Spectral moments of mechanomyographic signals recorded with accelerometer and microphone during sustained fatiguing contractions

Effects of biofeedback and strength training interventions on neck-shoulder sensory-motor responses among visual display unit users. A narrative review

Workplace biofeedback and strength training interventions have been conducted to treat neck-shoulder pain among visual display unit users. Biofeedback has been given using surface electromyography, mechanomyography, oculometrics, and spinal posture to promote either muscle relaxation, muscle activation or change in posture. Strength training has been performed mostly using basic exercise equipment according to various progression principles. These two types of interventions would thus result in increased ability to cope with physical workload or improved individual resources. In this narrative review, we analyzed the design, methods, and results of the retrieved studies on neck-shoulder sensory-motor responses among visual display unit users. A few studies have reported both an immediate decrease in neck-shoulder pain and an improvement after the end of the intervention following biofeedback, often based on surface electromyography, and strength training interventions targeting the shoulder girdle. Biofeedback and strength training interventions can respectively modify ability to cope with physical workload and individual resources resulting in increased physical capacity among visual display unit users. The long-term effects and the applicability of these approaches remain to be demonstrated at workplace settings. Future studies could combine both modalities to increase versatility of the interventions.

Assessing Quadriceps Muscle Contraction Using a Novel Surface Mechanomyography Sensor during Two Neuromuscular Control Screening Tasks

Electromyography (EMG) is the clinical standard for capturing muscle activation data to gain insight into neuromuscular control, yet challenges surrounding data analysis limit its use during dynamic tasks. Surface mechanomyography (sMMG) sensors are novel wearable devices that measure the physical output of muscle excursion during contraction, which may offer potential easy application to assess neuromuscular control. This study aimed to investigate sMMG detection of the timing patterns of muscle contraction compared to EMG. Fifteen healthy participants (mean age = 31.7 ± 9.1 y; eight males and seven females) were donned with EMG and sMMG sensors on their right quadriceps for simultaneous data capture during bilateral deep squats, and a subset performed three sets of repeated unilateral partial squats. No significant difference in the total duration of contraction was detected by EMG and sMMG during bilateral (p = 0.822) and partial (p = 0.246) squats. sMMG and EMG timing did not differ significantly for eccentric (p = 0.414) and concentric (p = 0.462) phases of muscle contraction during bilateral squats. The sMMG magnitude of quadriceps excursion demonstrated excellent intra-session retest reliability for bilateral (ICC_3,1 = 0.962 mm) and partial (ICC_3,1 = 0.936 mm, n = 10) squats. The sMMG sensors accurately and consistently provided key quadriceps muscle performance metrics during two physical activities commonly used to assess neuromuscular control for injury prevention, rehabilitation, and exercise training.

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.

Crosstalk in Mechanomyographic Signals From Elbow Flexor Muscles During Submaximal to Maximal Isometric Flexion, Pronation, and Supination Torque Tasks

This study analyzed the crosstalk in mechanomyographic (MMG) signals from elbow flexors during isometric muscle actions from 20% to 100% maximum voluntary isometric contraction (MVIC). Twenty-five young, healthy, male participants performed the isometric elbow flexion, forearm pronation, and supination tasks at an elbow joint angle of 90 deg. The MMG signals from the biceps brachii (BB), brachialis (BRA), and brachioradialis (BRD) muscles were recorded using accelerometers. The cross-correlation coefficient was used to quantify the crosstalk in MMG signals, recorded in a direction transverse to muscle fiber axis, among the muscle pairs (P1: BB and BRA, P2: BRA and BRD, and P3: BB and BRD). In addition, the MMG RMS and MPF were quantified. The mean normalized RMS and mean MPF exhibited increasing (r > 0.900) and decreasing (r < -0.900) trends, respectively, with increases in the effort levels in all three tasks. The magnitude of crosstalk ranged from 0.915% to 21.565% in all three muscle pairs. The crosstalk was found to exhibit high positive correlations with submaximal to maximal flexion [P1 (r = 0.970), P2 (r = 0.951), and P3 (r = 0.824)], pronation [P1 (r = 0.811), P2 (r = 0.763), and P3 (r = 0.901)] and supination [P1 (r = 0.898), P2 (r = 0.838), and P3 (r = 0.852)] torque levels (eight out of nine p-values were < 0.05). Regardless of the high positive correlation between crosstalk and level of effort, the crosstalk remained at a low range (0.915-21.565%) with increases in the torque levels.

Segmenting Mechanomyography Measures of Muscle Activity Phases Using Inertial Data

Electromyography (EMG) is the standard technology for monitoring muscle activity in laboratory environments, either using surface electrodes or fine wire electrodes inserted into the muscle. Due to limitations such as cost, complexity, and technical factors, including skin impedance with surface EMG and the invasive nature of fine wire electrodes, EMG is impractical for use outside of a laboratory environment. Mechanomyography (MMG) is an alternative to EMG, which shows promise in pervasive applications. The present study used an exerting squat-based task to induce muscle fatigue. MMG and EMG amplitude and frequency were compared before, during, and after the squatting task. Combining MMG with inertial measurement unit (IMU) data enabled segmentation of muscle activity at specific points: entering, holding, and exiting the squat. Results show MMG measures of muscle activity were similar to EMG in timing, duration, and magnitude during the fatigue task. The size, cost, unobtrusive nature, and usability of the MMG/IMU technology used, paired with the similar results compared to EMG, suggest that such a system could be suitable in uncontrolled natural environments such as within the home.

Mechanomyography responses characterize altered muscle function during electrical stimulation-evoked cycling in individuals with spinal cord injury

BACKGROUND

Investigation of muscle fatigue during functional electrical stimulation (FES)-evoked exercise in individuals with spinal cord injury using dynamometry has limited capability to characterize the fatigue state of individual muscles. Mechanomyography has the potential to represent the state of muscle function at the muscle level. This study sought to investigate surface mechanomyographic responses evoked from quadriceps muscles during FES-cycling, and to quantify its changes between pre- and post-fatiguing conditions in individuals with spinal cord injury.

METHODS

Six individuals with chronic motor-complete spinal cord injury performed 30-min of sustained FES-leg cycling exercise on two days to induce muscle fatigue. Each participant performed maximum FES-evoked isometric knee extensions before and after the 30-min cycling to determine pre- and post- extension peak torque concomitant with mechanomyography changes.

FINDINGS

Similar to extension peak torque, normalized root mean squared (RMS) and mean power frequency (MPF) of the mechanomyography signal significantly differed in muscle activities between pre- and post-FES-cycling for each quadriceps muscle (extension peak torque up to 69%; RMS up to 80%, and MPF up to 19%). Mechanomyographic-RMS showed significant reduction during cycling with acceptable between-days consistency (intra-class correlation coefficients, ICC = 0.51-0.91). The normalized MPF showed a weak association with FES-cycling duration (ICC = 0.08-0.23). During FES-cycling, the mechanomyographic-RMS revealed greater fatigue rate for rectus femoris and greater fatigue resistance for vastus medialis in spinal cord injured individuals.

INTERPRETATION

Mechanomyographic-RMS may be a useful tool for examining real time muscle function of specific muscles during FES-evoked cycling in individuals with spinal cord injury.

System identification of velocity mechanomyogram measured with a capacitor microphone for muscle stiffness estimation

A mechanomyogram (MMG) measured with a displacement sensor (displacement MMG) can provide a better estimation of longitudinal muscle stiffness than that measured with an acceleration sensor (acceleration MMG), but the displacement MMG cannot provide transverse muscle stiffness. We propose a method to estimate both longitudinal and transverse muscle stiffness from a velocity MMG using a system identification technique. The aims of this study are to show the advantages of the proposed method. The velocity MMG was measured using a capacitor microphone and a differential circuit, and the MMG, evoked by electrical stimulation, of the tibialis anterior muscle was measured five times in seven healthy young male volunteers. The evoked MMG system was identified using the singular value decomposition method and was approximated with a fourth-order model, which provides two undamped natural frequencies corresponding to the longitudinal and transverse muscle stiffness. The fluctuation of the undamped natural frequencies estimated from the velocity MMG was significantly smaller than that from the acceleration MMG. There was no significant difference between the fluctuations of the undamped natural frequencies estimated from the velocity MMG and that from the displacement MMG. The proposed method using the velocity MMG is thus more advantageous for muscle stiffness estimation.

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

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

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.

MEASUREMENT AND ESTIMATION OF MUSCLE CONTRACTION STRENGTH USING MECHANOMYOGRAPHY BASED ON ARTIFICIAL NEURAL NETWORK ALGORITHM

Muscle contraction strength estimation using mechanomyographic (MMG) signal is typically calculated by the root mean square (RMS) amplitude. Raw MMG signal is processed by rectification, low-pass filtering, and mapping. In this work, beside RMS amplitude, another significant parameter of MMG signal, i.e. frequency variance (VAR), is introduced and used for constructing an algorithm for estimating the muscle contraction strength. Seven participants produced isometric contractions about the elbow while MMG signal and generated torque (resultant of muscle contraction strength) of biceps brachii were recorded. We found that MMG RMS increased monotonously and VAR decreased under incremental voluntary contractions. Based on these results, a two-layer neural network was utilized for the model of estimating the muscle contraction strength from MMG RMS and VAR. Experimental evaluation was performed under constant posture and sinusoidal contractions at 0.5 Hz, 0.25 Hz, 0.125 Hz, and random frequency. The results of the proposed algorithm and MMG RMS linear mapping were also compared. The proposed algorithm has better accuracy than linear mapping for all contraction frequencies. The mean absolute error decreased 6% for the 0.5Hz contraction, 43% for 0.25 Hz contraction, 52% for 0.125 Hz contraction, and 30% for random frequency contraction.

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.

Correlation between mechanomyography features and passive movements in healthy and paraplegic subjects

Mechanomyography (MMG) measures both muscular contraction and stretching activities and can be used as feedback in the control of neuroprostheses with Functional Electrical Stimulation (FES). In this study we evaluated the correlation between MMG features and passive knee angular movement of rectus femoris and vastus lateralis muscles acquired from healthy volunteers (HV) and spinal cord injured volunteers (SCIV). Twelve HV and thirteen SCIV were submitted to passive and FES elicited knee extensions and in each extension, eleven windows of analysis with 0.5s length were inspected. Temporal (RMS and INT) and frequency (MF and μ3) features were extracted. Spearman correlation coefficients (p) were computed in order to check correlations between the features obtained from both MMG sensors. The correlation between MMG(MF) and MMG temporal analysis (RMS and INT) to HV was classified as positive, moderate (p from 0.635 to 0.681) and high (p from 0.859 to 0.870), and weak (positive e negative) to SCIV. These results differ from those obtained in voluntary contraction or artificially evoked by functional electrical stimulation and may be relevant in applications with closed loop control systems.

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.

Detection of chaos in human fatigue mechanomyogarphy signals

We undertake the study of the chaotic nature of mechanomygraphy (MMG) signal by recourse to the recent developments in the field of nonlinear dynamics. The MMG signals were measured from biceps brachii muscle of 5 subjects during fatigue of isometric contraction at 80% maximal voluntary contraction (MVC) level. Deterministic chaotic character was detected in all data by using the Volterra-Wiener-Korenberg model and noise titration approach. The noise limit (NL), which is a power indicator of chaos of fatigue MMG signals, is 22.2000 + or - 8.7293. Furthermore, we studied the nonlinear dynamic features of MMG signals by computing their correlation dimension D(2), which is 3.3524 + or - 0.3645 across all the subjects. These results indicate that MMG is a high-dimensional chaotic signal and support the use of the theory of nonlinear dynamics for the analysis and modeling the MMG signals.

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.

A comparison between mechanomyographic condenser microphone and accelerometer measurements during submaximal isometric, concentric and eccentric contractions

The aim of this study was to compare mechanomyogram (MMG) recorded by a condenser microphone (MIC) and an accelerometer (ACC) during submaximal isometric, concentric and eccentric contractions in 14 males. The maximal voluntary force (MVC) of the biceps brachii was measured. The subjects were asked to do short duration isometric, concentric and eccentric contraction at 10%, 30%, 50%, 70% MVC twice. For the concentric and eccentric contraction, the subject bent his arm for 3s (concentric) then held it for 3s and extended (eccentric) during 3s. The normalized root mean square (RMS) and mean power frequency (MPF) increased linearly with increased force for both transducers. There was a correlation between MIC MPF and ACC MPF at 10%, 30%, 50% MVC, and between MIC RMS and ACC RMS at 30% MVC during isometric contractions. There was significantly higher MPF for the ACC than for the MIC in concentric and eccentric modes, while the RMS did not differ among transducers in the three contraction modes. The RMS and MPF values coefficient of variations were significantly larger during anisometric contractions compared with isometric contractions and were lower for the accelerometer than for the microphone. The present results obtained during isometric, concentric and eccentric contractions of increased intensity showed that the information contained in microphone- and accelerometer-based MMG signals is different despite similar trends. It can be concluded that at low-moderate movement velocity, concentric contractions can be investigated by means of accelerometer and microphone.

Heterogeneous mechanomyographic absolute activation of paraspinal muscles assessed by a two-dimensional array during short and sustained contractions

Spatial dependency of paraspinal muscle activity was assessed using a new two-dimensional MMG recording system. MMG signals were detected over the left and right paraspinal muscles of 10 volunteers using a grid of 12 accelerometers. During two separate trials subjects maintained a 20 degrees flexed position and held loads that ranged from 0 to 15 kg (in 2.5 kg increments) for 20s; and 7.5 kg for 6 min. Maps of absolute and normalised (with respect to initial values) average rectified value, mean power frequency, variance and skewness of the power spectral density were obtained from the two-dimensional MMG recordings. For both the short duration and sustained contractions, the MMG absolute average rectified value, mean power frequency, variance and skewness depended on accelerometer location (P<0.05), while, with the exception of the skewness (P<0.05), normalised values did not. These results demonstrate both inhomogeneous MMG absolute activity and homogeneous MMG normalised activity in paraspinal muscles for short duration and sustained contractions. Moreover, the effect of accelerometer location on spectral variables confirmed the limited validity of general relationships between MMG spectral changes and motor unit recruitment strategies. This study underlines the importance of using multiple recording sites when assessing back muscle activity.

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.

Spatial and force dependency of mechanomyographic signal features

The aim was to investigate with a novel technique the spatial inhomogeneity in surface mechanomyographic (MMG) response to muscle contraction at varying force levels. MMG signals were detected over the dominant tibialis anterior muscle of 10 volunteers using a 5 x 3 grid of accelerometers. The subjects performed 3 s long isometric contractions at forces ranging from 0% to 100% of the maximal force (10% increment) in a randomised order. From the two-dimensional MMG recordings, maps of absolute and normalized temporal and spectral MMG descriptors were obtained. The centroid and entropy of these maps were computed to describe the spatial centre of activity and degree of homogeneity, respectively. MMG absolute amplitude did not depend on location over the muscle while normalized amplitude did and the centroid shifted with increasing force. Amplitude increased with force and its entropy decreased. Absolute and normalized spectral variables depended on location over the muscle and their centroid shifted with increasing force. In addition, the dependency of absolute and normalized spectral variables on force was affected by location. These results highlight limitations when using single-channel MMG features for the assessment of motor unit control strategies, due to a substantial effect of position on the relation between force and MMG characteristics.