Experimentally verified model of mechanomyograms recorded during single motor unit contractions

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.

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.

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.

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.

Evidence towards improved estimation of respiratory muscle effort from diaphragm mechanomyographic signals with cardiac vibration interference using sample entropy with fixed tolerance values

The analysis of amplitude parameters of the diaphragm mechanomyographic (MMGdi) signal is a non-invasive technique to assess respiratory muscle effort and to detect and quantify the severity of respiratory muscle weakness. The amplitude of the MMGdi signal is usually evaluated using the average rectified value or the root mean square of the signal. However, these estimations are greatly affected by the presence of cardiac vibration or mechanocardiographic (MCG) noise. In this study, we present a method for improving the estimation of the respiratory muscle effort from MMGdi signals that is robust to the presence of MCG. This method is based on the calculation of the sample entropy using fixed tolerance values (fSampEn), that is, with tolerance values that are not normalized by the local standard deviation of the window analyzed. The behavior of the fSampEn parameter was tested in synthesized mechanomyographic signals, with different ratios between the amplitude of the MCG and clean mechanomyographic components. As an example of application of this technique, the use of fSampEn was explored also in recorded MMGdi signals, with different inspiratory loads. The results with both synthetic and recorded signals indicate that the entropy parameter is less affected by the MCG noise, especially at low signal-to-noise ratios. Therefore, we believe that the proposed fSampEn parameter could improve estimates of respiratory muscle effort from MMGdi signals with the presence of MCG interference.

Extra-torque of human tibialis anterior during electrical stimulation with linearly varying frequency and amplitude trains

This work aimed to characterise the whole human muscle input/output law during electrical stimulation with triangular varying frequency and amplitude trains through combined analysis of torque, mechanomyogram (MMG) and electromyogram (EMG). The tibialis anterior (TA) of ten subjects (age 23-35 years) was investigated during static contraction obtained through neuromuscular electrical stimulation. After potentiation, TA underwent two 15s stimulation patterns: (a) frequency triangle (FT): 2 > 35 > 2 Hz at Vmax (amplitude providing full motor unit recruitment); (b) amplitude triangle (AT): Vmin > Vmax > Vmin (Vmin providing TA least mechanical response) at 35 Hz. 2 > 35 Hz or Vmin > Vmax as well as 35 > 2 Hz or Vmax > Vmin were defined as up-going ramp (UGR) and down-going ramp (DGR), respectively. TA torque, MMG and EMG were detected by a load cell, an optical laser distance sensor and a probe with two silver bar electrodes, respectively. For both FT and AT, only the two mechanical signals resulted always larger in DGR than in UGR, during AT extra-torque and extra-MMG were present even in the first 1/3 of the amplitude range where EMG data presented no significant differences between DGR and UGR. Our data suggest that extra-torque and extra-displacement are evident for both FT and AT, being mainly attributed to an intrinsic muscle property.

System identification of evoked mechanomyogram from abductor pollicis brevis muscle in isometric contraction

The purpose of this study is to verify the applicability of a sixth-order model to the mechanomyogram (MMG) system of the parallel-fibered muscle, which was identified from the MMG of the pennation muscle. The median nerve was stimulated, and an MMG and torque of the abductor pollicis brevis muscle were measured. The MMGs were detected with either a capacitor microphone or an acceleration sensor. The transfer functions between stimulation and the MMG and between stimulation and torque were identified by the singular value decomposition method. The torque and the MMG, which were detected with a capacitor microphone, DMMG, were approximated with a second- and a third-order model, respectively. The natural frequency of the torque, reflecting longitudinal mechanical characteristics, did not show a significant difference from that of the DMMG. The MMG detected with an acceleration sensor was approximated with a fourth-order model. The natural frequencies of the AMMG reflecting the muscle and subcutaneous tissue in the transverse direction were obtained. Both DMMG and AMMG have to be measured to investigate the model of the MMG system for parallel-fibered muscle. The MMG system of parallel-fibered muscle was also modeled with a sixth-order model.

The image of motor units architecture in the mechanomyographic signal during the single motor unit contraction: in vivo and simulation study

The mechanomyographic (MMG) signal analysis has been performed during single motor unit (MU) contractions of the rat medial gastrocnemius muscle. The MMG has been recorded as a muscle surface displacement by using a laser distance sensor. The profiles of the MMG signal let to categorize these signals for particular MUs into three classes. Class MMG-P (positive) comprises MUs with the MMG signal similar to the force signal profile, where the distance between the muscle surface and the laser sensor increases with the force increase. The class MMG-N (negative) has also the MMG profile similar to the force profile, however the MMG is inverted in comparison to the force signal and the distance measured by using laser sensor decreases with the force increase. The third class MMG-M (mixed) characterize the MMG which initially increases with the force increases and when the force exceeds some level it starts to decrease towards the negative values. The semi-pennate muscle model has been proposed, enabling estimation of the MMG generated by a single MU depending on its localization. The analysis have shown that in the semi-pennate muscle the localization of the MU and the relative position of the laser distance sensor determine the MMG profile and amplitude. Thus, proposed classification of the MMG recordings is not related to the physiological types of MUs, but only to the MU localization and mentioned sensor position. When the distance sensor is located over the middle of the muscle belly, a part of the muscle fibers have endings near the location of the sensor beam. For the MU MMG of class MMG-N the deflection of the muscle surface proximal to the sensor mainly influences the MMG recording, whereas for the MU MMG class MMG-P, it is mainly the distal muscle surface deformation. For the MU MMG of MMG-M type the effects of deformation within the proximal and distal muscle surfaces overlap. The model has been verified with experimental recordings, and its responses are consistent and adequate in comparison to the experimental data.

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.

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

The purpose of this review is to examine the literature that has investigated the potential relationship between mechanomyographic (MMG) frequency and motor unit firing rates. Several different experimental designs/methodologies have been used to address this issue, including: repetitive electrical stimulation, voluntary muscle actions in muscles with different fiber type compositions, fatiguing and non-fatiguing isometric or dynamic muscle actions, and voluntary muscle actions in young versus elderly subjects and healthy individuals versus subjects with a neuromuscular disease(s). Generally speaking, the results from these investigations have suggested that MMG frequency is related to the rate of motor unit activation and the contractile properties (contraction and relaxation times) of the muscle fibers. Other studies, however, have reported that MMG mean power frequency (MPF) does not always follow the expected pattern of firing rate modulation (e.g. motor unit firing rates generally increase with torque during isometric muscle actions, but MMG MPF may remain stable or even decrease). In addition, there are several factors that may affect the frequency content of the MMG signal during a voluntary muscle action (i.e. muscle stiffness, intramuscular fluid pressure, etc.), independent of changes in motor unit firing rates. Despite the potential influences of these factors, most of the evidence has suggested that the frequency domain of the MMG signal contains some information regarding motor unit firing rates. It is likely, however, that this information is qualitative, rather than quantitative in nature, and reflects the global motor unit firing rate, rather than the firing rates of a particular group of motor units.