the spatial dimension and among the discharges is applied to the raw signal. This second step is performed using only the not contaminated samples according to the validity mask. The resulting MMLSS-processed scanning-EMG signal is clean of artifact interference.

A Comparison of Muscle Activity Between the Cambered and Standard Bar During the Bench Press Exercise

The aim of this study was to compare the electromyographic activity between the standard and cambered bar during the bench press (BP) exercise. Twelve resistance-trained males performed the flat BP with a standard and a cambered bar at selected loads (50%, 70%, and 90% 1RM). Muscle activation assessed by surface electromyography (sEMG) was recorded for the pectoralis major, anterior deltoid, and the lateral and long heads of the triceps brachii during each attempt. A three-way repeated measures ANOVA indicated statistically significant main interaction for bar × load × muscle (p < 0.01); bar × load (p < 0.01); bar × muscle (p < 0.01); load × muscle (p < 0.01). There was also a main effect for the bar (p < 0.01); load (p < 0.01); and muscle group (p < 0.01). The post hoc analysis for the main multiple interaction effect of bar × load × muscle showed a statistically significant increase in sEMG for the standard bar in the pectoralis major compared to the cambered bar at 50% 1RM (p < 0.01) and 90% 1RM (p < 0.01), as well as in the triceps brachii long at 90% 1RM (p < 0.01). Furthermore, a statistically significant decrease in sEMG was registered for the standard bar in the anterior deltoid compared to the cambered bar at 90% 1RM (p = 0.02). The results indicated that the cambered bar was superior in activating the anterior deltoid muscle compared to the standard bar during the BP exercise, whereas the standard bar provided higher pectoralis major and triceps brachii long head sEMG activity at 90% 1RM.

Neurophysiological markers predicting recovery of standing in humans with chronic motor complete spinal cord injury

The appropriate selection of individual-specific spinal cord epidural stimulation (scES) parameters is crucial to re-enable independent standing with self-assistance for balance in individuals with chronic, motor complete spinal cord injury, which is a key achievement toward the recovery of functional mobility. To date, there are no available algorithms that contribute to the selection of scES parameters for facilitating standing in this population. Here, we introduce a novel framework for EMG data processing that implements spectral analysis by continuous wavelet transform and machine learning methods for characterizing epidural stimulation-promoted EMG activity resulting in independent standing. Analysis of standing data collected from eleven motor complete research participants revealed that independent standing was promoted by EMG activity characterized by lower median frequency, lower variability of median frequency, lower variability of activation pattern, lower variability of instantaneous maximum power, and higher total power. Additionally, the high classification accuracy of assisted and independent standing allowed the development of a prediction algorithm that can provide feedback on the effectiveness of muscle-specific activation for standing promoted by the tested scES parameters. This framework can support researchers and clinicians during the process of selection of epidural stimulation parameters for standing motor rehabilitation.

Functional motor control deficits in older FMR1 premutation carriers

Individuals with fragile X mental retardation 1 (FMR1) gene premutations are at increased risk for fragile X-associated tremor/ataxia syndrome (FXTAS) during aging. However, it is unknown whether older FMR1 premutation carriers, with or without FXTAS, exhibit functional motor control deficits compared with healthy individuals. The purpose of this study, therefore, was to determine whether older FMR1 premutation carriers exhibit impaired ability to perform functional motor tasks. Eight FMR1 premutation carriers (age: 58.88 ± 8.36 years) and eight age- and sex-matched healthy individuals (60.13 ± 9.25 years) performed (1) a steady isometric force control task with the index finger at 20% of their maximum voluntary contraction (MVC) and; (2) a single-step task. During the finger abduction task, firing rate of multiple motor units of the first dorsal interosseous (FDI) muscle was recorded. Compared with healthy controls, FMR1 premutation carriers exhibited (1) greater force variability (coefficient of variation of force) during isometric force (1.48 ± 1.02 vs. 0.63 ± 0.37%; P = 0.04); (2) reduced firing rate of multiple motor units during steady force, and; (3) reduced velocity of their weight transfer during stepping (156.62 ± 26.24 vs. 191.86 ± 18.83 cm/s; P = 0.01). These findings suggest that older FMR1 premutation carriers exhibit functional motor control deficits that reflect either subclinical issues associated with premutations independent of FXTAS, or prodromal markers of the development of FXTAS.

Potentiation of the first and second phases of the M wave after maximal voluntary contractions in the biceps brachii muscle

The study was undertaken to examine separately the potentiation of the first and second phases of the M wave in biceps brachii after conditioning maximal voluntary contractions (MVCs) of different durations. M waves were evoked in the biceps brachii muscle before and after isometric MVCs of 1, 3, 6, 10, 30, and 60 s. The amplitude, duration, and area of the first and second phases of monopolar M waves were measured during the 10-min period following each contraction. Our results indicated that the amplitude and area of the M-wave first phase increased after MVCs of long (≥ 30 s) duration (P < 0.05), while it decreased after MVCs of short (≤ 10 s) duration (P < 0.05). The enlargement after the long MVCs persisted for 5 min, whereas the depression after the short contractions lasted only for 15 s. The amplitude of the second phase increased immediately (1 s) after all MVCs tested (P < 0.05), regardless of their duration, and then returned rapidly (10 s) to control levels. Unexpectedly, the amplitude of the second phase decreased below control values between 15 s and 1 min after the MVCs lasting ≥ 6 s (P < 0.05). Our results reinforce the idea that the presence of fatigue is a necessary condition to induce an enlargement of the M-wave first phase and that this enlargement would be greater (and occur sooner) in muscles with a predominance of type II fibers (quadriceps and biceps brachii) compared to type-I predominant muscles (tibialis anterior). The unique findings observed for the M-wave second phase indicate that changes in this phase are highly muscle dependent. Graphical abstract Left panel-Representative examples of M waves recorded in one participant before (control) and at various times after conditioning maximal voluntary contractions (MVCs) of short (a1) and long (a2) duration. Left panel-Time course of recovery of the amplitude of the first (b1) and second (b2) phases of the M wave after conditioning MVCs of different durations.

Effects of ischemic conditioning on maximal voluntary plantar flexion contractions

Intermittent blood flow restriction to local or remote vascular beds induces endogenous protection against ischemia-reperfusion injury in several tissues and organs. When applied non-invasively by placing occlusion cuffs on the limbs, this ischemic conditioning has been shown to elicit an acute ergogenic response. However, the underlying mechanisms behind this phenomenon remain unknown. Prior research suggest that ischemic conditioning may operate via improved motor discharges from the central nervous system, thus enhancing the electrochemical activation and force generation of agonist muscles. Here we show that, for healthy individuals performing maximal voluntary contractions of the plantar flexors, the acute benefit elicited by ischemic conditioning on maximal isometric ankle torque production is largely explained by parallel gains in the surface myoelectrical activity of the triceps surae. However, the magnitude of this response appears to vary between individuals. These findings indicate that enhanced levels of agonist activity contribute to the ergogenic effect of ischemic conditioning during maximal efforts, thereby enabling more direct assessments of neural output following the procedure.

Sarcolemmal membrane excitability during repeated intermittent maximal voluntary contractions

NEW FINDINGS

What is the central question of this study? Is impaired membrane excitability reflected by an increase or by a decrease in M-wave amplitude? What is the main finding and its importance? The magnitude of the M-wave first and second phases changed in completely different ways during intermittent maximal voluntary contractions, leading to the counterintuitive conclusion that it is an increase (and not a decrease) of the M-wave first phase that reflects impaired membrane excitability.

ABSTRACT

The study was undertaken to investigate separately the changes in the first and second phases of the muscle compound action potential (M-wave) during 4 min of intermittent maximal voluntary contractions (MVCs) of the quadriceps. M-waves were evoked by supramaximal single electrical stimulation to the femoral nerve delivered in the resting periods between 48 successive MVCs of 3 s. The amplitude, duration and area of the M-wave first and second phases were measured separately, together with muscle conduction velocity and MVC force. During the intermittent MVCs, the amplitude of the M-wave first phase increased uninterruptedly for the first 3 min (12-16%, P < 0.05) and stabilized thereafter, whereas the second phase initially increased for 55-75 s (11-22%, P < 0.05), but decreased subsequently. The enlargement of the first phase occurred in parallel with an increase in its duration, and concomitantly with a decline in conduction velocity (maximal cross-correlations, 0.89-0.97; time lag, 0 s). Also, a significant temporal association was found between the amplitude of the first phase and MVC force (time lag, 0 s; maximal cross-correlations, 0.85-0.97). Conversely, there was no temporal association between the second phase amplitude and conduction velocity or MVC force (time lag, 73-117 s; maximal cross-correlations, 0.65-0.77). It is concluded that the enlargement of the M-wave first phase is the electrical manifestation of impaired muscle membrane excitability. The results highlight the importance of independently analysing the first and second phases, as only the first phase can be used reliably to detect changes in membrane excitability, while the second might be affected by muscle architecture.

Does vibration superimposed on low-level isometric contraction alter motor unit recruitment strategy?

OBJECTIVE

Beneficial effects, including improved muscle strength and power performance, have been observed during vibration exercise (VE) and partially ascribed to a specific reflex mechanism referred to as Tonic vibration reflex (TVR). TVR involves motor unit (MU) activation synchronized and un-synchronized with the vibration cycle; this suggests VE to alter the temporal MU recruitment strategy. However, the effects of VE on MU recruitment remain poorly understood. This study aims to elucidate the influence of VE on MU recruitment indirectly, by investigating the effects of low-intensity VE on muscle activation.

APPROACH

Twenty volunteers performed isometric contractions on the biceps brachii of the right arm at a baseline (low) force equal to 30% of the maximum voluntary contraction without vibration (control) and with vibration at 20, 30, 40, and 55 Hz. Three vibration amplitudes were employed at 12.5%, 25%, and 50% of the baseline. Mean muscle-fiber conduction velocity (mCV), mean frequency (MF), and root mean square (RMS) value were estimated from surface electromyography as indicators of the alteration in MU recruitment strategies.

MAIN RESULTS

The mCV estimates during VE were significantly (p  <  0.05) higher compared to the control condition. Furthermore, six VE conditions produced significantly larger RMS values compared to control condition. The estimated MF did not show any consistent trend.

SIGNIFICANCE

These results suggest that vibration superimposed on low-level isometric contraction alters the MU recruitment strategy, activating larger and faster MUs.

The Role of the Muscle Brachioradialis in Elbow Flexion: An Electromyographic Study

BACKGROUND

In the classical conception, the brachioradialis is a forearm supinator. The hypothesis of this study was that, at least in certain positions of elbow flexion and forearm rotation, the brachioradialis is, along with the biceps and brachialis, one of the main elbow flexors.

METHODS

Fifteen young healthy male volunteers participated in this research. The activities of the biceps, brachialis and brachioradialis muscles were studied using surface electromyography, while the subjects were performing elbow flexions/extensions with as much strength as possible, forearm in neutral position, then in full pronation, then in full supination. The elbow flexion torques were isokinetically measured at 60°/sec for an arc of 120°.

RESULTS

The biceps, brachialis and brachioradialis muscles were electromyographically very active throughout resisted elbow flexion, in all three investigated positions of forearm rotation. At certain positions, the electromyographic activities were much higher than the maximal voluntary contraction signal. For what concerns specifically the brachioradialis, in all three forearm rotation investigated positions, the activity curve demonstrated a slow increase during the first part of elbow flexion, reaching in 73.3% of subjects its peak at the end of flexion; in the remaining 26.7%, the brachioradialis had a flat activity without significant peak. The activity was slightly higher in supination.

CONCLUSIONS

This study indirectly supports the idea that the brachioradialis is one of the main elbow flexors, especially when the elbow flexion is done with the forearm in supination. This observation could be important in clinical elbow and wrist surgical practice.

End-of-Fiber Signals Strongly Influence the First and Second Phases of the M Wave in the Vastus Lateralis: Implications for the Study of Muscle Excitability

It has been recurrently observed that, for compound muscle action potentials (M wave) recorded over the innervation zone of the vastus lateralis, the descending portion of the first phase generally shows an “inflection” or “shoulder.” We sought to clarify the electrical origin of this shoulder-like feature and examine its implications. M waves evoked by maximal single shocks to the femoral nerve were recorded in monopolar and bipolar configurations from 126 individuals using classical (10-mm recording diameter, 20-mm inter-electrode distance) electrodes and from eight individuals using small electrodes arranged in a linear array. The changes of the M-wave waveform at different positions along the muscle fibers' direction were examined. The shoulder was identified more frequently in monopolar (97%) than in bipolar (46%) M waves. The shoulder of M waves recorded at different distances from the innervation zone had the same latency. Furthermore, the shoulder of the M wave recorded over the innervation zone coincided in latency with the positive peak of that recorded beyond the muscle. The positive phase of the M wave detected 20 mm away from the innervation zone was essentially composed of non-propagating components. The shoulder-like feature in monopolar and bipolar M waves results from the termination of action potentials at the superficial aponeurosis of the vastus lateralis. We conclude that, only the amplitude of the first phase, and not the second, of M waves recorded monopolarly and/or bipolarly in close proximity to the innervation zone can be used reliably to monitor possible changes in muscle membrane excitability.

A masked least-squares smoothing procedure for artifact reduction in scanning-EMG recordings

Scanning-EMG is an electrophysiological technique in which the electrical activity of the motor unit is recorded at multiple points along a corridor crossing the motor unit territory. Correct analysis of the scanning-EMG signal requires prior elimination of interference from nearby motor units. Although the traditional processing based on the median filtering is effective in removing such interference, it distorts the physiological waveform of the scanning-EMG signal. In this study, we describe a new scanning-EMG signal processing algorithm that preserves the physiological signal waveform while effectively removing interference from other motor units. To obtain a cleaned-up version of the scanning signal, the masked least-squares smoothing (MLSS) algorithm recalculates and replaces each sample value of the signal using a least-squares smoothing in the spatial dimension, taking into account the information of only those samples that are not contaminated with activity of other motor units. The performance of the new algorithm with simulated scanning-EMG signals is studied and compared with the performance of the median algorithm and tested with real scanning signals. Results show that the MLSS algorithm distorts the waveform of the scanning-EMG signal much less than the median algorithm (approximately 3.5 dB gain), being at the same time very effective at removing interference components.

Graphical Abstract

A computational model to investigate the effect of pennation angle on surface electromyogram of Tibialis Anterior

This study has described and experimentally validated the differential electrodes surface electromyography (sEMG) model for tibialis anterior muscles during isometric contraction. This model has investigated the effect of pennation angle on the simulated sEMG signal. The results show that there is no significant effect of pennation angle in the range 0° to 20° to the single fibre action potential shape recorded on the skin surface. However, the changes with respect to pennation angle are observed in sEMG amplitude, frequency and fractal dimension. It is also observed that at different levels of muscle contractions there is similarity in the relationships with Root Mean Square, Median Frequency, and Fractal Dimension of the recorded and simulated sEMG signals.

Generation of synthetic surface electromyography signals under fatigue conditions for varying force inputs using feedback control algorithm

Surface electromyography is a non-invasive technique used for recording the electrical activity of neuromuscular systems. These signals are random, complex and multi-component. There are several techniques to extract information about the force exerted by muscles during any activity. This work attempts to generate surface electromyography signals for various magnitudes of force under isometric non-fatigue and fatigue conditions using a feedback model. The model is based on existing current distribution, volume conductor relations, the feedback control algorithm for rate coding and generation of firing pattern. The result shows that synthetic surface electromyography signals are highly complex in both non-fatigue and fatigue conditions. Furthermore, surface electromyography signals have higher amplitude and lower frequency under fatigue condition. This model can be used to study the influence of various signal parameters under fatigue and non-fatigue conditions.

Associations between motor unit action potential parameters and surface EMG features

The surface interference EMG signal provides some information on the neural drive to muscles. However, the association between neural drive to muscle and muscle activation has long been debated with controversial indications due to the unavailability of motor unit population data. In this study, we clarify the potential and limitations of interference EMG analysis to infer motor unit recruitment strategies with an experimental investigation of several concurrently active motor units and of the associated features of the surface EMG. For this purpose, we recorded high-density surface EMG signals during linearly increasing force contractions of the tibialis anterior muscle, up to 70% of maximal force. The recruitment threshold (RT), conduction velocity (MUCV), median frequency (MDF_MU), and amplitude (RMS_MU) of action potentials of 587 motor units from 13 individuals were assessed and associated with features of the interference EMG. MUCV was positively associated with RT (R² = 0.64 ± 0.14), whereas MDF_MU and RMS_MU showed a weaker relation with RT (R² = 0.11 ± 0.11 and 0.39 ± 0.24, respectively). Moreover, the changes in average conduction velocity estimated from the interference EMG predicted well the changes in MUCV (R² = 0.71), with a strong association to ankle dorsiflexion force (R² = 0.81 ± 0.12). Conversely, both the average EMG MDF and RMS were poorly associated with motor unit recruitment. These results clarify the limitations of EMG spectral and amplitude analysis in inferring the neural strategies of muscle control and indicate that, conversely, the average conduction velocity could provide relevant information on these strategies.NEW & NOTEWORTHY The surface EMG provides information on the neural drive to muscles. However, the associations between EMG features and neural drive have been long debated due to unavailability of motor unit population data. Here, by using novel highly accurate decomposition of the EMG, we related motor unit population behavior to a wide range of voluntary forces. The results fully clarify the potential and limitation of the surface EMG to provide estimates of the neural drive to muscles.

How Arch Support Insoles Help Persons with Flatfoot on Uphill and Downhill Walking

The main purpose of this study was to investigate the effect of arch support insoles on uphill and downhill walking of persons with flatfoot. Sixteen healthy college students with flatfoot were recruited in this study. Their heart rate, peak oxygen uptake (VO₂), and median frequency (MDF) of surface electromyogram were recorded and analyzed. Nonparametric Wilcoxon signed-rank test was used for statistical analysis. The main results were as follows: (a) peak VO₂ significantly decreased with arch support insoles compared with flat insoles during uphill and downhill walking (arch support insole versus flat insole: uphill walking, 20.7 ± 3.6 versus 31.6 ± 5.5; downhill walking, 10.9 ± 2.3 versus 16.9 ± 4.2); (b) arch support insoles could reduce the fatigue of the rectus femoris muscle during downhill walking (MDF slope of arch support insole: 0.03 ± 1.17, flat insole: −6.56 ± 23.07); (c) insole hardness would increase not only the physical sensory input but also the fatigue of lower-limb muscles particularly for the rectus femoris muscle (MDF slope of arch support insole: −1.90 ± 1.60, flat insole: −0.83 ± 1.10) in persons with flatfoot during uphill walking. The research results show that arch support insoles could effectively be applied to persons with flatfoot to aid them during uphill and downhill walking.

Effects of auditory distraction on voluntary movements: exploring the underlying mechanisms associated with parallel processing

Highly demanding cognitive-motor tasks can be negatively influenced by the presence of auditory stimuli. The human brain attempts to partially suppress the processing of potential distractors in order that motor tasks can be completed successfully. The present study sought to further understand the attentional neural systems that activate in response to potential distractors during the execution of movements. Nineteen participants (9 women and 10 men) were administered isometric ankle-dorsiflexion tasks for 10 s at a light intensity. Electroencephalography was used to assess the electrical activity in the brain, and a music excerpt was used to distract participants. Three conditions were administered: auditory distraction during the execution of movement (auditory distraction; AD), movement execution in the absence of auditory distraction (control; CO), and auditory distraction in the absence of movement (stimulus-only; SO). AD was compared with SO to identify the mechanisms underlying the attentional processing associated with attentional shifts from internal association (task-related) to external (task-unrelated) sensory cues. The results of the present study indicated that the EMG amplitude was not compromised when the auditory stimulus was administered. Accordingly, EEG activity was upregulated at 0.368 s in AD when compared to SO. Source reconstruction analysis indicated that right and central parietal regions of the cortex activated at 0.368 s in order to reduce the processing of task-irrelevant stimuli during the execution of movements. The brain mechanisms that underlie the control of potential distractors during exercise were possibly associated with the activity of the frontoparietal network.

Assessment of Motor Units in Neuromuscular Disease

The motor unit comprises the anterior horn cell, its axon, and the muscle fibers that it innervates. Although the true number of motor units is unknown, the number of motor units appears to vary greatly between different muscles and between different individuals. Assessment of the number and function of motor units is needed in diseases of the anterior horn cell and other motor nerve disorders. Amyotrophic lateral sclerosis is the most important disease of anterior horn cells. The need for an effective biomarker for assessing disease progression and for use in clinical trials in amyotrophic lateral sclerosis has stimulated the study of methods to measure the number of motor units. Since 1970 a number of different methods, including the incremental, F-wave, multipoint, and statistical methods, have been developed but none has achieved widespread applicability. Two methods (MUNIX and the multipoint incremental method) are in current use across multiple centres and are discussed in detail in this review, together with other recently published methods. Imaging with magnetic resonance and ultrasound is increasingly being applied to this area. Motor unit number estimates have also been applied to other neuromuscular diseases such as spinal muscular atrophy, compression neuropathies, and prior poliomyelitis. The need for an objective measure for the assessment of motor units remains tantalizingly close but unfulfilled in 2016.

The Isokinetic and Electromyographic Assessment of Knee Muscles Strength in the Short- and Long-Term Type 2 Diabetes

BACKGROUND

Type 2 diabetes (T2DM) patients are subject to muscle weakness.

OBJECTIVES

The aim of the study was an assessment of electromyographic (EMG) activity of knee muscles during isometric maximal voluntary contraction in the different disease durations of T2DM.

METHODS

Eighteen patients with less than 10 years and twelve patients with more than 10 years of T2DM were compared with nineteen matched healthy control subjects. EMG of flexor and extensor muscles of knee concurrently with isometric maximal peak torque of knee flexion and extension at 75 degrees of knee flexion were recorded in three groups.

RESULTS

Isometric maximal peak torque of extension and root mean squared (RMS) of vastus lateralis and medial hamstring in the healthy control was significantly higher than both patient groups. Whenever the maximal isometric peak flexion torque was not significantly different between groups, the mean power frequency (MPF) of flexor muscles especially medial hamstrings were higher in the short-term T2DM than healthy control groups. The two factors, gender and age, had significant effect on maximal peak torque and RMS of knee muscles.

CONCLUSIONS

EMG could show the effect of T2DM, gender and age on knee muscles activity. It seems that the medial hamstring was the most sensitive muscle of knee compartment to show the effect of T2DM and difference of short and long-term T2DM in EMG study.

Influence of timing variability between motor unit potentials on M-wave characteristics

The transient enlargement of the compound muscle action potential (M wave) after a conditioning contraction is referred to as potentiation. It has been recently shown that the potentiation of the first and second phases of a monopolar M wave differed drastically; namely, the first phase remained largely unchanged, whereas the second phase underwent a marked enlargement and shortening. This dissimilar potentiation of the first and second phases has been suggested to be attributed to a transient increase in conduction velocity after the contraction. Here, we present a series of simulations to test if changes in the timing variability between motor unit potentials (MUPs) can be responsible for the unequal potentiation (and shortening) of the first and the second M-wave phases. We found that an increase in the mean motor unit conduction velocity resulted in a marked enlargement and narrowing of both the first and second M-wave phases. The enlargement of the first phase caused by a global increase in motor unit conduction velocities was apparent even for the electrode located over the innervation zone and became more pronounced with increasing distance to the innervation zone, whereas the potentiation of the second phase was largely independent of electrode position. Our simulations indicate that it is unlikely that an increase in motor unit conduction velocities (accompanied or not by changes in their distribution) could account for the experimental observation that only the second phase of a monopolar M wave, but not the first, is enlarged after a brief contraction. However, the combination of an increase in the motor unit conduction velocities and a spreading of the motor unit activation times could potentially explain the asymmetric potentiation of the M-wave phases.

The slow component of pulmonary O2 uptake accompanies peripheral muscle fatigue during high-intensity exercise

During constant-power output (PO) exercise above lactate threshold (LT), pulmonary O2 uptake (V̇o2p) features a developing slow component (V̇o2pSC). This progressive increase in O2 cost of exercise is suggested to be related to the effects of muscle fatigue development. We hypothesized that peripheral muscle fatigue as assessed by contractile impairment would be associated with the V̇o2pSC. Eleven healthy men were recruited to perform four constant-PO tests at an intensity corresponding to ∼Δ60 (very heavy, VH) where Δ is 60% of the difference between LT and peak V̇o2p. The VH exercise was completed for each of 3, 8, 13, and 18 min (i.e., VH3, VH8, VH13, VH18) with each preceded by 3 min of cycling at 20 W. Peripheral muscle fatigue was assessed via pre- vs. postexercise measurements of quadriceps torque in response to brief trains of electrical stimulation delivered at low (10 Hz) and high (50 Hz) frequencies. During exercise, breath-by-breath V̇o2p was measured by mass spectrometry and volume turbine. The magnitude of V̇o2pSC increased ( P < 0.05) from 224 ± 81 ml/min at VH3 to 520 ± 119, 625 ± 134, and 678 ± 156 ml/min at VH8, VH13, and VH18, respectively. The ratio of the low-to-high frequency (10/50 Hz) response was reduced ( P < 0.05) at VH3 (−12 ± 9%) and further reduced ( P < 0.05) at VH8 (−25 ± 11%), VH13 (−42 ± 19%), and VH18 (−46 ± 16%), mirroring the temporal pattern of V̇o2pSC development. The reduction in 10/50 Hz ratio was correlated ( P < 0.001, r2 = 0.69) with V̇o2pSC amplitude. The temporal and quantitative association of decrements in muscle torque production and V̇o2pSC suggest a common physiological mechanism between skeletal muscle fatigue and loss of muscle efficiency.