Non-invasive characterization of single motor unit electromyographic and mechanomyographic activities in the biceps brachii muscle

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.

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.

Inspiratory muscle activation increases with COPD severity as confirmed by non-invasive mechanomyographic analysis

There is a lack of instruments for assessing respiratory muscle activation during the breathing cycle in clinical conditions. The aim of the present study was to evaluate the usefulness of the respiratory muscle mechanomyogram (MMG) for non-invasively assessing the mechanical activation of the inspiratory muscles of the lower chest wall in both patients with chronic obstructive pulmonary disease (COPD) and healthy subjects, and to investigate the relationship between inspiratory muscle activation and pulmonary function parameters. Both inspiratory mouth pressure and respiratory muscle MMG were simultaneously recorded under two different respiratory conditions, quiet breathing and incremental ventilatory effort, in 13 COPD patients and 7 healthy subjects. The mechanical activation of the inspiratory muscles was characterised by the non-linear multistate Lempel–Ziv index (MLZ) calculated over the inspiratory time of the MMG signal. Subsequently, the efficiency of the inspiratory muscle mechanical activation was expressed as the ratio between the peak inspiratory mouth pressure to the amplitude of the mechanical activation. This activation estimated using the MLZ index correlated strongly with peak inspiratory mouth pressure throughout the respiratory protocol in both COPD patients (r = 0.80, p<0.001) and healthy (r = 0.82, p<0.001). Moreover, the greater the COPD severity in patients, the greater the level of muscle activation (r = -0.68, p = 0.001, between muscle activation at incremental ventilator effort and FEV₁). Furthermore, the efficiency of the mechanical activation of inspiratory muscle was lower in COPD patients than healthy subjects (7.61±2.06 vs 20.42±10.81, respectively, p = 0.0002), and decreased with increasing COPD severity (r = 0.78, p<0.001, between efficiency of the mechanical activation at incremental ventilatory effort and FEV₁). These results suggest that the respiratory muscle mechanomyogram is a good reflection of inspiratory effort and can be used to estimate the efficiency of the mechanical activation of the inspiratory muscles. Both, inspiratory muscle activation and inspiratory muscle mechanical activation efficiency are strongly correlated with the pulmonary function. Therefore, the use of the respiratory muscle mechanomyogram can improve the assessment of inspiratory muscle activation in clinical conditions, contributing to a better understanding of breathing in COPD patients.

The influence of confounding factors on the relationship between muscle contraction level and MF and MPF values of EMG signal: a review

The purpose of this article is to gather results of studies on the relationship between median frequency (MF) and mean power frequency (MPF) and the level of muscle contraction, and to use those results to discuss the differences in the trends according to factors related to measurement technique and subject. Twenty-one studies with 63 cases for upper limb muscles and nine studies with 31 cases for lower limb muscles were analysed. Most results showed an increase in parameters with an increased level of muscle contraction, only some studies showed a decrease. The influence on parameters of the level of muscle contraction and factors such as subjects, type of contraction, muscle length and electrodes was analysed for each muscle. It was concluded that when analysing the influence of different factors on MF and MPF, because those factors interact they should be considered together, not separately.

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.

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.

The influence of wrist posture on the time and frequency EMG signal measures of forearm muscles

This study investigates how altering wrist posture influences the relationship between the time and frequency measures of the electromyography (EMG) signal of extensor digitorum communis (EDC) and flexor carpi ulnaris (FCU). Thirteen participants exerted handgrip force related to maximum voluntary contraction (MVC) in four tests: 20%MVC and 50%MVC in neutral wrist posture and 20%MVC in full wrist flexion and extension. EMG measurements from EDC and FCU were used to calculate normalized values of amplitude (nRMS) and mean and median frequency of the power spectrum (nMPF, nMF). During muscle shortening (wrist flexion for FCU and wrist extension for EDC) nRMS was approximately twofold higher than in neutral posture for FCU and fourfold for EDC. All measures obtained at 20%MVC in neutral posture were significantly different from 20%MVC in wrist flexion for FCU and 20%MVC in wrist extension for EDC (p<0.05). Differences between 50%MVC and 20%MVC at neutral posture (nRMS) were significant for both muscles, although in nMPF and nMF for EDC only. Muscle shortening changed the pattern of statistical significance when the time and frequency domain measures were compared, whereas muscle lengthening did not. It can be concluded that muscle shortening caused by altering wrist posture influences the relationship between the time and frequency measures in both muscles. This suggests that in studies using EMG in different wrist postures, changes in the relationship between the time and the frequency measures should be considered.

Two-dimensional spatial distribution of surface mechanomyographical response to single motor unit activity

In order to better understand the mechanisms of generation of mechanomyography (MMG) signals, the two-dimensional distribution of surface MMG produced by the activity of single motor units was analyzed by a novel two-dimensional recording method. Motor unit action potentials were identified from intramuscular electromyographic (EMG) signals and used to trigger the averaging of MMG signals detected over the tibialis anterior muscle of 11 volunteers with a grid of 5x3 accelerometers (20-mm inter-accelerometer distance). The intramuscular wires were inserted between the first and second accelerometer in the middle column of the grid, proximal to the innervation zone. The subjects performed three contractions with visual feedback of the intramuscular EMG signals. In each contraction, a new motor unit was recruited at the minimum stable discharge rate (mean+/-S.D., N = 11 subjects, 7.3+/-2.3 pulse/s), resulting in torque of 2.4+/-2.8% of the maximal voluntary contraction (MVC), 4.6+/-2.7% MVC, and 6.3+/-3.1% MVC (all different, P < 0.01). For 23 out of 33 detected motor units, it was possible to extract the motor unit surface acceleration map (MUAM). A negative MUAM peak (-2.7+/-2.2 mm/s2) was detected laterally and a positive MUAM peak (4.1+/-2.4 mm/s2) medially (P < 0.001). The time-to-peak was shorter in the medial part of the muscle (2.9+/-0.4 ms) than in the other locations (3.4+/-0.5 ms, P < 0.001). The double integrated signals (muscle displacement) indicated negative deflection in the lateral part and inflation close to the tibia bone. The maps of acceleration showed spatial dependency in single motor unit MMG activities. The technique provides a new insight into motor unit contractile properties.

Clinical applications of high-density surface EMG: A systematic review

High density-surface EMG (HD-sEMG) is a non-invasive technique to measure electrical muscle activity with multiple (more than two) closely spaced electrodes overlying a restricted area of the skin. Besides temporal activity HD-sEMG also allows spatial EMG activity to be recorded, thus expanding the possibilities to detect new muscle characteristics. Especially muscle fiber conduction velocity (MFCV) measurements and the evaluation of single motor unit (MU) characteristics come into view. This systematic review of the literature evaluates the clinical applications of HD-sEMG. Although beyond the scope of the present review, the search yielded a large number of "non-clinical" papers demonstrating that a considerable amount of work has been done and that significant technical progress has been made concerning the feasibility and optimization of HD-sEMG techniques. Twenty-nine clinical studies and four reviews of clinical applications of HD-sEMG were considered. The clinical studies concerned muscle fatigue, motor neuron diseases (MND), neuropathies, myopathies (mainly in patients with channelopathies), spontaneous muscle activity and MU firing rates. In principle, HD-sEMG allows pathological changes at the MU level to be detected, especially changes in neurogenic disorders and channelopathies. We additionally discuss several bioengineering aspects and future clinical applications of the technique and provide recommendations for further development and implementation of HD-sEMG as a clinical diagnostic tool.