Longitudinal and transverse propagation of surface mechanomyographic waves generated by single motor unit activity

BiLSTM-Based Joint Torque Prediction From Mechanomyogram During Isometric Contractions: A Proof of Concept Study

Quantifying muscle strength is an important measure in clinical settings; however, there is a lack of practical tools that can be deployed for routine assessment. The purpose of this study is to propose a deep learning model for ankle plantar flexion torque prediction from time-series mechanomyogram (MMG) signals recorded during isometric contractions (i.e., a similar form to manual muscle testing procedure in clinical practice) and to evaluate its performance. Four different deep learning models in terms of model architecture (based on a stacked bidirectional long short-term memory and dense layers) were designed with different combinations of the number of units (from 32 to 512) and dropout ratio (from 0.0 to 0.8), and then evaluated for prediction performance by conducting the leave-one-subject-out cross-validation method from the 10-subject dataset. As a result, the models explained more variance in the untrained test dataset as the error metrics (e.g., root-mean-square error) decreased and as the slope of the relationship between the measured and predicted joint torques became closer to 1.0. Although the slope estimates appear to be sensitive to an individual dataset, >70% of the variance in nine out of 10 datasets was explained by the optimal model. These results demonstrated the feasibility of the proposed model as a potential tool to quantify average joint torque during a sustained isometric contraction.

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.

A Novel Mechanomyography (MMG) Sensor Based on Piezo-Resistance Principle and with a Pyramidic Microarray

Flexible piezoresistive sensors built by printing nanoparticles onto soft substrates are crucial for continuous health monitoring and wearable devices. In this study, a mechanomyography (MMG) sensor was developed using a flexible piezoresistive MMG signal sensor based on a pyramidal polydimethylsiloxane (PDMS) microarray sprayed with carbon nanotubes (CNTs). The experiment was conducted, and the results show that the sensitivity of the sensor can reach 0.4 kPa-1 in the measurement range of 0~1.5 kPa, and the correlation reached 96%. This has further implications for the possibility that muscle activation can be converted into mechanical movement. The integrity of the sensor in terms of its MMG signal acquisition was tested based on five subjects who were performing arm bending and arm extending movements. The results of this test were promising.

Kinematics of individual muscle units in natural contractions measured in vivo using ultrafast ultrasound

OBJECTIVE

The study of human neuromechanical control at the motor unit (MU) level has predominantly focussed on electrical activity and force generation, whilst the link between these, i.e., the muscle deformation, has not been widely studied. To address this gap, we analysed the kinematics of muscle units in natural contractions.

APPROACH

We combined high-density surface electromyography (HDsEMG) and ultrafast ultrasound (US) recordings, at 1000 frames per second, from the tibialis anterior muscle to measure the motion of the muscular tissue caused by individual MU contractions. The MU discharge times were identified online by decomposition of the HDsEMG and provided as biofeedback to 12 subjects who were instructed to keep the MU active at the minimum discharge rate (9.8 ± 4.7 pulses per second; force less than 10% of the maximum). The series of discharge times were used to identify the velocity maps associated with 51 single muscle unit movements with high spatio-temporal precision, by a novel processing method on the concurrently recorded US images. From the individual MU velocity maps, we estimated the region of movement, the duration of the motion, the contraction time, and the excitation-contraction (E-C) coupling delay.

MAIN RESULTS

Individual muscle unit motions could be reliably identified from the velocity maps in 10 out of 12 subjects. The duration of the motion, total contraction time, and E-C coupling were 17.9 ± 5.3 ms, 56.6 ± 8.4 ms, and 3.8 ± 3.0 ms (n = 390 across 10 participants). The experimental measures also provided the first evidence of muscle unit twisting during voluntary contractions and MU territories with distinct split regions.

SIGNIFICANCE

The proposed method allows for the study of kinematics of individual MU twitches during natural contractions. The described measurements and characterisations open new avenues for the study of neuromechanics in healthy and pathological conditions.

Characterizing Musculoskeletal Tissue Mechanics Based on Shear Wave Propagation: A Systematic Review of Current Methods and Reported Measurements

Developing methods for the non-invasive characterization of the mechanics of musculoskeletal tissues is an ongoing research focus in biomechanics. Often, these methods use the speed of shear wave propagation to characterize tissue mechanics (e.g., shear wave elastography and shear wave tensiometry). The primary purpose of this systematic review was to identify, compare, and contrast current methods for exciting and measuring shear wave propagation in musculoskeletal tissues. We conducted searches in the Web of Science, PubMed, and Scopus databases for studies published from January 1, 1900, to May 1, 2020. These searches targeted both shear wave excitation using acoustic pushes and mechanical taps, and shear wave speed measurement using ultrasound, magnetic resonance imaging, accelerometers, and laser Doppler vibrometers. Two reviewers independently screened and reviewed the articles, identifying 524 articles that met our search criteria. Regarding shear wave excitation, we found that acoustic pushes are useful for exciting shear waves through the thickness of the tissue of interest, and mechanical taps are useful for exciting shear waves in wearable applications. Regarding shear wave speed measurement, we found that ultrasound is used most broadly to measure shear waves due to its ability to study regional differences and target specific tissues of interest. The strengths of magnetic resonance imaging, accelerometers, and laser Doppler vibrometers make them advantageous to measure shear wave speeds for high-resolution shear wave imaging, wearable measurements, and non-contact ex vivo measurements, respectively. The advantages that each method offers for exciting and measuring shear waves indicate that a variety of systems can be assembled using currently available technologies to determine musculoskeletal tissue material behavior across a range of innovative applications.

Case Study: Intra- and Interpersonal Coherence of Muscle and Brain Activity of Two Coupled Persons during Pushing and Holding Isometric Muscle Action

Inter-brain synchronization is primarily investigated during social interactions but had not been examined during coupled muscle action between two persons until now. It was previously shown that mechanical muscle oscillations can develop coherent behavior between two isometrically interacting persons. This case study investigated if inter-brain synchronization appears thereby, and if differences of inter- and intrapersonal muscle and brain coherence exist regarding two different types of isometric muscle action. Electroencephalography (EEG) and mechanomyography/mechanotendography (MMG/MTG) of right elbow extensors were recorded during six fatiguing trials of two coupled isometrically interacting participants (70% MVIC). One partner performed holding and one pushing isometric muscle action (HIMA/PIMA; tasks changed). The wavelet coherence of all signals (EEG, MMG/MTG, force, ACC) were analyzed intra- and interpersonally. The five longest coherence patches in 8−15 Hz and their weighted frequency were compared between real vs. random pairs and between HIMA vs. PIMA. Real vs. random pairs showed significantly higher coherence for intra-muscle, intra-brain, and inter-muscle-brain activity (p < 0.001 to 0.019). Inter-brain coherence was significantly higher for real vs. random pairs for EEG of right and central areas and for sub-regions of EEG left (p = 0.002 to 0.025). Interpersonal muscle-brain synchronization was significantly higher than intrapersonal one, whereby it was significantly higher for HIMA vs. PIMA. These preliminary findings indicate that inter-brain synchronization can arise during muscular interaction. It is hypothesized both partners merge into one oscillating neuromuscular system. The results reinforce the hypothesis that HIMA is characterized by more complex control strategies than PIMA. The pilot study suggests investigating the topic further to verify these results on a larger sample size. Findings could contribute to the basic understanding of motor control and is relevant for functional diagnostics such as the manual muscle test which is applied in several disciplines, e.g., neurology, physiotherapy.

Identification of single motor units in skeletal muscle under low force isometric voluntary contractions using ultrafast ultrasound

The central nervous system (CNS) controls skeletal muscles by the recruitment of motor units (MUs). Understanding MU function is critical in the diagnosis of neuromuscular diseases, exercise physiology and sports, and rehabilitation medicine. Recording and analyzing the MUs’ electrical depolarization is the basis for state-of-the-art methods. Ultrafast ultrasound is a method that has the potential to study MUs because of the electrical depolarizations and consequent mechanical twitches. In this study, we evaluate if single MUs and their mechanical twitches can be identified using ultrafast ultrasound imaging of voluntary contractions. We compared decomposed spatio-temporal components of ultrasound image sequences against the gold standard needle electromyography. We found that 31% of the MUs could be successfully located and their firing pattern extracted. This method allows new non-invasive opportunities to study mechanical properties of MUs and the CNS control in neuromuscular physiology.

Wearable MMG-Plus-One Armband: Evaluation of Normal Force on Mechanomyography (MMG) to Enhance Human-Machine Interfacing

In this paper, we introduce a new mode of mechanomyography (MMG) signal capture for enhancing the performance of human-machine interfaces (HMIs) through modulation of normal pressure at the sensor location. Utilizing this novel approach, increased MMG signal resolution is enabled by a tunable degree of freedom normal to the sensor-skin contact area. We detail the mechatronic design, experimental validation, and user study of an armband with embedded acoustic sensors demonstrating this capacity. The design is motivated by the nonlinear viscoelasticity of the tissue, which increases with the normal surface pressure. This, in theory, results in higher conductivity of mechanical waves and hypothetically allows to interface with deeper muscle; thus, enhancing the discriminative information context of the signal space. Ten subjects (seven able-bodied and three trans-radial amputees) participated in a study consisting of the classification of hand gestures through MMG while increasing levels of contact force were administered. Four MMG channels were positioned around the forearm and placed over the flexor carpi radialis, brachioradialis, extensor digitorum communis, and flexor carpi ulnaris muscles. A total of 852 spectrotemporal features were extracted (213 features per each channel) and passed through a Neighborhood Component Analysis (NCA) technique to select the most informative neurophysiological subspace of the features for classification. A linear support vector machine (SVM) then classified the intended motion of the user. The results indicate that increasing the normal force level between the MMG sensor and the skin can improve the discriminative power of the classifier, and the corresponding pattern can be user-specific. These results have significant implications enabling embedding MMG sensors in sockets for prosthetic limb control and HMI.

Association of anthropometric parameters with amplitude and crosstalk of mechanomyographic signals during forearm flexion, pronation and supination torque tasks

This study aimed to quantify the association of four anthropometric parameters of the human arm, namely, the arm circumference (CA), arm length (LA), skinfold thickness (ST) and inter-sensor distance (ISD), with amplitude (RMS) and crosstalk (CT) of mechanomyography (MMG) signals. Twenty-five young, healthy, male participants were recruited to perform forearm flexion, pronation and supination torque tasks. Three accelerometers were employed to record the MMG signals from the biceps brachii (BB), brachialis (BRA) and brachioradialis (BRD) at 80% maximal voluntary contraction (MVC). Signal RMS was used to quantify the amplitude of the MMG signals from a muscle, and cross-correlation coefficients were used to quantify the magnitude of the CT among muscle pairs (BB & BRA, BRA & BRD, and BB & BRD). For all investigated muscles and pairs, RMS and CT showed negligible to low negative correlations with CA, LA and ISD (r = −0.0001–−0.4611), and negligible to moderate positive correlations with ST (r = 0.004–0.511). However, almost all of these correlations were statistically insignificant (p > 0.05). These findings suggest that RMS and CT values for the elbow flexor muscles recorded and quantified using accelerometers appear invariant to anthropometric parameters.

Coherent behavior of neuromuscular oscillations between isometrically interacting subjects: experimental study utilizing wavelet coherence analysis of mechanomyographic and mechanotendographic signals

Previous research has shown that electrical muscle activity is able to synchronize between muscles of one subject. The ability to synchronize the mechanical muscle oscillations measured by Mechanomyography (MMG) is not described sufficiently. Likewise, the behavior of myofascial oscillations was not considered yet during muscular interaction of two human subjects. The purpose of this study is to investigate the myofascial oscillations intra- and interpersonally. For this the mechanical muscle oscillations of the triceps and the abdominal external oblique muscles were measured by MMG and the triceps tendon was measured by mechanotendography (MTG) during isometric interaction of two subjects (n = 20) performed at 80% of the MVC using their arm extensors. The coherence of MMG/MTG-signals was analyzed with coherence wavelet transform and was compared with randomly matched signal pairs. Each signal pairing shows significant coherent behavior. Averagely, the coherent phases of n = 485 real pairings last over 82 ± 39 % of the total duration time of the isometric interaction. Coherent phases of randomly matched signal pairs take 21 ± 12 % of the total duration time (n = 39). The difference between real vs. randomly matched pairs is significant (U = 113.0, p = 0.000, r = 0.73). The results show that the neuromuscular system seems to be able to synchronize to another neuromuscular system during muscular interaction and generate a coherent behavior of the mechanical muscular oscillations. Potential explanatory approaches are discussed.

Eccentric exercise induces spatial changes in the mechanomyographic activity of the upper trapezius muscle

In this study, we hypothesized that the recordings of multichannel mechanomyography (MMG) of the upper trapezius muscle would reveal spatially dependent manifestations in the presence of delayed onset muscle soreness occurring 24 hours after eccentric exercise (ECC). Sixteen participants performed high-intensity eccentric exercises (5 sets of 10 eccentric contractions at 100% of max elevation force) targeting the upper trapezius on their dominant side. Twelve accelerometers were attached to record MMG activity during submaximal exercise consisting of static and dynamic arm flexion and abduction. Measurements were taken before and 24 hours after ECC. Average rectified value (ARV), percentage of determinism (% DET), and recurrence (% REC) of the MMG signals were computed to estimate the level of muscular activity and the magnitude of regularity of the MMG. The ARV, % REC, and % DET maps revealed heterogeneous MMG activity of the upper trapezius 24 hours after ECC when compared with before. Increased ARV, % REC, and % DET were found 24 hours after ECC when compared with before. The study provides new key information on how a single muscle responds to ECC. Our findings suggest that multichannel MMG and nonlinear analyses may detect muscular and musculo-tendinous alterations due to ECC.

Reliability of mechanomyographic amplitude measurements for trunk muscles during maximal voluntary isometric contraction

BACKGROUND

Mechanomyography (MMG) has been used to investigate mechanical characteristics of muscle contraction in clinical and experimental settings.

OBJECTIVE

The aim of this study was to determine the test-retest reliability of mechanomyographic amplitude (MMGRMS) measurements as a tool for measuring the maximal voluntary isometric contractions (MVICs) of trunk muscles in healthy participants.

METHODS

There were ten young adults participating in this study. Accelerometers were used to detect surface MMG signals from three trials of 5-s MVICs of the rectus abdominis, external obliques, erector spinae, and multifidus in the vertical, transverse, and longitudinal directions. Intraclass correlation coefficient (ICC), standard error of measurement (SEM), and minimum detectable change were calculated.

RESULTS

Good to excellent test-retest reliability of mechanomyographic amplitude (MMGRMS) measurements was achieved for all MVICs of trunk muscles in healthy participants, as indicated by ICCs ranging from 0.99 to 0.64 for MMGRMS of the trunk muscles during MVIC.

CONCLUSIONS

This study demonstrates that MMG is a reliable measurement to detect the activation amplitudes of trunk muscles during MVIC.

Are there two forms of isometric muscle action? Results of the experimental study support a distinction between a holding and a pushing isometric muscle function

BACKGROUND

In isometric muscle function, there are subjectively two different modes of performance: one can either hold isometrically - thus resist an impacting force - or push isometrically - therefore work against a stable resistance. The purpose of this study is to investigate whether or not two different isometric muscle actions - the holding vs. pushing one (HIMA vs PIMA) - can be distinguished by objective parameters.

METHODS

Ten subjects performed two different measuring modes at 80% of MVC realized by a special pneumatic system. During HIMA the subject had to resist the defined impacting force of the pneumatic system in an isometric position, whereby the force of the cylinder works in direction of elbow flexion against the subject. During PIMA the subject worked isometrically in direction of elbow extension against a stable position of the system. The signals of pressure, force, acceleration and mechanomyography/-tendography (MMG/MTG) of the elbow extensor (MMGtri/MTGtri) and the abdominal muscle (MMGobl) were recorded and evaluated concerning the duration of maintaining the force level (force endurance) and the characteristics of MMG-/MTG-signals. Statistical group differences comparing HIMA vs. PIMA were estimated using SPSS.

RESULTS

Significant differences between HIMA and PIMA were especially apparent regarding the force endurance: During HIMA the subjects showed a decisively shorter time of stable isometric position (19 ± 8 s) in comparison with PIMA (41 ± 24 s; p = .005). In addition, during PIMA the longest isometric plateau amounted to 59.4% of the overall duration time of isometric measuring, during HIMA it lasted 31.6% (p = .000). The frequency of MMG/MTG did not show significant differences. The power in the frequency ranges of 8-15 Hz and 10-29 Hz was significantly higher in the MTGtri performing HIMA compared to PIMA (but not for the MMGs). The amplitude of MMG/MTG did not show any significant difference considering the whole measurement. However, looking only at the last 10% of duration time (exhaustion), the MMGtri showed significantly higher amplitudes during PIMA.

CONCLUSION

The results suggest that under holding isometric conditions muscles exhaust earlier. That means that there are probably two forms of isometric muscle action. We hypothesize two potential reasons for faster yielding during HIMA: (1) earlier metabolic fatigue of the muscle fibers and (2) the complexity of neural control strategies.

Muscle stiffness estimation using a system identification technique applied to evoked mechanomyogram during cycling exercise

The aims of this study were to develop a method to extract the evoked mechanomyogram (MMG) during cycling exercise and to clarify muscle stiffness at various cadences, workloads, and power. Ten young healthy male participants were instructed to pedal a cycle ergometer at cadences of 40 and 60 rpm. The loads were 4.9, 9.8, 14.7, and 19.6 N, respectively. One electrical stimulus per two pedal rotations was applied to the vastus lateralis muscle at a knee angle of 80° in the down phase. MMGs were measured using a capacitor microphone, and the MMGs were divided into stimulated and non-stimulated sequences. Each sequence was synchronously averaged. The synchronously averaged non-stimulated MMG was subtracted from the synchronously averaged stimulated MMG to extract an evoked MMG. The evoked MMG system was identified and the poles of the transfer function were calculated. The poles and mass of the vastus lateralis muscle were used to estimate muscle stiffness. Results showed that muscle stiffness was 186-626 N /m and proportional to the workloads and power. In conclusion, our method can be used to assess muscle stiffness proportional to the workload and power.

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.

Longitudinal, lateral and transverse axes of forearm muscles influence the crosstalk in the mechanomyographic signals during isometric wrist postures

Problem Statement

In mechanomyography (MMG), crosstalk refers to the contamination of the signal from the muscle of interest by the signal from another muscle or muscle group that is in close proximity.

Purpose

The aim of the present study was two-fold: i) to quantify the level of crosstalk in the mechanomyographic (MMG) signals from the longitudinal (L_o), lateral (L_a) and transverse (T_r) axes of the extensor digitorum (ED), extensor carpi ulnaris (ECU) and flexor carpi ulnaris (FCU) muscles during isometric wrist flexion (WF) and extension (WE), radial (RD) and ulnar (UD) deviations; and ii) to analyze whether the three-directional MMG signals influence the level of crosstalk between the muscle groups during these wrist postures.

Methods

Twenty, healthy right-handed men (mean ± SD: age = 26.7±3.83 y; height = 174.47±6.3 cm; mass = 72.79±14.36 kg) participated in this study. During each wrist posture, the MMG signals propagated through the axes of the muscles were detected using three separate tri-axial accelerometers. The x-axis, y-axis, and z-axis of the sensor were placed in the L_o, L_a, and T_r directions with respect to muscle fibers. The peak cross-correlations were used to quantify the proportion of crosstalk between the different muscle groups.

Results

The average level of crosstalk in the MMG signals generated by the muscle groups ranged from: 34.28–69.69% for the L_o axis, 27.32–52.55% for the L_a axis and 11.38–25.55% for the T_r axis for all participants and their wrist postures. The T_r axes between the muscle groups showed significantly smaller crosstalk values for all wrist postures [F (2, 38) = 14–63, p<0.05, η² = 0.416–0.769].

Significance

The results may be applied in the field of human movement research, especially for the examination of muscle mechanics during various types of the wrist postures.

Synchronization of Muscular Oscillations Between Two Subjects During Isometric Interaction

Muscles oscillate with a frequency around 10 Hz. But what happens with myofascial oscillations, if two neuromuscular systems interact? The purpose of this study was to examine this question, initially, on the basis of a case study. Oscillations of the triceps brachii muscles of two subjects were determined through mechanomyography (MMG) during isometric interaction. The MMG-signals were analyzed concerning the interaction of the two subjects with algorithms of nonlinear dynamics. In this case study it could be shown, that the muscles of both neuromuscular systems also oscillate with the known frequency (here 12 Hz) during interaction. Furthermore, both subjects were able to adapt their oscillations against each other. This adjustment induced a significant (α < .05) coherent behavior, which was characterized by a phase shifting of approximately 90°. The authors draw the conclusion, that the complementary neuromuscular partners potentially have the ability of mutual synchronization.

Mechanomyogram for muscle function assessment: a review

BACKGROUND

Mechanomyography (MMG) has been extensively applied in clinical and experimental practice to examine muscle characteristics including muscle function (MF), prosthesis and/or switch control, signal processing, physiological exercise, and medical rehabilitation. Despite several existing MMG studies of MF, there has not yet been a review of these. This study aimed to determine the current status on the use of MMG in measuring the conditions of MFs.

METHODOLOGY/PRINCIPAL FINDINGS

Five electronic databases were extensively searched for potentially eligible studies published between 2003 and 2012. Two authors independently assessed selected articles using an MS-Word based form created for this review. Several domains (name of muscle, study type, sensor type, subject's types, muscle contraction, measured parameters, frequency range, hardware and software, signal processing and statistical analysis, results, applications, authors' conclusions and recommendations for future work) were extracted for further analysis. From a total of 2184 citations 119 were selected for full-text evaluation and 36 studies of MFs were identified. The systematic results find sufficient evidence that MMG may be used for assessing muscle fatigue, strength, and balance. This review also provides reason to believe that MMG may be used to examine muscle actions during movements and for monitoring muscle activities under various types of exercise paradigms.

CONCLUSIONS/SIGNIFICANCE

Overall judging from the increasing number of articles in recent years, this review reports sufficient evidence that MMG is increasingly being used in different aspects of MF. Thus, MMG may be applied as a useful tool to examine diverse conditions of muscle activity. However, the existing studies which examined MMG for MFs were confined to a small sample size of healthy population. Therefore, future work is needed to investigate MMG, in examining MFs between a sufficient number of healthy subjects and neuromuscular patients.

Imaging two-dimensional mechanical waves of skeletal muscle contraction

Skeletal muscle contraction is related to rapid mechanical shortening and thickening. Recently, specialized ultrasound systems have been applied to demonstrate and quantify transient tissue velocities and one-dimensional (1-D) propagation of mechanical waves during muscle contraction. Such waves could potentially provide novel information on musculoskeletal characteristics, function and disorders. In this work, we demonstrate two-dimensional (2-D) mechanical wave imaging following the skeletal muscle contraction. B-mode image acquisition during multiple consecutive electrostimulations, speckle-tracking and a time-stamp sorting protocol were used to obtain 1.4 kHz frame rate 2-D tissue velocity imaging of the biceps brachii muscle contraction. The results present novel information on tissue velocity profiles and mechanical wave propagation. In particular, counter-propagating compressional and shear waves in the longitudinal direction were observed in the contracting tissue (speed 2.8-4.4 m/s) and a compressional wave in the transverse direction of the non-contracting muscle tissue (1.2-1.9 m/s). In conclusion, analysing transient 2-D tissue velocity allows simultaneous assessment of both active and passive muscle tissue properties.

Bulk movement included in multi-channel mechanomyography: similarity between mechanomyography of resting muscle and that of contracting muscle

Although mechanomyography (MMG) reflects local vibrations from contracting muscle fibers, it also includes bulk movement: deformation in global soft tissue around measuring points. To distinguish between them, we compared the multi-channel MMG of resting muscle, which dominantly reflected the bulk movement caused by arterial pulsations, to that of the contracting muscle. The MMG signals were measured at five points around the upper arms of 10 male subjects during resting and during isometric ramp contraction from 5% to 85% of maximal voluntary contraction (MVC) of the biceps brachii muscle. The characteristics of bulk movement were defined as the amplitude distribution and phase relation among the five MMG signals. The bulk movement characteristics during the rest state were not necessarily the same among the subjects. However, below 30 Hz, each subject's characteristics remained the same from the rest state (0% MVC) to the contracting state (80% MVC), at which the bulk movement mainly originates from muscle contraction activity. Results show that the MMG of the low frequency domain (<30 Hz) includes bulk movement depending on the mechanical deformation characteristics of each subject's body, for a wide range of muscle contraction intensities.

Propagation direction of natural mechanical oscillations in the biceps brachii muscle during voluntary contraction

The aim of the study was to determine the directionality of the coupling of mechanical vibrations across the biceps brachii muscle at different frequencies of interest during voluntary contraction. The vibrations that are naturally generated by skeletal muscles were recorded by a two-dimensional array of skin mounted accelerometers over the biceps brachii muscle (surface mechanomyogram, S-MMG) during voluntary isometric contractions in ten healthy young men. As a measure of the similarity of vibration between a given pair of accelerometers, the spatial coherence of S-MMG at low (f<25Hz) and high (f>25Hz) frequency bands were investigated to determine if the coupling of the natural mechanical vibrations were due to the different physiological muscle activity at low and high frequencies. In both frequency bands, spatial coherence values for sensor pairs aligned longitudinally along the proximal to distal ends of the biceps were significantly higher compared with those for the sensor pairs oriented perpendicular to the muscle fibers. This difference was more evident at the higher frequency band. The findings indicated that coherent mechanical oscillations mainly propagated along the longitudinal direction of the biceps brachii muscle fibers at high frequencies (f>25Hz).

The effect of accelerometer location on the classification of single-site forearm mechanomyograms

Background

Recently, pattern recognition methods have been deployed in the classification of multiple activation states from mechanomyogram (MMG) signals for the purpose of controlling switching interfaces. Given the propagative properties of MMG signals, it has been suggested that MMG classification should be robust to changes in sensor placement. Nonetheless, this purported robustness remains speculative to date. This study sought to quantify the change in classification accuracy, if any, when a classifier trained with MMG signals from the muscle belly, is subsequently tested with MMG signals from a nearby location.

Methods

An arrangement of 5 accelerometers was attached to the flexor carpi radialis muscle of 12 able-bodied participants; a reference accelerometer was located over the muscle belly, two peripheral accelerometers were positioned along the muscle's transverse axis and two more were aligned to the muscle's longitudinal axis. Participants performed three classes of muscle activity: wrist flexion, wrist extension and semi-pronation. A collection of time, frequency and time-frequency features were considered and reduced by genetic feature selection. The classifier, trained using features from the reference accelerometer, was tested with signals from the longitudinally and transversally displaced accelerometers.

Results

Classification degradation due to accelerometer displacement was significant for all participants, and showed no consistent trend with the direction of displacement. Further, the displaced accelerometer signals showed task-dependent de-correlations with respect to the reference accelerometer.

Conclusions

These results indicate that MMG signal features vary with spatial location and that accelerometer displacements of only 1-2 cm cause sufficient feature drift to significantly diminish classification accuracy. This finding emphasizes the importance of consistent sensor placement between MMG classifier training and deployment for accurate control of switching interfaces.

On functional motor adaptations: from the quantification of motor strategies to the prevention of musculoskeletal disorders in the neck-shoulder region

BACKGROUND

Occupations characterized by a static low load and by repetitive actions show a high prevalence of work-related musculoskeletal disorders (WMSD) in the neck-shoulder region. Moreover, muscle fatigue and discomfort are reported to play a relevant initiating role in WMSD.

AIMS

To investigate relationships between altered sensory information, i.e. localized muscle fatigue, discomfort and pain and their associations to changes in motor control patterns.

MATERIALS & METHODS

In total 101 subjects participated. Questionnaires, subjective assessments of perceived exertion and pain intensity as well as surface electromyography (SEMG), mechanomyography (MMG), force and kinematics recordings were performed.

RESULTS

Multi-channel SEMG and MMG revealed that the degree of heterogeneity of the trapezius muscle activation increased with fatigue. Further, the spatial organization of trapezius muscle activity changed in a dynamic manner during sustained contraction with acute experimental pain. A graduation of the motor changes in relation to the pain stage (acute, subchronic and chronic) and work experience were also found. The duration of the work task was shorter in presence of acute and chronic pain. Acute pain resulted in decreased activity of the painful muscle while in subchronic and chronic pain, a more static muscle activation was found. Posture and movement changed in the presence of neck-shoulder pain. Larger and smaller sizes of arm and trunk movement variability were respectively found in acute pain and subchronic/chronic pain. The size and structure of kinematics variability decreased also in the region of discomfort. Motor variability was higher in workers with high experience. Moreover, the pattern of activation of the upper trapezius muscle changed when receiving SEMG/MMG biofeedback during computer work.

DISCUSSION

SEMG and MMG changes underlie functional mechanisms for the maintenance of force during fatiguing contraction and acute pain that may lead to the widespread pain seen in WMSD. A lack of harmonious muscle recruitment/derecruitment may play a role in pain transition. Motor behavior changed in shoulder pain conditions underlining that motor variability may play a role in the WMSD development as corroborated by the changes in kinematics variability seen with discomfort. This prognostic hypothesis was further, supported by the increased motor variability among workers with high experience.

CONCLUSION

Quantitative assessments of the functional motor adaptations can be a way to benchmark the pain status and help to indentify signs indicating WMSD development. Motor variability is an important characteristic in ergonomic situations. Future studies will investigate the potential benefit of inducing motor variability in occupational settings.

The effects of accelerometer placement on mechanomyographic amplitude and mean power frequency during cycle ergometry

The purposes of this study were threefold: (1) to compare the power output related patterns of absolute and normalized MMG amplitude and MPF responses for proximal and distal accelerometer placements on the vastus lateralis (VL) muscle during incremental cycle ergometry; (2) to examine the influence of accelerometer placements on mean absolute MMG amplitude and MPF values; and (3) to determine the effects of normalization on mean MMG amplitude and MPF values from proximal and distal accelerometer placements. Fifteen adults (10 men and 5 women; mean+/-SD age=23.9+/-3.1 years) performed incremental cycle ergometry tests to exhaustion. Two accelerometers were placed proximal and distal on the VL muscle. Paired t-tests indicated that absolute MMG amplitude values for the proximal accelerometer were greater (p<0.05) than the distal accelerometer at all power outputs. The normalized MMG amplitude also had greater values for the proximal accelerometer at all power outputs, except 50W. There were no differences, however, between proximal and distal accelerometers for absolute MMG MPF, except at 75W, and normalization eliminated this difference. Twenty-seven percent of the subjects exhibited different power output related patterns of responses between accelerometer placements for MMG amplitude and 47% exhibited different patterns for MPF. These findings indicated that normalization did not eliminate the influence of accelerometer placement on MMG amplitude and highlighted the importance of standardizing accelerometer placements to compare MMG values during cycle ergometry.

Two dimensional spatial coherence of the natural vibrations of the biceps brachii muscle generated during voluntary contractions

Surface mechanomyograms (S-MMGs) are recorded from low frequency (〈100 Hz) mechanical oscillations that are naturally generated by skeletal muscle during voluntary contractions. This study investigates a method to determine the propagation directionality of the S-MMG waves. A 3×5 grid of skin mounted accelerometers was mounted on the biceps brachii muscle during submaximal voluntary contractions. This method resulted in findings that the propagation directionality of the S-MMGs are frequency dependent. At high frequencies (>25 Hz), high spatial coherence values were only measured for sensor pairs aligned along the proximal to distal (i.e. longitudinal) orientation, thus indicating that coherent S-MMG were mainly propagating along the muscle fibers direction of the biceps brachii at those frequencies. On the other hand, at lower frequencies (〈25 Hz), the S-MMG spatial coherence values did not exhibit a specific directionality. This method provides results that have an important implication of finding the average phase velocity of the propagating S-MMG wave, which can be used to determine viscoelastic properties of skeletal muscles.