Does the frequency content of the surface mechanomyographic signal reflect motor unit firing rates? A brief review

No sex differences in time-to-task failure and neuromuscular patterns of response during submaximal, bilateral, isometric leg extensions

BACKGROUND

In general, it has been suggested that females are more fatigue-resistant than males, with the magnitude of difference being most pronounced during low-intensity sustained contractions. However, the mechanisms for the apparent sex difference have not yet been fully elucidated in the literature. This study aimed to examine sex-related differences in fatigability and patterns of neuromuscular responses for surface electromyographic (sEMG) and mechanomyographic (sMMG) amplitude and frequency (MPF) characteristics during a sustained submaximal bilateral, isometric leg extension muscle action.

METHODS

A sample of 20 young recreationally active males and females with previous resistance training experience performed a sustained, submaximal, bilateral isometric leg extension until task failure. Time-to-task failure was compared using a nonparametric bootstrap of the 95% confidence interval for the mean difference between males and females. Additionally, patterns of response for sEMG and sMMG amplitude and MPF of the dominant limb were examined using linear mixed effect models.

RESULTS

There were no differences in time-to-task failure between males and females. Additionally, neuromuscular responses revealed similar patterns of responses between males and females. Interestingly, sEMG amplitude and sMMG amplitude and MPF all revealed non-linear responses, while sEMG MPF demonstrated linear responses.

CONCLUSION

These data revealed that time-to-task failure was not different between males and females during sustained submaximal bilateral, isometric leg extension. Interestingly, the parallel, non-linear, increases in sEMG and sMMG amplitude may indicate fatigue induced increases in motor unit recruitment, while the parallel decreases in sMMG MPF may be explained by the intrinsic properties of later recruited motor units, which may have inherently lower firing rates than those recruited earlier.

3D muscle networks based on vibrational mechanomyography

Objective. Muscle network modeling maps synergistic control during complex motor tasks. Intermuscular coherence (IMC) is key to isolate synchronization underlying coupling in such neuromuscular control. Model inputs, however, rely on electromyography, which can limit the depth of muscle and spatial information acquisition across muscle fibers.Approach. We introduce three-dimensional (3D) muscle networks based on vibrational mechanomyography (vMMG) and IMC analysis to evaluate the functional co-modulation of muscles across frequency bands in concert with the longitudinal, lateral, and transverse directions of muscle fibers. vMMG is collected from twenty subjects using a bespoke armband of accelerometers while participants perform four hand gestures. IMC from four superficial muscles (flexor carpi radialis, brachioradialis, extensor digitorum communis, and flexor carpi ulnaris) is decomposed using matrix factorization into three frequency bands. We further evaluate the practical utility of the proposed technique by analyzing the network responses to various sensor-skin contact force levels, studying changes in quality, and discriminative power of vMMG.Main results. Results show distinct topological differences, with coherent coupling as high as 57% between specific muscle pairs, depending on the frequency band, gesture, and direction. No statistical decrease in signal strength was observed with higher contact force.Significance. Results support the usability vMMG as a tool for muscle connectivity analyses and demonstrate the use of IMC as a new feature space for hand gesture classification. Comparison of spectrotemporal and muscle network properties between levels of force support the robustness of vMMG-based network models to variations in tissue compression. We argue 3D models of vMMG-based muscle networks provide a new foundation for studying synergistic muscle activation, particularly in out-of-clinic scenarios where electrical recording is impractical.

Electromyographic and mechanomyographic responses of the biceps brachii during concentric and eccentric muscle actions to failure at high and low relative loads

PURPOSE

This study examined neuromuscular responses of the biceps brachii (BB) for concentric and eccentric muscle actions during bilateral, dynamic constant external resistance (DCER), reciprocal forearm flexions and extensions to failure at high (80% 1 repetition maximum [1RM]) and low (30% 1RM) relative loads.

METHODS

Nine women completed 1RM testing and repetitions to failure (RTF) at 30 and 80% 1RM. Electromyographic (EMG) and mechanomyographic (MMG) amplitude (AMP) and mean power frequency (MPF) signals were measured from the BB. Analyses included repeated measures ANOVAs (p < 0.05) and post-hoc pairwise comparisons with Bonferroni corrected alpha of p < 0.008 and p < 0.01 for between and within factor pairwise comparisons, respectively.

RESULTS

EMG AMP and MPF were significantly greater for concentric than eccentric muscle actions, regardless of load or time. However, time course of change analysis revealed parallel increases in EMG AMP for concentric and eccentric muscle actions during the RTF trials at 30% 1RM, but no change at 80% 1RM. There were significant increases in MMG AMP during concentric muscle actions, but decreases or no change during eccentric muscle actions. EMG and MMG MPF decreased over time, regardless of muscle action type and loading condition.

CONCLUSION

The greater EMG AMP and MPF values during concentric compared to eccentric muscle actions may reflect the difference in the efficiency characteristic of these muscle actions. The neuromuscular responses suggested that fatigue may be mediated by recruitment of additional motor units with lower firing rates during concentric muscle actions, and changes in motor unit synchronization during eccentric muscle actions.

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

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

Mechanomyographic Analysis for Muscle Activity Assessment during a Load-Lifting Task

The purpose of this study was to compare electromyographic (EMG) with mechanomyographic (MMG) recordings during isometric conditions, and during a simulated load-lifting task. Twenty-two males (age: 25.5 ± 5.3 years) first performed maximal voluntary contractions (MVC) and submaximal isometric contractions of upper limb muscles at 25%, 50% and 75% MVC. Participants then executed repetitions of a functional activity simulating a load-lifting task above shoulder level, at 25%, 50% and 75% of their maximum activity (based on MVC). The low-frequency part of the accelerometer signal (<5 Hz) was used to segment the six phases of the motion. EMG and MMG were both recorded during the entire experimental procedure. Root mean square (RMS) and mean power frequency (MPF) were selected as signal extraction features. During isometric contractions, EMG and MMG exhibited similar repeatability scores. They also shared similar RMS vs. force relationship, with RMS increasing to 75% MVC and plateauing to 100%. MPF decreased with increasing force to 75% MVC. In dynamic condition, RMSMMG exhibited higher sensitivity to changes in load than RMSEMG. These results confirm the feasibility of MMG measurements to be used during functional activities outside the laboratory. It opens new perspectives for future applications in sports science, ergonomics and human-machine interface conception.

Load-Specific Performance Fatigability, Coactivation, and Neuromuscular Responses to Fatiguing Forearm Flexion Muscle Actions in Women

ABSTRACT

Benitez, B, Dinyer-McNeeley, TK, McCallum, L, Kwak, M, Succi, PJ, and Bergstrom, HC. Load-specific performance fatigability, coactivation, and neuromuscular responses to fatiguing forearm flexion muscle actions in women. J Strength Cond Res 37(4): 769-779, 2023-This study examined the effects of fatiguing, bilateral, dynamic constant external resistance (DCER) forearm flexion on performance fatigability, coactivation, and neuromuscular responses of the biceps brachii (BB) and triceps brachii (TB) at high (80% 1 repetition maximum [1RM]) and low (30% 1RM) relative loads in women. Ten women completed 1RM testing and repetitions to failure (RTF) at 30 and 80% 1RM. Maximal voluntary isometric force was measured before and after RTF. Electromyographic (EMG) and mechanomyographic (MMG) amplitude (AMP) and mean power frequency (MPF) signals were measured from the BB and TB. Performance fatigability was greater (p < 0.05) after RTF at 30% (%∆ = 41.56 ± 18.61%) than 80% (%∆ = 19.65 ± 8.47%) 1RM. There was an increase in the coactivation ratio (less coactivation) between the initial and final repetitions at 30%, which may reflect greater increases in agonist muscle excitation (EMG AMP) relative to the antagonist for RTF at 30% than 80% 1RM. The initial repetitions EMG AMP was greater for 80% than 30% 1RM, but there was no difference between loads for the final repetitions. For both loads, there were increases in EMG MPF and MMG AMP and decreases in MMG MPF that may suggest fatigue-dependent recruitment of higher-threshold motor units. Thus, RTF at 30 and 80% 1RM during DCER forearm flexion may not necessitate additional muscle excitation to the antagonist muscle despite greater fatigability after RTF at 30% 1RM. These specific acute performance and neuromuscular responses may provide insight into the unique mechanism underlying adaptations to training performed at varying relative loads.

Analysis of anthropometrics and mechanomyography signals as forearm flexion, pronation and supination torque predictors

This study aimed to analyze anthropometrics and mechanomyography (MMG) signals as forearm flexion, pronation, and supination torque predictors. 25 young, healthy, male participants performed isometric forearm flexion, pronation, and supination tasks from 20 to 100% maximal voluntary isometric contraction (MVIC) while maintaining 90° at the elbow joint. Nine anthropometric measures were recorded, and MMG signals from the biceps brachii (BB), brachialis (BRA), and brachioradialis (BRD) muscles were digitally acquired using triaxial accelerometers. These were then correlated with torque values. Significant positive correlations were found for arm circumference (CA) and MMG root mean square (RMS) values with flexion torque. Flexion torque might be predicted using CA (r = 0.426–0.575), a pseudo for muscle size while MMG_RMS (r = 0.441), an indication of muscle activation.

Estimation of Knee Extension Force Using Mechanomyography Signals Based on GRA and ICS-SVR

During lower-extremity rehabilitation training, muscle activity status needs to be monitored in real time to adjust the assisted force appropriately, but it is a challenging task to obtain muscle force noninvasively. Mechanomyography (MMG) signals offer unparalleled advantages over sEMG, reflecting the intention of human movement while being noninvasive. Therefore, in this paper, based on MMG, a combined scheme of gray relational analysis (GRA) and support vector regression optimized by an improved cuckoo search algorithm (ICS-SVR) is proposed to estimate the knee joint extension force. Firstly, the features reflecting muscle activity comprehensively, such as time-domain features, frequency-domain features, time–frequency-domain features, and nonlinear dynamics features, were extracted from MMG signals, and the relational degree was calculated using the GRA method to obtain the correlation features with high relatedness to the knee joint extension force sequence. Then, a combination of correlated features with high relational degree was input into the designed ICS-SVR model for muscle force estimation. The experimental results show that the evaluation indices of the knee joint extension force estimation obtained by the combined scheme of GRA and ICS-SVR were superior to other regression models and could estimate the muscle force with higher estimation accuracy. It is further demonstrated that the proposed scheme can meet the need of muscle force estimation required for rehabilitation devices, powered prostheses, etc.

Effects of Endurance Cycling on Mechanomyographic Median Power Frequency of the Vastus Lateralis

This study examined the effects of cycling training on mechanomyographic median power frequency (MMGMDF)–torque relationships of the vastus lateralis (VL). Ten males (Age ± SD; 20.20 ± 1.87 years) and 14 females (21.93 ± 5.33 years) performed isometric trapezoidal muscle actions with the knee extensors at 40% maximal voluntary contraction (MVC) before (PRE) and following 10 weeks of cycling training at the same absolute submaximal torque as pre-training (POSTABS). MMGMDF–torque relationships (increasing and decreasing segment) were log-transformed and b terms (slopes) were calculated. MMGMDF was averaged during steady torque. For POSTABS, the b terms for the females (0.133 ± 0.190) were greater than for the males (−0.083 ± 0.200; p = 0.013) and compared to PRE (0.008 ± 0.161; p = 0.036). At PRE, the b terms for the linearly increasing-muscle action (0.123 ± 0.192) were greater compared to the linearly decreasing-muscle action (−0.061 ± 0.188; p < 0.001), whereas no differences existed between muscle actions for POSTABS (p > 0.05). In conclusion, 10 weeks of cycling training resulted in different motor unit (MU) control strategies between sexes and altered MU control strategies between muscle actions for the VL during a moderate-intensity contraction.

Synergistic Upper-limb Functional Muscle Connectivity using Acoustic Mechanomyography

Functional connectivity is a critical concept in describing synergistic muscle synchronization for the execution of complex motor tasks. Muscle synchronization is typically derived from the decomposition of intermuscular coherence (IMC) at different frequency bands through electromyography (EMG) signal analysis with limited out-of-clinic applications. In this investigation, we introduce muscle network analysis to assess the coordination and functional connectivity of muscles based on mechanomyography (MMG), focused on a targeted group of muscles that are typically active in the conduction of activities of daily living using the upper limb. In this regard, functional muscle networks are evaluated in this paper for ten able-bodied participants and three amputees. MMG activity was acquired from a custom-made wearable MMG armband placed over four superficial muscles around the forearm (i.e., flexor carpi radialis (FCR), brachioradialis (BR), extensor digitorum communis (EDC), and flexor carpi ulnaris (FCU)) while participants performed four different hand gestures. The results of connectivity analysis at multiple frequency bands showed significant topographical differences across gestures for low (< 5Hz) and high (> 12 Hz) frequencies and observable differences between able-bodied and amputee subjects. These findings show evidence that MMG can be used for the analysis of functional muscle connectivity and mapping of synergistic synchronization of upper-limb muscles in complex upper-limb tasks. The new physiological modality further provides key insights into the neural circuitry of motor coordination and offers the concomitant outcomes of demonstrating the feasibility of MMG to map muscle coherence from a neurophysiological perspective as well as providing the mechanistic basis for its translation into human-robot interfaces.

Comparing the Accuracy of Visual and Computerized Onset Detection Methods on Simulated Electromyography Signals with Varying Signal-to-Noise Ratios

Electromyography (EMG) onsets determined by computerized detection methods have been compared against the onsets selected by experts through visual inspection. However, with this type of approach, the true onset remains unknown, making it impossible to determine if computerized detection methods are better than visual detection (VD) as they can only be as good as what the experts select. The use of simulated signals allows for all aspects of the signal to be precisely controlled, including the onset and the signal-to-noise ratio (SNR). This study compared three onset detection methods: approximated generalized likelihood ratio, double threshold (DT), and VD determined by eight trained individuals. The selected onset was compared against the true onset in simulated signals which varied in the SNR from 5 to 40 dB. For signals with 5 dB SNR, the VD method was significantly better, but for SNRs of 20 dB or greater, no differences existed between the VD and DT methods. The DT method is recommended as it can improve objectivity and reduce time of analysis when determining EMG onsets. Even for the best-quality signals (SNR of 40 dB), all the detection methods were off by 15-30 ms from the true onset and became progressively more inaccurate as the SNR decreased. Therefore, although all the detection methods provided similar results, they can be off by 50-80 ms from the true onset as the SNR decreases to 10 dB. Caution must be used when interpreting EMG onsets, especially on signals where the SNR is low or not reported at all.

Assessment of muscle activity using electrical stimulation and mechanomyography: a systematic review

This research has proved that mechanomyographic (MMG) signals can be used for evaluating muscle performance. Stimulation of the lost physiological functions of a muscle using an electrical signal has been determined crucial in clinical and experimental settings in which voluntary contraction fails in stimulating specific muscles. Previous studies have already indicated that characterizing contractile properties of muscles using MMG through neuromuscular electrical stimulation (NMES) showed excellent reliability. Thus, this review highlights the use of MMG signals on evaluating skeletal muscles under electrical stimulation. In total, 336 original articles were identified from the Scopus and SpringerLink electronic databases using search keywords for studies published between 2000 and 2020, and their eligibility for inclusion in this review has been screened using various inclusion criteria. After screening, 62 studies remained for analysis, with two additional articles from the bibliography, were categorized into the following: (1) fatigue, (2) torque, (3) force, (4) stiffness, (5) electrode development, (6) reliability of MMG and NMES approaches, and (7) validation of these techniques in clinical monitoring. This review has found that MMG through NMES provides feature factors for muscle activity assessment, highlighting standardized electromyostimulation and MMG parameters from different experimental protocols. Despite the evidence of mathematical computations in quantifying MMG along with NMES, the requirement of the processing speed, and fluctuation of MMG signals influence the technique to be prone to errors. Interestingly, although this review does not focus on machine learning, there are only few studies that have adopted it as an alternative to statistical analysis in the assessment of muscle fatigue, torque, and force. The results confirm the need for further investigation on the use of sophisticated computations of features of MMG signals from electrically stimulated muscles in muscle function assessment and assistive technology such as prosthetics control.

A Multimodal Intention Detection Sensor Suite for Shared Autonomy of Upper-Limb Robotic Prostheses

Neurorobotic augmentation (e.g., robotic assist) is now in regular use to support individuals suffering from impaired motor functions. A major unresolved challenge, however, is the excessive cognitive load necessary for the human–machine interface (HMI). Grasp control remains one of the most challenging HMI tasks, demanding simultaneous, agile, and precise control of multiple degrees-of-freedom (DoFs) while following a specific timing pattern in the joint and human–robot task spaces. Most commercially available systems use either an indirect mode-switching configuration or a limited sequential control strategy, limiting activation to one DoF at a time. To address this challenge, we introduce a shared autonomy framework centred around a low-cost multi-modal sensor suite fusing: (a) mechanomyography (MMG) to estimate the intended muscle activation, (b) camera-based visual information for integrated autonomous object recognition, and (c) inertial measurement to enhance intention prediction based on the grasping trajectory. The complete system predicts user intent for grasp based on measured dynamical features during natural motions. A total of 84 motion features were extracted from the sensor suite, and tests were conducted on 10 able-bodied and 1 amputee participants for grasping common household objects with a robotic hand. Real-time grasp classification accuracy using visual and motion features obtained 100%, 82.5%, and 88.9% across all participants for detecting and executing grasping actions for a bottle, lid, and box, respectively. The proposed multimodal sensor suite is a novel approach for predicting different grasp strategies and automating task performance using a commercial upper-limb prosthetic device. The system also shows potential to improve the usability of modern neurorobotic systems due to the intuitive control design.

Interlimb Neuromuscular Responses During Fatiguing, Bilateral, Leg Extension Exercise at a Moderate Versus High Load

This study determined the load- and limb-dependent neuromuscular responses to fatiguing, bilateral, leg extension exercise performed at a moderate (50% one-repetition maximum [1RM]) and high load (80% 1RM). Twelve subjects completed 1RM testing for the bilateral leg extension, followed by repetitions to failure at 50% and 80% 1RM, on separate days. During all visits, the electromyographic (EMG) and mechanomyographic (MMG), amplitude (AMP) and mean power frequency (MPF) signals were recorded from the vastus lateralis of both limbs. There were no limb-dependent responses for any of the neuromuscular signals and no load-dependent responses for EMG AMP, MMG AMP, or MMG MPF (p = .301-.757), but there were main effects for time that indicated increases in EMG and MMG AMP and decreases in MMG MPF. There was a load-dependent decrease in EMG MPF over time (p = .032) that suggested variability in the mechanism responsible for metabolite accumulation at moderate versus high loads. These findings suggested that common drive from the central nervous system was used to modulate force during bilateral leg extension performed at moderate and high loads.

New advances in mechanomyography sensor technology and signal processing: Validity and intrarater reliability of recordings from muscle

Introduction

The Mechanical Muscle Activity with Real-time Kinematics project aims to develop a device incorporating wearable sensors for arm rehabilitation following stroke. These will record kinematic activity using inertial measurement units and mechanical muscle activity. The gold standard for measuring muscle activity is electromyography; however, mechanomyography offers an appropriate alterative for our home-based rehabilitation device. We have patent filed a new laboratory-tested device that combines an inertial measurement unit with mechanomyography. We report on the validity and reliability of the mechanomyography against electromyography sensors.

Methods

In 18 healthy adults (27–82 years), mechanomyography and electromyography recordings were taken from the forearm flexor and extensor muscles during voluntary contractions. Isometric contractions were performed at different percentages of maximal force to examine the validity of mechanomyography. Root-mean-square of mechanomyography and electromyography was measured during 1 s epocs of isometric flexion and extension. Dynamic contractions were recorded during a tracking task on two days, one week apart, to examine reliability of muscle onset timing.

Results

Reliability of mechanomyography onset was high (intraclass correlation coefficient = 0.78) and was comparable with electromyography (intraclass correlation coefficient = 0.79). The correlation between force and mechanomyography was high (R² = 0.94).

Conclusion

The mechanomyography device records valid and reliable signals of mechanical muscle activity on different days.

The Time Course of Changes in Neuromuscular Responses During the Performance of Leg Extension Repetitions to Failure Below and Above Critical Resistance in Women

Dinyer, TK, Byrd, MT, Succi, PJ, and Bergstrom, HC. The time course of changes in neuromuscular responses during the performance of leg extension repetitions to failure below and above critical resistance in women. J Strength Cond Res XX(X): 000-000, 2020-Critical resistance (CR) is the highest sustainable resistance that can be completed for an extended number of repetitions. Exercise performed below (CR-15%) and above (CR+15%) CR may represent 2 distinct intensities that demonstrate separate mechanisms of fatigue. Electromyography (EMG) and mechanomyography (MMG) have been used to examine the mechanism of fatigue during resistance exercise. Therefore, the purposes of this study were to (a) compare the patterns of responses and time course of changes in neuromuscular parameters (EMG and MMG amplitude [AMP] and mean power frequency [MPF]) during the performance of repetitions to failure at CR-15% and CR+15% and (b) identify the motor unit activation strategy that best describes the fatigue-induced changes in the EMG and MMG signals at CR-15% and CR+15%. Ten women completed one repetition maximum (1RM) testing and repetitions to failure at 50, 60, 70, and 80% 1RM (to determine CR), and at CR-15% and CR+15% on the leg extension. During all visits, EMG and MMG signals were measured from the vastus lateralis. There were similar patterns of responses in the neuromuscular parameters, and time-dependent changes in EMG AMP and EMG MPF, but not MMG AMP or MMG MPF, during resistance exercise performed at CR-15% and CR+15% (p < 0.05). The onset of fatigue occurred earlier for EMG AMP, but later for EMG MPF, during repetitions performed at CR+15% compared with those performed at CR-15%. Thus, resistance exercise performed below and above CR represented 2 distinct intensities that were defined by different neuromuscular fatigue mechanisms but followed similar motor unit activation strategies.

Performance fatigability and neuromuscular responses for bilateral versus unilateral leg extensions in women

The purpose of this study was to compare isokinetic peak torque and the patterns of responses for electromyographic (EMG) and mechanomyographic (MMG), amplitude (AMP) and mean power frequency (MPF) for bilateral (BL) versus unilateral (UL), maximal, isokinetic leg extensions. Eleven recreationally trained women (Mean ± SD: age 22.9 ± 0.9 yrs; body mass 60.5 ± 10.1 kg; height 167.2 ± 6.4 cm) performed 50 maximal, BL and UL isokinetic leg extensions at 60° s^-1 on separate days. Electromyographic and MMG signals from the vastus lateralis of the nondominant leg were recorded. Five separate 2 (Condition [BL and UL]) × 10 (Repetitions [5-50]) repeated measures ANOVAs were performed to examine normalized EMG AMP, EMG MPF, MMG AMP, MMG MPF, and isokinetic torque. The results indicated no significant interactions or main effects for EMG AMP and MMG AMP. There were significant interactions for normalized isokinetic peak torque (p < 0.001, η²_p = 0.493) and MMG MPF (p = 0.003, η²_p = 0.234). For EMG MPF, there was no significant interaction, but significant main effects for Condition (p = 0.003, η²_p = 0.607) and Repetitions (p < 0.001, η²_p = 0.805). The current findings demonstrated greater performance fatigability for UL than BL leg extensions. Both modalities exhibited similar patterns of neuromuscular responses that were consistent with the Muscular Wisdom hypothesis.

Inter- and Intra-Individual Differences in EMG and MMG during Maximal, Bilateral, Dynamic Leg Extensions

The purpose of this study was to compare the composite, inter-individual, and intra-individual differences in the patterns of responses for electromyographic (EMG) and mechanomyographic (MMG) amplitude (AMP) and mean power frequency (MPF) during fatiguing, maximal, bilateral, and isokinetic leg extension muscle actions. Thirteen recreationally active men (age = 21.7 ± 2.6 years; body mass = 79.8 ± 11.5 kg; height = 174.2 ± 12.7 cm) performed maximal, bilateral leg extensions at 180°·s⁻¹ until the torque values dropped to 50% of peak torque for two consecutive repetitions. The EMG and MMG signals from the vastus lateralis (VL) muscles of both limbs were recorded. Four 2(Leg) × 19(time) repeated measures ANOVAs were conducted to examine mean differences for EMG AMP, EMG MPF, MMG AMP, and MMG MPF between limbs, and polynomial regression analyses were performed to identify the patterns of neuromuscular responses. The results indicated no significant differences between limbs for EMG AMP (p = 0.44), EMG MPF (p = 0.33), MMG AMP (p = 0.89), or MMG MPF (p = 0.52). Polynomial regression analyses demonstrated substantial inter-individual variability. Inferences made regarding the patterns of neuromuscular responses to fatiguing and bilateral muscle actions should be considered on a subject-by-subject basis.

Towards Wearable Comprehensive Capture and Analysis of Skeletal Muscle Activity during Human Locomotion

Background: Motion capture and analyzing systems are essential for understanding locomotion. However, the existing devices are too cumbersome and can be used indoors only. A newly-developed wearable motion capture and measurement system with multiple sensors and ultrasound imaging was introduced in this study. Methods: In ten healthy participants, the changes in muscle area and activity of gastrocnemius, plantarflexion and dorsiflexion of right leg during walking were evaluated by the developed system and the Vicon system. The existence of significant changes in a gait cycle, comparison of the ankle kinetic data captured by the developed system and the Vicon system, and test-retest reliability (evaluated by the intraclass correlation coefficient, ICC) in each channel’s data captured by the developed system were examined. Results: Moderate to good test-retest reliability of various channels of the developed system (0.512 ≤ ICC ≤ 0.988, p < 0.05), significantly high correlation between the developed system and Vicon system in ankle joint angles (0.638R ≤ 0.707, p < 0.05), and significant changes in muscle activity of gastrocnemius during a gait cycle (p < 0.05) were found. Conclusion: A newly developed wearable motion capture and measurement system with ultrasound imaging that can accurately capture the motion of one leg was evaluated in this study, which paves the way towards real-time comprehensive evaluation of muscles and joint motions during different activities in both indoor and outdoor environments.

Surface mechanomyography and electromyography provide non-invasive indices of inspiratory muscle force and activation in healthy subjects

The current gold standard assessment of human inspiratory muscle function involves using invasive measures of transdiaphragmatic pressure (Pdi) or crural diaphragm electromyography (oesEMGdi). Mechanomyography is a non-invasive measure of muscle vibration associated with muscle contraction. Surface electromyogram and mechanomyogram, recorded transcutaneously using sensors placed over the lower intercostal spaces (sEMGlic and sMMGlic respectively), have been proposed to provide non-invasive indices of inspiratory muscle activation, but have not been directly compared to gold standard Pdi and oesEMGdi measures during voluntary respiratory manoeuvres. To validate the non-invasive techniques, the relationships between Pdi and sMMGlic, and between oesEMGdi and sEMGlic were measured simultaneously in 12 healthy subjects during an incremental inspiratory threshold loading protocol. Myographic signals were analysed using fixed sample entropy (fSampEn), which is less influenced by cardiac artefacts than conventional root mean square. Strong correlations were observed between: mean Pdi and mean fSampEn |sMMGlic| (left, 0.76; right, 0.81), the time-integrals of the Pdi and fSampEn |sMMGlic| (left, 0.78; right, 0.83), and mean fSampEn oesEMGdi and mean fSampEn sEMGlic (left, 0.84; right, 0.83). These findings suggest that sMMGlic and sEMGlic could provide useful non-invasive alternatives to Pdi and oesEMGdi for the assessment of inspiratory muscle function in health and disease.

Gender- and Muscle-Specific Responses During Fatiguing Exercise

Hill, EC, Housh, TJ, Smith, CM, Schmidt, RJ, and Johnson, GO. Gender- and muscle-specific responses during fatiguing exercise. J Strength Cond Res 32(5): 1471-1478, 2018-The purpose of the present investigation was to examine potential gender-related differences in electromyographic (EMG) and mechanomyographic (MMG) responses during submaximal, concentric, isokinetic, forearm flexion muscle contractions. Twelve men and 12 women performed concentric peak torque trials before (pretest) and after (posttest) a fatiguing exercise bout that consisted of 50 submaximal (65% of concentric peak torque), concentric, isokinetic (60°·s), forearm flexion muscle contractions. Surface EMG and MMG signals were simultaneously recorded from the biceps brachii and brachioradialis muscles. There was a gender-related difference in the decline in absolute concentric peak torque for the men (23.8%) vs. women (18.5%) that was eliminated when covaried for differences in pretest concentric peak torque values. During the fatiguing exercise bout, EMG amplitude(AMP) increased and EMG mean power frequency (MPF) decreased for both genders and muscles. There were, however, muscle- and gender-specific increases, decreases, and no changes for MMG AMP and MMG MPF. The gender-related difference for the posttest decline in concentric peak torque was associated with differences in muscle strength which may have resulted in greater blood flow occlusion in the men than the women. The muscles with the most pronounced fatigue-induced neuromuscular responses were the biceps brachii in men and the brachioradialis in women. These findings may be related to gender differences in the usage patterns of synergistic muscles during a fatiguing task.

A CNN-SVM combined model for pattern recognition of knee motion using mechanomyography signals

The commonly used classifiers for pattern recognition of human motion, like backpropagation neural network (BPNN) and support vector machine (SVM), usually implement the classification by extracting some hand-crafted features from the human biological signals. These features generally require the domain knowledge for researchers to be designed and take a long time to be tested and selected for high classification performance. In contrast, convolutional neural network (CNN), which has been widely applied to computer vision, can learn to automatically extract features from the training data by means of convolution and subsampling, but CNN training usually requires large sample data and has the overfitting problem. On the other hand, SVM has good generalization ability and can solve the small sample problem. Therefore, we proposed a CNN-SVM combined model to make use of their advantages. In this paper, we detected 4-channel mechanomyography (MMG) signals from the thigh muscles and fed them in the form of time series signals to the CNN-SVM combined model for the pattern recognition of knee motion. Compared with the common classifier performing the classification with hand-crafted features, the CNN-SVM combined model could automatically extract features using CNN, and better improved the generalization ability of CNN and the classification accuracy by means of combining the SVM. This study would provide reference for human motion recognition using other time series signals and further expand the application fields of CNN.

Investigation of the Relationship Between Electrical Stimulation Frequency and Muscle Frequency Response Under Submaximal Contractions

Neuromuscular electrical stimulation (NMES) is a common tool that is used in clinical and laboratory experiments and can be combined with mechanomyography (MMG) for biofeedback in neuroprostheses. However, it is not clear if the electrical current applied to neuromuscular tissues influences the MMG signal in submaximal contractions. The objective of this study is to investigate whether the electrical stimulation frequency influences the mechanomyographic frequency response of the rectus femoris muscle during submaximal contractions. Thirteen male participants performed three maximal voluntary isometric contractions (MVIC) recorded in isometric conditions to determine the maximal force of knee extensors. This was followed by the application of nine modulated NMES frequencies (20, 25, 30, 35, 40, 45, 50, 75, and 100 Hz) to evoke 5% MVIC. Muscle behavior was monitored by the analysis of MMG signals, which were decomposed into frequency bands by using a Cauchy wavelet transform. For each applied electrical stimulus frequency, the mean MMG spectral/frequency response was estimated for each axis (X, Y, and Z axes) of the MMG sensor with the values of the frequency bands used as weights (weighted mean). Only with respect to the Z (perpendicular) axis of the MMG signal, the stimulus frequency of 20 Hz did not exhibit any difference with the weighted mean (P = 0.666). For the frequencies of 20 and 25 Hz, the MMG signal displayed the bands between 12 and 16 Hz in the three axes (P < 0.050). In the frequencies from 30 to 100 Hz, the muscle presented a higher concentration of the MMG signal between the 22 and 29 Hz bands for the X and Z axes, and between 16 and 34 Hz bands for the Y axis (P < 0.050 for all cases). We observed that MMG signals are not dependent on the applied NMES frequency, because their frequency contents tend to mainly remain between the 20- and 25-Hz bands. Hence, NMES does not interfere with the use of MMG in neuroprosthesis.

Mechanomyographic responses for the biceps brachii are associated with failure times during isometric force tasks

In order to characterize the physiological adjustments within the neuromuscular system that contribute to task failure, this study examined the surface mechanomyographic (MMG) response during maximal and submaximal isometric force tasks of the elbow flexors sustained to failure. The time and frequency components of the MMG signal have shown to be influenced by motor unit activation patterns as well as tetanus. Therefore, it was hypothesized that the rate of change for the MMG response would associate with failure times and would be reduced to a similar degree between the two tasks. The isometric force tasks were performed by the dominant elbow flexors of twenty healthy males (age: 25 ± 4 years) and MMG was collected from the biceps brachii. Regression analyses were used to model the relationships between the rates of change for MMG versus failure times. There were high levels of interindividual variability in the response patterns, yet the models demonstrated significant negative associations between the rate of change for the MMG responses and failure times during both tasks (R2  = 0.41-0.72, P < 0.05). Similarly, the mean MMG amplitude and frequency values were reduced to comparable levels at the failure point of the two tasks. The results of this study demonstrated that force failure is associated with the rate of diminution in the properties of the muscle force twitch.

Real-time continuous recognition of knee motion using multi-channel mechanomyography signals detected on clothes

Mechanomyography (MMG) signal has been recently investigated for pattern recognition of human motion. In theory, it is no need of direct skin contact to be detected and unaffected by changes in skin impedance. So, it is hopeful for developing wearable sensing device with clothes. However, there have been no studies so far to detect MMG signal on clothes and verify the feasibility of pattern recognition. For this study, 4-channel MMG signals were detected on clothes from the thigh muscles of 8 able-bodied participants. The support vector machines (SVM) classifier with 4 common features was used to recognize 6 knee motions and the average accuracy of nearly 88% was achieved. The accuracy can be further improved up to 91% by introducing a new proposed feature of the difference of mean absolute value (DMAV), but not by root mean square (RMS) or mean absolute value (MAV). Furthermore, the first-order Markov chain model was combined with the SVM classifier and it can avoid the misclassifications in some cases. For application to wearable power-assisted devices, this study would promote the developments of more flexible, more comfortable, and minimally obtrusive wearable sensing devices with clothes and recognition techniques of human motion intention.

Gaussian Process Autoregression for Simultaneous Proportional Multi-Modal Prosthetic Control With Natural Hand Kinematics

Matching the dexterity, versatility, and robustness of the human hand is still an unachieved goal in bionics, robotics, and neural engineering. A major limitation for hand prosthetics lies in the challenges of reliably decoding user intention from muscle signals when controlling complex robotic hands. Most of the commercially available prosthetic hands use muscle-related signals to decode a finite number of predefined motions and some offer proportional control of open/close movements of the whole hand. Here, in contrast, we aim to offer users flexible control of individual joints of their artificial hand. We propose a novel framework for decoding neural information that enables a user to independently control 11 joints of the hand in a continuous manner-much like we control our natural hands. Toward this end, we instructed six able-bodied subjects to perform everyday object manipulation tasks combining both dynamic, free movements (e.g., grasping) and isometric force tasks (e.g., squeezing). We recorded the electromyographic and mechanomyographic activities of five extrinsic muscles of the hand in the forearm, while simultaneously monitoring 11 joints of hand and fingers using a sensorized data glove that tracked the joints of the hand. Instead of learning just a direct mapping from current muscle activity to intended hand movement, we formulated a novel autoregressive approach that combines the context of previous hand movements with instantaneous muscle activity to predict future hand movements. Specifically, we evaluated a linear vector autoregressive moving average model with exogenous inputs and a novel Gaussian process ( ) autoregressive framework to learn the continuous mapping from hand joint dynamics and muscle activity to decode intended hand movement. Our approach achieves high levels of performance (RMSE of 8°/s and ). Crucially, we use a small set of sensors that allows us to control a larger set of independently actuated degrees of freedom of a hand. This novel undersensored control is enabled through the combination of nonlinear autoregressive continuous mapping between muscle activity and joint angles. The system evaluates the muscle signals in the context of previous natural hand movements. This enables us to resolve ambiguities in situations, where muscle signals alone cannot determine the correct action as we evaluate the muscle signals in their context of natural hand movements. autoregression is a particularly powerful approach which makes not only a prediction based on the context but also represents the associated uncertainty of its predictions, thus enabling the novel notion of risk-based control in neuroprosthetics. Our results suggest that autoregressive approaches with exogenous inputs lend themselves for natural, intuitive, and continuous control in neurotechnology, with the particular focus on prosthetic restoration of natural limb function, where high dexterity is required for complex movements.

Unilateral fatiguing exercise and its effect on ipsilateral and contralateral resting mechanomyographic mean frequency between aerobic populations

The purpose of this investigation was to establish a better understanding of contralateral training and its effects between homologous muscles following unilateral fatiguing aerobic exercise during variable resting postural positions, and to determine if any observable disparities could be attributed to the differences between the training ages of the participants. Furthermore, we hypothesized that we would observe a contralateral cross-over effect for both groups, with the novice trained group having the higher mechanomyographic mean frequency values in both limbs, across all resting postural positions. Twenty healthy male subjects exercised on an upright cycle ergometer, using only their dominate limb, for 30 min at 60% of their VO2 peak. Resting electromyographic and mechanomyographic signals were measured prior to and following fatiguing aerobic exercise. We found that there were resting mechanomyographic mean frequency differences of approximately 1.9 ± 0.8% and 0.9 ± 0.7%; 9.1 ± 0.3% and 10.2 ± 3.7%; 2 ± 1.8% and 3 ± 1.4%; and 0.9 ± 0.6% and 0.2 ± 1.3% between the novice and advanced trained groups (for the upright sitting position with legs extended 180°; upright sitting position with legs bent 90°; lying supine position with legs extended 180°; and lying supine with legs bent 90°, respectively), from the dominant and nondominant limbs, respectively. We have concluded that despite the relative matching of exercise intensity between groups, acute responses to contralateral training become less accentuated as one progresses in training age. Additionally, our results lend support to the notion that there are multiple, overlapping neural and mechanical mechanisms concurrently contributing to the contralateral cross-over effects observed across the postexercise resting time course.

Combining regression and mean comparisons to identify the time course of changes in neuromuscular responses during the process of fatigue

The purposes of the present study were to apply a unique method for the identification of the time course of changes in neuromuscular responses and to infer the motor unit activation strategies used to maintain force during a fatiguing, intermittent isometric workbout. Eleven men performed 50, 6 s intermittent isometric muscle actions of the leg extensors, each separated by 2 s of rest at 60% maximal voluntary isometric contraction (MVIC). Electromyographic (EMG) and mechanomyographic (MMG) amplitude (root mean square; RMS) and frequency (mean power frequency; MPF) were obtained from the vastus lateralis (VL) every 5 of the 50 repetitions and normalized as a percent of the initial repetition. Polynomial regression analyses were used to determine the model of best fit for the normalized EMG RMS, EMG MPF, MMG RMS, and MMG MPF versus repetition relationships and one-way repeated measures ANOVAs with post-hoc Student Newman-Keuls were used to identify when these neuromuscular parameters changed from the initial repetition. The findings of the present study indicated two unique phases of neuromuscular responses (repetitions 1-20 and 20-50) during the fatiguing workbout. The time course of changes in these four neuromuscular responses suggested that the after-hyperpolarization theory could not explain the maintenance of force production, but Muscle Wisdom and the Onion Skin Scheme could. The findings of the current study suggested that the time course of changes in neuromuscular responses can provide insight in to the motor unit activation strategies used to maintain force production and allow for a greater understanding of the fatiguing process by identifying the time-points at which these neuromuscular parameters changed.

Time Course of Changes in Neuromuscular Parameters During Sustained Isometric Muscle Actions

Smith, CM, Housh, TJ, Herda, TJ, Zuniga, JM, Camic, CL, Bergstrom, HC, Smith, DB, Weir, JP, Hill, EC, Cochrane, KC, Jenkins, NDM, Schmidt, RJ, and Johnson, GO. Time course of changes in neuromuscular parameters during sustained isometric muscle actions. J Strength Cond Res 30(10): 2697-2702, 2016-The objective of the present study was to identify the time course of changes in electromyographic (EMG) and mechanomyographic (MMG) time and frequency domain parameters during a sustained isometric muscle action of the leg extensors at 50% maximal voluntary isometric contraction. The EMG and MMG signals were measured from the vastus lateralis of 11 subjects to identify when motor unit activation strategies changed throughout the sustained isometric muscle action. The EMG amplitude (muscle activation) had a positive linear relationship (p = 0.018, r = 0.77) that began to increase at the initiation of the muscle action and continued until task failure. Electromyographic frequency (motor unit action potential conduction velocity) and MMG frequency (global motor unit firing rate) had negative quadratic relationships (p = 0.002, R = 0.99; p = 0.015, R = 0.94) that began to decrease at 30% of the time to exhaustion. The MMG amplitude (motor unit activation) had a cubic relationship (p = 0.001, R = 0.94) that increased from 10 to 30% of the time to exhaustion, then decreased from 40 to 70% of the time to exhaustion, and then markedly increased from 70% to task failure. The time course of changes in the neuromuscular parameters suggested that motor unit activation strategies changed at approximately 30 and 70% of the time to exhaustion during the sustained isometric muscle action. These findings indicate that the time course of changes in neuromuscular responses provide insight into the strategies used to delay the effects of fatigue and are valuable tools for quantifying changes in the fatiguing process during training programs or supplementation research.

Inter-individual variability in the patterns of responses for electromyography and mechanomyography during cycle ergometry using an RPE-clamp model

PURPOSE

To examine inter-individual variability versus composite models for the patterns of responses for electromyography (EMG) and mechanomyography (MMG) versus time relationships during moderate and heavy cycle ergometry using a rating of perceived exertion (RPE) clamp model.

METHODS

EMG amplitude (amplitude root-mean-square, RMS), EMG mean power frequency (MPF), MMG-RMS, and MMG-MPF were collected during two, 60-min rides at a moderate (RPE at the gas exchange threshold; RPEGET) and heavy (RPE at 15 % above the GET; RPEGET+15 %) intensity when RPE was held constant (clamped). Composite (mean) and individual responses for EMG and MMG parameters were compared during each 60-min ride.

RESULTS

There was great inter-individual variability for each EMG and MMG parameters at RPEGET and RPEGET+15 %. Composite models showed decreases in EMG-RMS (r (2) = -0.92 and R (2) = 0.96), increases in EMG-MPF (R (2) = 0.90), increases in MMG-RMS (r (2) = 0.81 and 0.55), and either no change or a decrease (r (2) = 0.34) in MMG-MPF at RPEGET and RPEGET+15 %, respectively.

CONCLUSIONS

The results of the present study indicated that there were differences between composite and individual patterns of responses for EMG and MMG parameters during moderate and heavy cycle ergometry at a constant RPE. Thus, composite models did not represent the unique muscle activation strategies exhibited by individual responses when cycling in the moderate and heavy intensity domains when using an RPE-clamp model.

Examination of a neural cross-over effect using resting mechanomyographic mean frequency from the vastus lateralis muscle in different resting positions following aerobic exercise

PURPOSE

To evaluate the potential neural cross-over effect between the vastus lateralis muscles in different postural resting positions.

METHODS

Subjects exercised on an upright cycle ergometer, using only their dominate leg, for 2 min at 30 % VO2 peak. Following this warm-up, subjects then cycled (still using only their dominant leg) for 30 min at 60 % VO2 peak. After the aerobic phase, subjects cooled down (again, using only their dominant leg) for 2 min at 30 % VO2 peak. Resting mechanomyography mean frequency was measured prior to and following aerobic exercise.

RESULTS

There was an approximate 6.3 ± 6.8 and a 10 ± 5.1 % increase (upright sitting position with the subject's knee joint angle fixed at 180°); an approximate 7 ± 6.6 and a 16.1 ± 6.5 % increase (upright sitting position with the subject's knee joint angle fixed at 90°); an approximate 0.5 ± 6.8 and 3.7 ± 5.6 % increase (lying supine position with the subject's knee joint angle fixed at 180°); and an approximately 2 ± 8.3 and 2.5 ± 8.6 % increase (lying supine position with the subject's knee joint angle fixed at 90°) in normalized mechanomyography mean frequency after aerobic exercise for the dominant and non-dominate vastus lateralis muscles, respectfully.

CONCLUSION

There appears to be a statistically significant neural cross-over effect for the vastus lateralis muscle, during three of the four postural resting positions, with the non-dominant vastus lateralis muscle having a greater increase in mechanomyography mean frequency.

Electromyographic, mechanomyographic, and metabolic responses during cycle ergometry at a constant rating of perceived exertion

Ten subjects performed four 8-min rides (65%-80% peak oxygen consumption) to determine the physical working capacity at the OMNI rating of perceived exertion (RPE) threshold (PWCOMNI). Polynomial regression analyses were used to examine the patterns of responses for surface electromyographic (EMG) amplitude (EMG AMP), EMG mean power frequency (EMG MPF), mechanomyographic (MMG) AMP, and MMG MPF of the vastus lateralis as well as oxygen consumption rate, respiratory exchange ratio (RER), and power output (PO) were examined during a 1-h ride on a cycle ergometer at a constant RPE that corresponded to the PWCOMNI. EMG AMP and MMG MPF tracked the decreases in oxygen consumption rate, RER, and PO, while EMG MPF and MMG AMP tracked RPE. The decreases in EMG AMP and MMG MPF were likely attributable to decreases in motor unit (MU) recruitment and firing rate, while the lack of change in MMG AMP may have resulted from a balance between MU de-recruitment as PO decreased, and an increase in the ability of activated fibers to oscillate. The current findings suggested that during submaximal cycle ergometry at a constant RPE, MU de-recruitment and mechanical changes within the muscle may influence the perception of effort via feedback from group III and IV afferents.

Mechanomyographic mean power frequency during an isometric trapezoid muscle action at multiple contraction intensities

This study examined the mechanomyographic mean power frequency (MMGMPF)-force relationships for five (age = 19.20   ±   0.45 years) aerobically-trained (AT), five (age = 25   ±   4.53 years) resistance-trained (RT), and five (age = 21.20   ±   2.17 years) sedentary (SED) individuals. Participants performed isometric trapezoidal muscle actions at 50, 60, and 70% maximal voluntary contraction (MVC) of the leg extensors that included linearly increasing, steady force, and linearly decreasing segments. MMG was recorded from the vastus lateralis. Linear regressions were fit to the natural-log transformed MMGMPF versus natural log-transformed force relationships (linearly increasing and decreasing segments) with the b (slope) and a (y-intercept) terms used for comparisons. MMGMPF was averaged for the entire steady force segment. The b and a terms were not different among training statuses (P  >  0.05) or linearly increasing and decreasing segments (P  >  0.05). There were muscle action-related differences in the b terms as a function of training status from the 70% MVC. The SED had greater b terms during the linearly increasing than decreasing muscle action (P = 0.010), and the converse was true for the AT (P = 0.013), whereas the RT displayed no muscle action-related differences (P  >  0.05). The unique muscle action-related differences in the b terms as a function of training status may be the result of unique adaptations to motor unit activation and deactivation strategies.

Motor unit activation strategy during a sustained isometric contraction of finger flexor muscles in elite climbers

The aim of the study was to evaluate, by an electromyographic (EMG) and mechanomyographic (MMG) combined approach, whether years of specific climbing activity induced neuromuscular changes towards performances related to a functional prevalence of fast resistant or fast fatigable motor units. For this purpose, after the maximum voluntary contraction (MVC) assessment, 11 elite climbers and 10 controls performed an exhaustive handgrip isometric effort at 80% MVC. Force, EMG and MMG signals were recorded from the finger flexor muscles during contraction. Time and frequency domain analysis of EMG and MMG signals was performed. In climbers: (i) MVC was higher (762 ± 34 vs 512 ± 57 N; effect size: 1.64; confidence interval: 0.65-2.63; P < 0.05); (ii) endurance time at 80% MVC was 43% longer (34.2 ± 3.7 vs 22.3 ± 1.5 s; effect size: 1.21; confidence interval: 0.28-2.14; P < 0.05); (iii) force accuracy and stability were greater during contraction (P < 0.05); (iv) EMG and MMG parameters were higher throughout the entire isometric effort (P < 0.05). Collectively, force, EMG and MMG combined analysis revealed that several years of specific climbing activity addressed the motor control system to adopt muscle activation strategies based on the functional prevalence of fast resistant motor units.

Mechanomyographic parameter extraction methods: an appraisal for clinical applications

The research conducted in the last three decades has collectively demonstrated that the skeletal muscle performance can be alternatively assessed by mechanomyographic signal (MMG) parameters. Indices of muscle performance, not limited to force, power, work, endurance and the related physiological processes underlying muscle activities during contraction have been evaluated in the light of the signal features. As a non-stationary signal that reflects several distinctive patterns of muscle actions, the illustrations obtained from the literature support the reliability of MMG in the analysis of muscles under voluntary and stimulus evoked contractions. An appraisal of the standard practice including the measurement theories of the methods used to extract parameters of the signal is vital to the application of the signal during experimental and clinical practices, especially in areas where electromyograms are contraindicated or have limited application. As we highlight the underpinning technical guidelines and domains where each method is well-suited, the limitations of the methods are also presented to position the state of the art in MMG parameters extraction, thus providing the theoretical framework for improvement on the current practices to widen the opportunity for new insights and discoveries. Since the signal modality has not been widely deployed due partly to the limited information extractable from the signals when compared with other classical techniques used to assess muscle performance, this survey is particularly relevant to the projected future of MMG applications in the realm of musculoskeletal assessments and in the real time detection of muscle activity.

Mouse activity across time scales: fractal scenarios

In this work we devise a classification of mouse activity patterns based on accelerometer data using Detrended Fluctuation Analysis. We use two characteristic mouse behavioural states as benchmarks in this study: waking in free activity and slow-wave sleep (SWS). In both situations we find roughly the same pattern: for short time intervals we observe high correlation in activity - a typical 1/f complex pattern - while for large time intervals there is anti-correlation. High correlation of short intervals ( to : waking state and to : SWS) is related to highly coordinated muscle activity. In the waking state we associate high correlation both to muscle activity and to mouse stereotyped movements (grooming, waking, etc.). On the other side, the observed anti-correlation over large time scales ( to : waking state and to : SWS) during SWS appears related to a feedback autonomic response. The transition from correlated regime at short scales to an anti-correlated regime at large scales during SWS is given by the respiratory cycle interval, while during the waking state this transition occurs at the time scale corresponding to the duration of the stereotyped mouse movements. Furthermore, we find that the waking state is characterized by longer time scales than SWS and by a softer transition from correlation to anti-correlation. Moreover, this soft transition in the waking state encompass a behavioural time scale window that gives rise to a multifractal pattern. We believe that the observed multifractality in mouse activity is formed by the integration of several stereotyped movements each one with a characteristic time correlation. Finally, we compare scaling properties of body acceleration fluctuation time series during sleep and wake periods for healthy mice. Interestingly, differences between sleep and wake in the scaling exponents are comparable to previous works regarding human heartbeat. Complementarily, the nature of these sleep-wake dynamics could lead to a better understanding of neuroautonomic regulation mechanisms.

Cross-talk in mechanomyographic signals from the forearm muscles during sub-maximal to maximal isometric grip force

PURPOSE

This study aimed: i) to examine the relationship between the magnitude of cross-talk in mechanomyographic (MMG) signals generated by the extensor digitorum (ED), extensor carpi ulnaris (ECU), and flexor carpi ulnaris (FCU) muscles with the sub-maximal to maximal isometric grip force, and with the anthropometric parameters of the forearm, and ii) to quantify the distribution of the cross-talk in the MMG signal to determine if it appears due to the signal component of intramuscular pressure waves produced by the muscle fibers geometrical changes or due to the limb tremor.

METHODS

Twenty, right-handed healthy men (mean ± SD: age  = 26.7±3.83 y; height  = 174.47±6.3 cm; mass  = 72.79±14.36 kg) performed isometric muscle actions in 20% increment from 20% to 100% of the maximum voluntary isometric contraction (MVIC). During each muscle action, MMG signals generated by each muscle were detected using three separate accelerometers. The peak cross-correlations were used to quantify the cross-talk between two muscles.

RESULTS

The magnitude of cross-talk in the MMG signals among the muscle groups ranged from, R2(x, y) = 2.45-62.28%. Linear regression analysis showed that the magnitude of cross-talk increased linearly (r2 = 0.857-0.90) with the levels of grip force for all the muscle groups. The amount of cross-talk showed weak positive and negative correlations (r2 = 0.016-0.216) with the circumference and length of the forearm respectively, between the muscles at 100% MVIC. The cross-talk values significantly differed among the MMG signals due to: limb tremor (MMGTF), slow firing motor unit fibers (MMGSF) and fast firing motor unit fibers (MMGFF) between the muscles at 100% MVIC (p<0.05, η2 = 0.47-0.80).

SIGNIFICANCE

The results of this study may be used to improve our understanding of the mechanics of the forearm muscles during different levels of the grip force.

Torque and mechanomyogram correlations during muscle relaxation: effects of fatigue and time-course of recovery

To assess the validity and reliability of the mechanomyogram (MMG) as a tool to investigate the fatigue-induced changes in the muscle during relaxation, the torque and MMG signals from the gastrocnemius medialis muscle of 23 participants were recorded during tetanic electrically-elicited contractions before and immediately after fatigue, as well as at min 2 and 7 of recovery. The peak torque (pT), contraction time (CT) and relaxation time (RT), and the acceleration of force development (d2RFD) and relaxation (d2RFR) were calculated. The slope and τ of force relaxation were also determined. MMG peak-to-peak was assessed during contraction (MMG p-p) and relaxation (R-MMG p-p). After fatigue, pT, d2RFD, d2RFR, slope, MMG p-p and R-MMG p-p decreased significantly, while CT, RT and τ increased (P < 0.05 for all comparisons), remaining altered throughout the entire recovery period. R-MMG p-p correlated with pT, MMG p-p, slope, τ and d2RFR both before and after fatigue. Reliability measurements always ranged from high to very high. In conclusion, MMG may represent a valid and reliable index to monitor the fatigue-induced changes in muscle mechanical behavior, and could be therefore considered an effective alternative to the force signal, also during relaxation.

Mechanomyographic responses for the biceps brachii are unable to track the declines in peak torque during 25, 50, 75, and 100 fatiguing isokinetic muscle actions

This study examined the peak torque and mechanomyographic (MMG) amplitude and mean frequency (MNF) responses during fatiguing isokinetic muscle actions. On four separate occasions, twenty men (mean ± SD age = 23 ± 3 years) performed 25, 50, 75, and 100 repeated maximal concentric isokinetic muscle actions of the dominant forearm flexors. During each muscle action, the MMG signal was detected from the biceps brachii with an accelerometer. The data were examined with linear regression and one-way repeated measures analyses of variance. The results indicated that the mean percent decline in peak torque value for the 25 repetition trial (25.6%) was significantly less than that for the 50 repetition trial (45.2%). Furthermore, the mean linear slope coefficient for the peak torque versus repetition number relationship for the 50 repetition trial was significantly less than that for the 100 repetition trial. There were no mean differences among the trials for the linear slope coefficients and y-intercepts for the MMG amplitude and MNF versus repetition number relationships. When detected with an accelerometer, the linear slope coefficients and y-intercepts for the MMG amplitude and MNF versus repetition number relationships were not sensitive enough to track the decline in muscle function during fatigue.