Mechanomyographic amplitude and mean power frequency versus torque relationships during isokinetic and isometric muscle actions of the biceps brachii

Comparison of Force, Neuromuscular, and Metabolic Responses During Sustained, Isometric Handgrip Holds to Failure Anchored to Low and High Perceptual Intensities in Men: An Exploratory Study

ABSTRACT

Kwak, M, Succi, PJ, Benitez, B, Mitchinson, C, Samaan, MA, Abel, MG, and Bergstrom, HC. Comparison of force, neuromuscular, and metabolic responses during sustained, isometric handgrip holds to failure anchored to low and high perceptual intensities in men: An exploratory study. J Strength Cond Res 38(8): e405-e416, 2024-This study examined the responses of force alterations, relative to critical force (CF), neuromuscular parameters, and muscle oxygenation (SmO2) for isometric handgrip holds to failure (HTF) anchored to ratings of perceived exertion (RPE) of 3 and 7. Twelve men completed pre-maximal voluntary isometric contractions (pre-MVIC), submaximal HTF at 4 percentages of pre-MVIC, HTF at RPE = 3 and 7, and post-MVIC. Mechanomyograpic (MMG) signals and SmO2 were recorded during the RPE HTF. Analyses included paired-samples t-tests and repeated-measures ANOVAs at an alpha level of p ≤ 0.05. Time to task failure was not different between RPE 3 (478.7 ± 196.6 s) and RPE 7 (495.8 ± 173.8 s). Performance fatigability (PF) and MMG amplitude (AMP) were greater for RPE 7 (PF: 37.9 ± 12.9%; MMG AMP: 15.7 ± 7.4% MVIC) than RPE 3 (PF: 30.0 ± 14.5%; MMG AMP: 10.2 ± 6.5% MVIC), but MMG mean power frequency (MPF) was greater for RPE 3 (146.2 ± 31.1% MVIC) than RPE 7 (128.8 ± 23.0% MVIC). There were RPE-dependent decreases in force (p ≤ 0.01) across 3 discernable phases during the HTF. There were decreases in MMG AMP across time for both RPEs, but there were no significant changes in MMG MPF or SmO2. There were overall similar motor unit control strategies and local metabolic demand between RPEs. The majority of the HTF performed below CF at RPE 3 and 7 indicated CF did not reflect the highest sustainable force. When prescribing isometric exercise anchored to RPE, practitioners should be aware of the magnitude of force loss and relative intensity of the task to be sure desired training loads are met.

High-Intensity Cycling Training Necessitates Increased Neuromuscular Demand of the Vastus Lateralis During a Fatiguing Contraction

Purpose: To examine the effects of a 5-week continuous cycling training intervention on electromyographic amplitude (EMGRMS)- and mechanomyographic amplitude (MMGRMS)-torque relationships of the vastus lateralis (VL) during a prolonged contraction. Methods: Twenty-four sedentary, young adults performed maximal voluntary contractions (MVCs) and a prolonged isometric trapezoidal contraction at the same absolute 40% MVC for the knee extensors before (PRE) and after training (POSTABS). Individual b- (slopes) and a-terms (y-intercepts) were calculated from the log-transformed electromyographic amplitude (EMGRMS)- and mechanomyographic amplitude (MMGRMS)-torque relationships during the increasing and decreasing segments of the trapezoid. EMGRMS and MMGRMS was normalized for the 45-s steady torque segment. Results: At PRE, b-terms for the EMGRMS-torque relationships during the linearly decreasing segment were greater than the increasing segment (p < .001), and decreased from PRE to POSTABS (p = .027). a-terms were greater during the linearly increasing than decreasing segment at PRE, while the a-terms for the linearly decreasing segment increased from PRE to POSTABS (p = .027). For the MMGRMS-torque relationships, b-terms during the linearly decreasing segment decreased from PRE to POSTABS (p = .013), while a-terms increased from PRE to POSTABS when collapsed across segments (p = .022). Steady torque EMGRMS increased for POSTABS (p < .001). Conclusion: Although cycling training increased aerobic endurance, incorporating resistance training may benefit athletes/individuals as the alterations in neuromuscular parameters post-training suggest a greater neural cost (EMGRMS) and mechanical output (MMGRMS) to complete the same pre-training fatiguing contraction.

Are performance and perceived fatigability dependent on the anchor scheme of fatiguing isometric tasks in men?

BACKGROUND

Ratings of perceived exertion (RPE) can be used to regulate exercise intensity. This study examined the effect of anchor scheme on performance fatigability and neuromuscular responses following fatiguing forearm flexion tasks.

METHODS

Twelve men (age 20.9±2.2 years; height 179.8±5.3 cm; body mass 80.2±9.9 kg) performed sustained, isometric forearm flexion tasks to failure anchored to RPE=6 (RPEFT) and the torque (TRQFT) that corresponded to RPE=6. Pre-test and post-test maximal voluntary isometric contractions (MVIC) were performed to quantify changes in the amplitude (AMP) and mean power frequency (MPF) of the electromyographic (EMG) and mechanomyographic (MMG) signals. Neuromuscular efficiency (NME) was calculated by dividing normalized torque by normalized EMG AMP. A dependent t-test was used to assess the mean difference for time to task failure (TTF). Repeated measures ANOVAs were used to compare mean differences for performance fatigability and normalized neuromuscular parameters.

RESULTS

The RPEFT had a greater TTF than the TRQFT (P<0.001). MVIC and NME decreased from pre-test to post-test following the RPEFT and TRQFT (P<0.05) with no differences between anchor schemes. Following the TRQFT, normalized EMG MPF decreased from pre-test to post-test (P=0.004). Following the RPEFT, normalized MMG MPF increased from pre-test to post-test (P=0.021). There were no changes in normalized EMG AMP or MMG AMP (P>0.05).

CONCLUSIONS

These findings indicated anchor scheme-specific neuromuscular responses and TTF, despite no difference in performance fatigability. Furthermore, performance fatigability was likely due to peripheral fatigue (based on normalized EMG MPF and NME) following the TRQFT, but peripheral and central fatigue (based on normalized MMG MPF and NME) following the RPEFT.

Blood flow restriction attenuates surface mechanomyography lateral and longitudinal, but not transverse oscillations during fatiguing exercise

Objective. Surface mechanomyography (sMMG) can measure oscillations of the activated muscle fibers in three axes (i.e.X,Y, andZ-axes) and has been used to describe motor unit activation patterns (X-axis). The application of blood flow restriction (BFR) is common in exercise studies, but the cuff may restrict muscle fiber oscillations. Therefore, the purpose of this investigation was to examine the acute effects of submaximal, fatiguing exercise with and without BFR on sMMG amplitude in theX,Y, andZ-axes among female participants.Approach. Sixteen females (21 ± 1 years) performed two separate exercise bouts to volitional exhaustion that consisted of unilateral, submaximal (50% maximal voluntary isometric contraction [MVIC]) intermittent, isometric, leg extensions with and without BFR. sMMG was recorded and examined across percent time to exhaustion (%TTE) in 20% increments. Separate 2-way repeated measures ANOVA models were constructed: (condition [BFR, non-BFR]) × (time [20, 40, 60, 80, and 100% TTE]) to examine absolute (m·s-2) and normalized (% of pretest MVIC) sMMG amplitude in theX-(sMMG-X),Y-(sMMG-Y), andZ-(sMMG-Z) axes.Main results. The absolute sMMG-X amplitude responses were attenuated with the application of BFR (mean ± SD = 0.236 ± 0.138 m·s-2) relative to non-BFR (0.366 ± 0.199 m·s-2, collapsed across time) and for sMMG-Y amplitude at 60%-100% of TTE (BFR range = 0.213-0.232 m·s-2versus non-BFR = 0.313-0.445 m·s-2). Normalizing sMMG to pretest MVIC removed most, but not all the attenuation which was still evident for sMMG-Y amplitude at 100% of TTE between BFR (72.9 ± 47.2%) and non-BFR (98.9 ± 53.1%). Interestingly, sMMG-Z amplitude was not affected by the application of BFR and progressively decreased across %TTE (0.332 ± 0.167 m·s-2to 0.219 ± 0.104 m·s-2, collapsed across condition.)Significance. The application of BFR attenuated sMMG-X and sMMG-Y amplitude, although normalizing sMMG removed most of this attenuation. Unlike theXandY-axes, sMMG-Z amplitude was not affected by BFR and progressively decreased across each exercise bout potentially tracking the development of muscle fatigue.

Effects of a Sustained, Isometric Forearm Flexion Task to Failure on Torque and Neuromuscular Responses at 3 Elbow Joint Angles

ABSTRACT

Ortega, DG, Housh, TJ, Smith, RW, Arnett, JE, Neltner, TJ, Anders, JPV, Schmidt, RJ, and Johnson, GO. The effects of a sustained, isometric forearm flexion task to failure on torque and neuromuscular responses at 3 elbow joint angles. J Strength Cond Res 38(1): e25-e33, 2024-This study examined the effects of a sustained, isometric forearm flexion task anchored to torque to task failure on maximal voluntary isometric contraction (MVIC) and neuromuscular responses at 3 elbow joint angles. Eleven women (mean ± SD: age = 20.8 ± 2.7 years, height = 169.3 ± 7.4 cm, body mass = 67.7 ± 6.9 kg) performed two 3s forearm flexion MVICs at elbow joint angles (JAs) of 75°, 100°, and 125° before and after a sustained, isometric forearm flexion task to failure at a fatiguing joint angle of 100° anchored to a torque value that corresponded to a rating of perceived exertion of 8 (RPE = 8). The amplitude (AMP) and mean power frequency (MPF) of the electromyographic (EMG) and mechanomyographic (MMG) signals were recorded from the biceps brachii. Repeated-measures ANOVAs were used to compare mean differences for MVIC and neuromuscular parameters. Collapsed across JAs, MVIC (p < 0.001) and EMG MPF (p = 0.006) pretest values were greater than posttest values. Collapsed across time, EMG MPF at JA75 was greater than JA100 (p < 0.001) and JA125 (p < 0.001), and JA100 was greater (p = 0.007) than JA125. For EMG AMP, there was a fatigue-induced decrease at JA75 (p = 0.003). For neuromuscular efficiency (NME = normalized torque/normalized EMG AMP), there were decreases from pretest to posttest at JA100 (p = 0.002) and JA125 (p = 0.008). There were no significant interactions or main effects for MMG AMP and MMG MPF. From these findings, it was hypothesized that the decline in MVICs at JA75, JA100, and JA125 was due to fatigue-induced metabolic perturbations that resulted in JA-specific neuromuscular responses. Thus, neuromuscular parameters may provide insight into the JA-specific mechanisms of fatigue.

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.

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.

Fatiguing Joint Angle Does Not Influence Torque and Neuromuscular Responses Following Sustained, Isometric Forearm Flexion Tasks Anchored to Perceptual Intensity in Men

This study examined the effects of joint angle (JA) on maximal voluntary isometric contraction (MVIC) and neuromuscular responses following fatiguing tasks anchored to RPE. Nine men (mean ± SD: age = 20.7 ± 1.2 yrs) performed forearm flexion MVICs at elbow JAs of 75° and 125° before and after sustained, isometric forearm flexion tasks to failure at fatiguing joint angles (FJA) of 75° and 125° anchored to RPE = 8. The amplitude and frequency of the electromyographic and mechanomyographic signals were recorded. Neuromuscular efficiency was calculated by dividing normalized torque by normalized electromyographic amplitude. A dependent t-test was used to assess the mean difference for time to task failure (TTF) between FJA. Repeated measure ANOVAs were used to assess mean differences for pre-test to post-test MVIC and neuromuscular responses. There was no significant difference between FJA for TTF (p = 0.223). The MVIC (collapsed across FJA and MVIC JA) decreased from pre-test to post-test (51.1 ± 5.0 vs. 45.3 ± 5.6 Nm, p < 0.001). Normalized neuromuscular parameters remained unchanged (p > 0.05). The FJA resulted in similar torque and neuromuscular responses, and the decreases in MVIC were not tracked by changes in the neuromuscular parameters. Thus, the neuromuscular parameters were not sensitive to fatigue, and pre-test to post-test measures may be compared between different FJA.

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.

A Wireless Multi-Layered EMG/MMG/NIRS Sensor for Muscular Activity Evaluation

A wireless multi-layered sensor that allows electromyography (EMG), mechanomyography (MMG) and near-infrared spectroscopy (NIRS) measurements to be carried out simultaneously is presented. The multi-layered sensor comprises a thin silver electrode, transparent piezo-film and photosensor. EMG and MMG measurements are performed using the electrode and piezo-film, respectively. NIRS measurements are performed using the photosensor. Muscular activity is then analyzed in detail using the three types of data obtained. In experiments, the EMG, MMG and NIRS signals were measured for isometric ramp contraction at the forearm and cycling exercise of the lateral vastus muscle with stepped increments of the load using the layered sensor. The results showed that it was possible to perform simultaneous EMG, MMG and NIRS measurements at a local position using the proposed sensor. It is suggested that the proposed sensor has the potential to evaluate muscular activity during exercise, although the detection of the anaerobic threshold has not been clearly addressed.

A non-volitional skeletal muscle endurance test measures functional changes associated with impaired blood flow

Introduction: An electrically stimulated intermittent fatigue test using mechanomyography was recently proposed as a possible tool for detecting clinically relevant changes in muscle function. This study was designed to determine whether the proposed test can detect additional fatigue when it should be present. Methods: Subjects (n = 10) underwent two trials each (occluded and normal blood flow) with a standardized fatigue protocol on the Ankle Dorsiflexors (AD) and Wrist Extensors (WE) using a clinical electrical stimulator. Results: Mean normalized twitch acceleration was strongly predictive of mean normalized torque (R ² = 0.828). The WE experienced lower twitch magnitudes throughout the tourniquet trial (10.81 ± 1.25 m/s²) compared to normal blood flow (18.05 ± 1.06 m/s²). The AD twitches were overall reduced in the tourniquet trial (3.87 ± 0.48 m/s²) compared with the control trial (8.57 ± 0.91 m/s²). Conclusion: Occluding blood flow to a muscle should cause greater muscle fatigue. The ability to detect reduced contraction magnitudes during an electrically stimulated fatigue protocol resulting from low blood flow suggests the proposed test may be capable of detecting clinically relevant muscle deficits.

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.

A comparison of contributions of individual muscle and combination muscles to interaction force prediction using KPCA-DRSN model

Rapid and accurate prediction of interaction force is an effective way to enhance the compliant control performance. However, whether individual muscles or a combination of muscles is more suitable for interaction force prediction under different contraction tasks is of great importance in the compliant control of the wearable assisted robot. In this article, a novel algorithm that is based on sEMG and KPCA-DRSN is proposed to explore the relationship between interaction force prediction and sEMG signals. Furthermore, the contribution of each muscle to the interaction force is assessed based on the predicted results. First of all, the experimental platform for obtaining the sEMG is described. Then, the raw sEMG signal of different muscles is collected from the upper arm during different contractions. Meanwhile, the output force is collected by the force sensor. The Kernel Principal Component Analysis (KPCA) method is adopted to remove the invalid components of the raw sEMG signal. After that, the processed sequence is fed into the Deep Residual Shrinkage Network (DRSN) to predict the interaction force. Finally, based on the prediction results, the contribution of each sEMG signal from different muscles to the interaction force is evaluated by the mean impact value (MIV) indicator. The experimental results demonstrate that our methods can automatically extract the valid features of sEMG signal and provided fast and efficient prediction. In addition, the single muscle with the largest MIV index could predict the interaction force faster and more accurately than the muscle combination in different contraction tasks. The finding of our research provides a solid evidence base for the compliant control of the wearable robot.

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.

Noninvasive Assessment of Neuromechanical and Neuroventilatory Coupling in COPD

This study explored the use of parasternal second intercostal space and lower intercostal space surface electromyogram (sEMG) and surface mechanomyogram (sMMG) recordings (sEMGpara and sMMGpara, and sEMGlic and sMMGlic, respectively) to assess neural respiratory drive (NRD), neuromechanical (NMC) and neuroventilatory (NVC) coupling, and mechanical efficiency (MEff) noninvasively in healthy subjects and chronic obstructive pulmonary disease (COPD) patients. sEMGpara, sMMGpara, sEMGlic, sMMGlic, mouth pressure (Pmo), and volume (Vi) were measured at rest, and during an inspiratory loading protocol, in 16 COPD patients (8 moderate and 8 severe) and 9 healthy subjects. Myographic signals were analyzed using fixed sample entropy and normalized to their largest values (fSEsEMGpara%max, fSEsMMGpara%max, fSEsEMGlic%max, and fSEsMMGlic%max). fSEsMMGpara%max, fSEsEMGpara%max, and fSEsEMGlic%max were significantly higher in COPD than in healthy participants at rest. Parasternal intercostal muscle NMC was significantly higher in healthy than in COPD participants at rest, but not during threshold loading. Pmo-derived NMC and MEff ratios were lower in severe patients than in mild patients or healthy subjects during threshold loading, but differences were not consistently significant. During resting breathing and threshold loading, Vi-derived NVC and MEff ratios were significantly lower in severe patients than in mild patients or healthy subjects. sMMG is a potential noninvasive alternative to sEMG for assessing NRD in COPD. The ratios of Pmo and Vi to sMMG and sEMG measurements provide wholly noninvasive NMC, NVC, and MEff indices that are sensitive to impaired respiratory mechanics in COPD and are therefore of potential value to assess disease severity in clinical practice.

A long short-term memory neural network model for knee joint acceleration estimation using mechanomyography signals

With the growth of the number of elderly and disabled with motor dysfunction, the demand for assisted exercise is increasing. Wearable power assistance robots are developed to provide athletic ability of limbs for the elderly or the disabled who have weakened limbs to better self-care ability. Existing wearable power-assisted robots generally use surface electromyography (sEMG) to obtain effective human motion intentions. Due to the characteristics of sEMG signals, it is limited in many applications. To solve the above problems, we design a long short-term memory (LSTM) neural network model based on human mechanomyography (MMG) signals to estimate the motion acceleration of knee joint. The acceleration can be further calculated by the torque required for movement control of the wearable power assistance robots for the lower limb. We detect MMG signals on the clothed thigh, extract features of the MMG signals, and then, use principal component analysis to reduce the features’ dimensions. Finally, the dimension-reduced features are inputted into the LSTM neural network model in time series for estimating the acceleration. The experimental results show that the average correlation coefficient ( R) is 94.48 ± 1.91% for the estimation of acceleration in the process of continuously performing under approximately π/4 rad/s. This approach can be applied in the practical applications of wearable field.

Self-Regulated Force and Neuromuscular Responses During Fatiguing Isometric Leg Extensions Anchored to a Rating of Perceived Exertion

The purpose of the study was to examine the fatigue-related patterns of responses for electromyography (EMG), mechanomyography (MMG), and force during a sustained isometric muscle action anchored to RPE = 5. Ten men (22.9 ± 2.0 year) performed maximal voluntary isometric contractions (MVIC) prior to and following an isometric leg extension muscle action, which was sustained for a maximal time-limit of 5 min or until it could not be maintained at RPE = 5 (actual time-limit). EMG amplitude (AMP), EMG mean power-frequency (MPF), MMG AMP, MMG MPF, and force values were determined every 5% of the actual time-limit. Regression analyses were used to examine the neuromuscular parameters and force responses, and a t test was used to examine MVIC. The pretest MVIC (62.4 ± 14.3 kg) was significantly (p < 0.001; d = 1.07) greater than posttest (47.9 ± 12.8 kg). The percent decline in force during the sustained isometric muscle action was 47.5 ± 19.6%, and there was a significant, negative force versus time relationship (p < 0.001; R = - 0.980). There was a significant, negative EMG AMP versus time relationship (p < 0.001; R = -0.789), but no significant (p > 0.05) relationships for EMG MPF, MMG AMP, or MMG MPF versus time. The findings indicated that it was necessary to reduce force and EMG AMP to maintain RPE = 5. We hypothesize that the maintenance of RPE = 5 was initially accomplished by an anticipatory feedforward mechanism and then continuous integrations of afferent feedback, which resulted in reductions of EMG AMP and force, due to reductions in neural drive, to attenuate the impact of metabolic byproducts.

A preliminary study of classification of upper limb motions and forces based on mechanomyography

Rehabilitation training is essential for patients who have a history of certain illnesses, such as stroke. As a crucial part of rehabilitation training, upper limb training involves such key factors as upper limb motions and forces. This study investigated three upper limb motions (elbow flexion of 135°, Motion 1; shoulder flexion of 90°, Motion 2; and shoulder abduction of 90°, Motion 3) and various forces (muscle Force 0, no force; holding one 1.4 kg dumbbell, muscle Force 1; holding one 2.4 kg dumbbell, muscle Force 2) in combination to evaluate nine motion patterns. These patterns were completed by twelve healthy volunteers. Mechanomyography (MMG) measurements of the biceps brachii (Channel 1), triceps (Channel 2), and deltoid (Channel 3) muscles were collected. These were subsequently divided into signal segments corresponding to each of the motions using a segmentation method based on average energy. After extracting time-domain features and wavelet packet energy features, support vector machine analysis (SVM) was used for the classification of the upper limb motions and forces based on the MMG measurements. Channel 2 and Channel 3 were shown to play an important role in the classification of upper limb motions, and Channel 1 played a role in the classification of the forces. These results demonstrate that collection of MMG measurements from the three muscles is feasible and suggest a foundation for further studies in which rehabilitation training is evaluated based on MMG measurements.

SVR modelling of mechanomyographic signals predicts neuromuscular stimulation-evoked knee torque in paralyzed quadriceps muscles undergoing knee extension exercise

BACKGROUND AND OBJECTIVE

Using traditional regression modelling, we have previously demonstrated a positive and strong relationship between paralyzed knee extensors' mechanomyographic (MMG) signals and neuromuscular electrical stimulation (NMES)-assisted knee torque in persons with spinal cord injuries. In the present study, a method of estimating NMES-evoked knee torque from the knee extensors' MMG signals using support vector regression (SVR) modelling is introduced and performed in eight persons with chronic and motor complete spinal lesions.

METHODS

The model was developed to estimate knee torque from experimentally derived MMG signals and other parameters related to torque production, including the knee angle and stimulation intensity, during NMES-assisted knee extension.

RESULTS

When the relationship between the actual and predicted torques was quantified using the coefficient of determination (R²), with a Gaussian support vector kernel, the R² value indicated an estimation accuracy of 95% for the training subset and 94% for the testing subset while the polynomial support vector kernel indicated an accuracy of 92% for the training subset and 91% for the testing subset. For the Gaussian kernel, the root mean square error of the model was 6.28 for the training set and 8.19 for testing set, while the polynomial kernels for the training and testing sets were 7.99 and 9.82, respectively.

CONCLUSIONS

These results showed good predictive accuracy for SVR modelling, which can be generalized, and suggested that the MMG signals from paralyzed knee extensors are a suitable proxy for the NMES-assisted torque produced during repeated bouts of isometric knee extension tasks. This finding has potential implications for using MMG signals as torque sensors in NMES closed-loop systems and provides valuable information for implementing this method in research and clinical settings.

Are There Sex-Specific Neuromuscular or Force Responses to Fatiguing Isometric Muscle Actions Anchored to a High Perceptual Intensity?

Keller, JL, Housh, TJ, Hill, EC, Smith, CM, Schmidt, RJ, and Johnson, GO. Are there sex-specific neuromuscular or force responses to fatiguing isometric muscle actions anchored to a high perceptual intensity? J Strength Cond Res XX(X): 000-000, 2019-The purpose of this study was to use the ratings of perceived exertion (RPE) clamp model to examine sex-specific changes in neuromuscular responses and force after a sustained isometric leg extension muscle action anchored to RPE = 8. Twenty adults (10 men and 10 women) performed sustained, isometric leg extension muscle actions at RPE = 8. Electromyographic (EMG) and mechanomyographic signals were recorded from the dominant leg. Neuromuscular and force values resulting from the sustained muscle action were normalized to pretest maximal voluntary isometric contractions (MVICs). The level of significance set for the study was p ≤ 0.05. The pretest MVIC was significantly (p < 0.001) greater (averaged across sex) than posttest MVIC force (55.5 ± 10.0 vs. 47.6 ± 11.1 kg). There was a significant (p < 0.01) decrease from pretest (95.4 ± 7.7 Hz) to posttest (76.2 ± 5.9 Hz) in EMG mean power frequency (MPF) for the men. The normalized force (averaged across sex) decreased significantly (p < 0.001) from the initial timepoint (57.1 ± 16.4%) to the final timepoint (44.3 ± 15.7%) of the sustained muscle action. Normalized EMG MPF (averaged across sex) decreased significantly (p = 0.001) from the initial timepoint (96.4 ± 17.5%) to final timepoint (87.8 ± 18.1%). The men and women exhibited similar fatigue-induced changes in force and neuromuscular parameters; therefore, these findings did not indicate different sex-specific responses after the fatiguing task anchored to a high perception of exertion. The force corresponding to RPE = 8 did not match the anticipated value; so, RPE and percentages of MVIC cannot be used interchangeably, and sustained isometric muscle actions anchored to RPE may elicit unique neuromuscular adaptations.

Electrically evoked wrist extensor muscle fatigue throughout repetitive motion as measured by mechanomyography and near-infrared spectroscopy

Repetitive electrically-evoked muscle contraction leads to accelerated muscle fatigue. This study assessed electrically-evoked fatiguing muscle with changes to mechanomyography root mean square percentage (%RMS-MMG) and tissue saturation index (%TSI) in extensor carpi radialis. Forty healthy volunteers (n=40) performed repetitive electrical-evoked wrist extension to fatigue and results were analyzed pre- and post-fatigue, i.e. 50% power output (%PO) drop. Responses of %PO, %TSI and %RMS-MMG were correlated while the relationships between %RMS-MMG and %TSI were investigated using linear regression. The %TSI for both groups were negatively correlated with declining %PO as the ability of the muscle to take up oxygen became limited due to fatigued muscle. The %RMS-MMG behaved in two different patterns post-fatigue against declining %PO whereby; (i) group A showed positive correlation (%RMS-MMG decreased) throughout the session and (ii) group B demonstrated negative correlation (%RMS-MMG increased) with declining %PO until the end of the session. Regression analysis showed %TSI was inversely proportional to %RMS-MMG during post-fatigue in group A. Small gradients in both groups suggested that %TSI was not sensitive to the changes in %RMS-MMG and they were mutually exclusive. Most correlation and regression changed significantly post-fatigue indicating that after fatigue, the condition of muscle had changed mechanically and physiologically.

Research on GA-SVM Based Head-Motion Classification via Mechanomyography Feature Analysis

This study investigated classification of six types of head motions using mechanomyography (MMG) signals. An unequal segmenting algorithm was adopted to segment the MMG signals generated by head motions. Three types of features (time domain, time-frequency domain and nonlinear dynamics) were extracted to construct five feature sets as candidate datasets for classification analysis. Genetic algorithm optimized support vector machine (GA-SVM) was used to classify the MMG signals. Three different kernel functions, different combinations of feature sets, different number of signal channels and training samples were selected for comparative analysis to evaluate the classification accuracy. Experimental results showed that the classifier had the best overall classification accuracy when using the radial basis function (RBF). Any combination of three different types of feature sets guaranteed an average accuracy of over 80%. In the case of the best combination (feature set 2 + 3 + 5), the classification accuracy was up to 88.2%. Using four channels to acquire MMG signal and no less than 60 training samples can assure a satisfactory classification accuracy.

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.

Neuromuscular Fatigue Does Not Impair the Rate of Force Development in Ballistic Contractions of Submaximal Amplitudes

The effect of muscle fatigue on rate of force development (RFD) is usually assessed during tasks that require participants to reach as quickly as possible maximal or near-maximal force. However, endurance sports require athletes to quickly produce force of submaximal, rather than maximal, amplitudes. Thus, this study investigated the effect of muscle fatigue induced by long-distance running on the capacity to quickly produce submaximal levels of force. Twenty-one male amateur runners were evaluated before and shortly after a half-marathon race. Knee extensors force was recorded under maximal voluntary and electrically evoked contractions. Moreover, a series of ballistic contractions at different submaximal amplitudes (from 20 to 100% of maximal voluntary force) was obtained, by asking the participants to reach submaximal forces as fast as possible. The RFD was calculated for each contraction. After the race, maximal voluntary activation, resting doublet twitch, maximal force, and RFD during maximal contraction decreased (-12, -12, -21, and -19%, respectively, all P-values < 0.0001). Nevertheless, the RFD values measured during ballistic contractions up to 60% of maximal force were unaffected (all P-values > 0.4). Long-distance running impaired the capacity to quickly produce force in ballistic contractions of maximal, but not of submaximal, amplitudes. Overall, these findings suggest that central and peripheral fatigue do not affect the quickness to which muscle contracts across a wide range of submaximal forces. This is a relevant finding for running and other daily life activities that rely on the production of rapid submaximal contractions rather than maximal force levels.

The effect of epoch length on time and frequency domain parameters of electromyographic and mechanomyographic signals

The selection of epoch lengths affects the time and frequency resolution of electromyographic (EMG) and mechanomyographic (MMG) signals, as well as decisions regarding the signal processing techniques to use for determining the power density spectrum. No previous studies, however, have examined the effects of epoch length on parameters of the MMG signal. The purpose of this study was to examine the differences between epoch lengths for EMG amplitude, EMG mean power frequency (MPF), MMG amplitude, and MMG MPF from the VL and VM muscles during MVIC muscle actions as well as at each 10% of the time to exhaustion (TTE) during a continuous isometric muscle action of the leg extensors at 50% of MVIC. During the MVIC trial, there were no significant (p > 0.05) differences between epoch lengths (0.25, 0.50, 1.00, and 2.00-s) for mean absolute values for any of the EMG or MMG parameters. During the submaximal, sustained muscle action, however, absolute MMG amplitude and MMG MPF were affected by the length of epoch. All epoch related differences were eliminated by normalizing the absolute values to MVIC. These findings supported normalizing EMG and MMG parameter values to MVIC and utilizing epoch lengths that ranged from 0.25 to 2.00-s.

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.

Kinesio taping and manual pressure release: Short-term effects in subjects with myofasical trigger point

STUDY DESIGN

Randomized controlled trial.

INTRODUCTION

Myofascial pain syndrome is characterized by myofascial trigger points (MTrPs) and fascia tenderness.

PURPOSE OF THE STUDY

We investigated the effects of manual pressure release (MPR) alone or in combination with taping (MPR/MKT) in subjects with MTrPs.

METHODS

Fifteen and 16 subjects received MPR and MPR/MKT respectively. Outcomes including Pressure pain threshold, muscle stiffness, mechanomyography were assessed at baseline, post-intervention and 7-days later.

RESULTS

Pressure pain threshold improved significantly (d = 1.79, p < 0.005) in both groups. Significant improvement in muscle stiffness in the MPR/MKT group (0.27-0.49 mm) as compared to the MPR group (-0.02-0.23 mm). Mechanomyography amplitude in the MPR/MKT group was significantly higher than that of the MPR group (p < 0.05).

CONCLUSION

MPR and MPR/MKT are effective in reducing pain in these subjects. MPR/MKT has a greater effect on muscle stiffness and contraction amplitude.

LEVEL OF EVIDENCE

IV.

Muscle- and Mode-Specific Responses of the Forearm Flexors to Fatiguing, Concentric Muscle Actions

BACKGROUND

Electromyographic (EMG) and mechanomyographic (MMG) studies of fatigue have generally utilized maximal isometric or dynamic muscle actions, but sport- and work-related activities involve predominately submaximal movements. Therefore, the purpose of the present investigation was to examine the torque, EMG, and MMG responses as a result of submaximal, concentric, isokinetic, forearm flexion muscle actions.

METHODS

Twelve men performed concentric peak torque (PT) and isometric PT trials before (pretest) and after (posttest) performing 50 submaximal (65% of concentric PT), concentric, isokinetic (60°·s^-1), forearm flexion muscle actions. Surface EMG and MMG signals were simultaneously recorded from the biceps brachii and brachioradialis muscles.

RESULTS

The results of the present study indicated similar decreases during both the concentric PT and isometric PT measurements for torque, EMG mean power frequency (MPF), and MMG MPF following the fatiguing workbout, but no changes in EMG amplitude (AMP) or MMG AMP.

CONCLUSIONS

These findings suggest that decreases in torque as a result of fatiguing, dynamic muscle actions may have been due to the effects of metabolic byproducts on excitation⁻contraction coupling as indicated by the decreases in EMG MPF and MMG MPF, but lack of changes in EMG AMP and MMG AMP from both the biceps brachii and brachioradialis muscles.

The effect of exercise hypertrophy and disuse atrophy on muscle contractile properties: a mechanomyographic analysis

PURPOSE

To determine whether mechanomyographic (MMG) determined contractile properties of the biceps brachii change during exercise-induced hypertrophy and subsequent disuse atrophy.

METHODS

Healthy subjects (mean ± SD, 23.7 ± 2.6 years, BMI 21.8 ± 2.4, n = 19) performed unilateral biceps curls (9 sets × 12 repetitions, 5 sessions per week) for 8 weeks (hypertrophic phase) before ceasing exercise (atrophic phase) for the following 8 weeks (non-dominant limb; treatment, dominant limb; control). MMG measures of muscle contractile properties (contraction time; T _c, maximum displacement; D _max, contraction velocity; V _c), electromyographic (EMG) measures of muscle fatigue (median power frequency; MPF), strength measures (maximum voluntary contraction; MVC) and measures of muscle thickness (ultrasound) were obtained.

RESULTS

Two-way repeated measures ANOVA showed significant differences (P < 0.05) between treatment and control limbs. During the hypertrophic phase treatment MVC initially declined (weeks 1-3), due to fatigue (decline in MPF), followed by improvement against control during weeks 6-8. Between weeks 5 and 8 treatment, muscle thickness was greater than control, reflecting gross hypertrophy. MMG variables Dmax (weeks 2, 7) and Vc (weeks 7, 8) declined. During the atrophic phase, MVC (weeks 9-12) and muscle thickness (weeks 9, 10) initially remained high before declining to control levels, reflecting gross atrophy. MMG variables D _max (weeks 9, 14) and V _c (weeks 9, 14, 15) also declined during the atrophic phase. No change in T _c was found throughout the hypertrophic or atrophic phases.

CONCLUSIONS

MMG detects changes in contractile properties during stages of exercise-induced hypertrophy and disuse atrophy suggesting its applicability as a clinical tool in musculoskeletal rehabilitation.

Estimation of Electrically-Evoked Knee Torque from Mechanomyography Using Support Vector Regression

The difficulty of real-time muscle force or joint torque estimation during neuromuscular electrical stimulation (NMES) in physical therapy and exercise science has motivated recent research interest in torque estimation from other muscle characteristics. This study investigated the accuracy of a computational intelligence technique for estimating NMES-evoked knee extension torque based on the Mechanomyographic signals (MMG) of contracting muscles that were recorded from eight healthy males. Simulation of the knee torque was modelled via Support Vector Regression (SVR) due to its good generalization ability in related fields. Inputs to the proposed model were MMG amplitude characteristics, the level of electrical stimulation or contraction intensity, and knee angle. Gaussian kernel function, as well as its optimal parameters were identified with the best performance measure and were applied as the SVR kernel function to build an effective knee torque estimation model. To train and test the model, the data were partitioned into training (70%) and testing (30%) subsets, respectively. The SVR estimation accuracy, based on the coefficient of determination (R²) between the actual and the estimated torque values was up to 94% and 89% during the training and testing cases, with root mean square errors (RMSE) of 9.48 and 12.95, respectively. The knee torque estimations obtained using SVR modelling agreed well with the experimental data from an isokinetic dynamometer. These findings support the realization of a closed-loop NMES system for functional tasks using MMG as the feedback signal source and an SVR algorithm for joint torque estimation.

Torque and mechanomyogram relationships during electrically-evoked isometric quadriceps contractions in persons with spinal cord injury

The interaction between muscle contractions and joint loading produces torques necessary for movements during activities of daily living. However, during neuromuscular electrical stimulation (NMES)-evoked contractions in persons with spinal cord injury (SCI), a simple and reliable proxy of torque at the muscle level has been minimally investigated. Thus, the purpose of this study was to investigate the relationships between muscle mechanomyographic (MMG) characteristics and NMES-evoked isometric quadriceps torques in persons with motor complete SCI. Six SCI participants with lesion levels below C4 [(mean (SD) age, 39.2 (7.9) year; stature, 1.71 (0.05) m; and body mass, 69.3 (12.9) kg)] performed randomly ordered NMES-evoked isometric leg muscle contractions at 30°, 60° and 90° knee flexion angles on an isokinetic dynamometer. MMG signals were detected by an accelerometer-based vibromyographic sensor placed over the belly of rectus femoris muscle. The relationship between MMG root mean square (MMG-RMS) and NMES-evoked torque revealed a very high association (R(2)=0.91 at 30°; R(2)=0.98 at 60°; and R(2)=0.97 at 90° knee angles; P<0.001). MMG peak-to-peak (MMG-PTP) and stimulation intensity were less well related (R(2)=0.63 at 30°; R(2)=0.67 at 60°; and R(2)=0.45 at 90° knee angles), although were still significantly associated (P≤0.006). Test-retest interclass correlation coefficients (ICC) for the dependent variables ranged from 0.82 to 0.97 for NMES-evoked torque, between 0.65 and 0.79 for MMG-RMS, and from 0.67 to 0.73 for MMG-PTP. Their standard error of measurements (SEM) ranged between 10.1% and 31.6% (of mean values) for torque, MMG-RMS and MMG-PTP. The MMG peak frequency (MMG-PF) of 30Hz approximated the stimulation frequency, indicating NMES-evoked motor unit firing rate. The results demonstrated knee angle differences in the MMG-RMS versus NMES-isometric torque relationship, but a similar torque related pattern for MMG-PF. These findings suggested that MMG was well associated with torque production, reliably tracking the motor unit recruitment pattern during NMES-evoked muscle contractions. The strong positive relationship between MMG signal and NMES-evoked torque production suggested that the MMG might be deployed as a direct proxy for muscle torque or fatigue measurement during leg exercise and functional movements in the SCI population.

The influence of myosin heavy chain isoform content on mechanical behavior of the vastus lateralis in vivo

This study examined correlations between type I percent myosin heavy chain isoform content (%MHC) and mechanomyographic amplitude (MMGRMS) during isometric muscle actions. Fifteen (age=21.63±2.39) participants performed 40% and 70% maximal voluntary contractions (MVC) of the leg extensors that included increasing, steady force, and decreasing segments. Muscle biopsies were collected and MMG was recorded from the vastus lateralis. Linear regressions were fit to the natural-log transformed MMGRMS-force relationships (increasing and decreasing segments) and MMGRMS was selected at the targeted force level during the steady force segment. Correlations were calculated among type I%MHC and the b (slopes) terms from the MMGRMS-force relationships and MMGRMS at the targeted force. For the 40% MVC, correlations were significant (P<0.02) between type I%MHC and the b terms from the increasing (r=-0.804) and decreasing (r=-0.568) segments, and MMGRMS from the steady force segment (r=-0.606). Type I%MHC was only correlated with MMGRMS during the steady force segment (P=0.044, r=-0.525) during the 70% MVC. Higher type I%MHC reduced acceleration in MMGRMS (b terms) during the 40% MVC and the amplitude during the steady force segments. The surface MMG signal recorded during a moderate intensity contraction provided insight on the contractile properties of the VL in vivo.

Comparing EMG amplitude patterns of responses during dynamic exercise: polynomial vs log-transformed regression

The purposes of this study were to determine if (a) the log-transformed model can be applied to dynamic exercise and (b) the slope and y-intercept terms can provide additional information above and beyond the polynomial regression analyses. Eleven physically active individuals performed incremental cycle ergometry on a single occasion. Electromyographic electrodes were placed on the three superficial quadriceps muscles to record muscle activation during the exercise test. The patterns of responses for electromyographic amplitude vs power output were analyzed with polynomial and log-transformed regression models. The results of the polynomial regression for the composite data indicated that the best-fit model for the vastus lateralis muscle was linear (R(2) = 0.648, P < 0.0001), whereas the best-fit model for the rectus femoris (R(2) = 0.346, P = 0.013) and vastus medialis (R(2) = 0.764,P = 0.020) muscles was quadratic. One-way repeated measures analyses indicated no significant differences(P > 0.05) across the three superficial quadriceps muscles for the slope and y-intercept terms. These findings suggest that the log-transformed model may be a more versatile statistical approach to examining neuromuscular responses during dynamic exercise.

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.

Comparative study of a muscle stiffness sensor and electromyography and mechanomyography under fatigue conditions

This paper proposes the feasibility of a stiffness measurement for muscle contraction force estimation under muscle fatigue conditions. Bioelectric signals have been widely studied for the estimation of the contraction force for physical human-robot interactions, but the correlation between the biosignal and actual motion is decreased under fatigue conditions. Muscle stiffness could be a useful contraction force estimator under fatigue conditions because it measures the same physical quantity as the muscle contraction that generates the force. Electromyography (EMG), mechanomyography (MMG), and a piezoelectric resonance-based active muscle stiffness sensor were used to analyze the biceps brachii under isometric muscle fatigue conditions with reference force sensors at the end of the joint. Compared to EMG and MMG, the change in the stiffness signal was smaller (p < 0.05) in the invariable contraction force generation test until failure. In addition, in the various contraction level force generation tests, the stiffness signal under the fatigue condition changed <10% (p < 0.05) compared with the signal under non-fatigue conditions. This result indicates that the muscle stiffness signal is less sensitive to muscle fatigue than other biosignals. This investigation provides insights into methods of monitoring and compensating for muscle fatigue.