Associations between the masticatory system and muscle activity of other body districts. A meta-analysis of surface electromyography studies

The aim of this meta-analysis regarding the use of surface electromyography (sEMG) is to assess the scientific evidence for detectable correlations between the masticatory system and muscle activity of the other body districts, particularly those mainly responsible for body posture. A literature survey was performed using the PubMed database, covering the period from January 1966 to April 2011, and choosing medical subject headings. After selection, five articles qualified for the final analysis. One study article was judged to be of medium quality, the remaining four of low quality. No study included a control group or follow-up; in only one study, subjects with impairment of the masticatory system were enrolled. In all studies, detectable correlations between the masticatory systems and muscle activity of the other body districts, or vice versa, were found; however, after a reappraisal of the data provided in these studies, only weak correlations were found, which reached biological, but not clinical relevance. With the limitations that arise from the poor methodological quality of the published study reports discussed here, the conclusion is that a correlation between the masticatory system and muscle activity of the other body districts might be detected through sEMG under experimental conditions; however, this correlation has little clinical relevance. While more investigations with improved levels of scientific evidence are needed, the current evidence does not support clinically relevant correlations between the masticatory system and the muscle activity of other body districts, including those responsible for body posture.     

A surface electromyography based objective method to identify patients with nonspecific chronic low back pain,presenting a flexion related movement control impairment

Movement control impairments (MCI) are often present in patients with non-specific chronic low back pain (NS-CLBP). Therefore, movement control exercises are widely used to rehabilitate patients. However, the objective assessment remains difficult.The purpose of this study was to develop a statistical model, based on logistic regression analysis, to differentiate patients with NS-CLBP presenting a flexion-related MCI from healthy subjects. This model is based on trunk muscle activation patterns measured by surface electromyography (sEMG), during movement control exercises.Sixty-three healthy male subjects and 36 male patients with a flexion-related MCI participated in this study. Muscle activity of the internal obliques, the external obliques, the lumbar multifidus and the thoracic part of the iliocostalis was registered. Ratios of deep stabilizing to superficial torque producing muscle activity were calculated to examine trunk muscle recruitment patterns during 6 different exercises. Logistic regression analyses were performed (1) to define the ratios and exercises that were most discriminating between patients and non-patients, (2) to make a predictive model. K-Fold cross-validation was used to assess the performance of the predictive model.This study demonstrated that sEMG trunk muscle recruitment patterns during movement control tests, allows differentiating NSCLBP patients with a flexion-related MCI from healthy subjects.     

Discrete wavelet transform analysis of surface electromyography for the fatigue assessment of neck and shoulder muscles

Assessment of neuromuscular fatigue is essential for early detection and prevention of risks associated with work-related musculoskeletal disorders. In recent years, discrete wavelet transform (DWT) of surface electromyography (SEMG) has been used to evaluate muscle fatigue, especially during dynamic contractions when the SEMG signal is non-stationary. However, its application to the assessment of work-related neck and shoulder muscle fatigue is not well established. Therefore, the purpose of this study was to establish DWT analysis as a suitable method to conduct quantitative assessment of neck and shoulder muscle fatigue under dynamic repetitive conditions. Ten human participants performed 40 min of fatiguing repetitive arm and neck exertions while SEMG data from the upper trapezius and sternocleidomastoid muscles were recorded. The ten of the most commonly used wavelet functions were used to conduct the DWT analysis. Spectral changes estimated using power of wavelet coefficients in the 12–23 Hz frequency band showed the highest sensitivity to fatigue induced by the dynamic repetitive exertions. Although most of the wavelet functions tested in this study reasonably demonstrated the expected power trend with fatigue development and recovery, the overall performance of the “Rbio3.1” wavelet in terms of power estimation and statistical significance was better than the remaining nine wavelets.     

A new surface electromyography analysis method to determine spread of muscle fiber conduction velocities.

Muscle fiber conduction velocity (MFCV) estimation from surface signals is widely used to study muscle function, e.g., in neuromuscular disease and in fatigue studies. However, most analysis methods do not yield information about the velocity distribution of the various motor unit action potentials. We have developed a new method-the interpeak latency method (IPL)-to calculate both the mean MFCV and the spread of conduction velocities in vivo, from bipolar surface electromyogram (sEMG) during isometric contractions. sEMG was analyzed in the biceps brachii muscle in 15 young male volunteers. The motor unit action potential peaks are automatically detected with a computer program. Associated peaks are used to calculate a mean MFCV and the SD. The SD is taken as a measure of the MFCV spread. The main finding is that the IPL method can derive a measure of MFCV spread at different contraction levels. In conclusion, the IPL method provides accurate values for the MFCV and additionally gives information about the scatter of conduction velocities.     

Motion analysis of leg joints associated with escape turns of the cockroach,Periplaneta americana

Considerable information is now available on the neural organization of the escape system of the American cockroach. To relate these data to the behavior, we need detailed information on the movements made at the principle leg joints that produce the turn. We used motion analysis of high speed video records to acquire such information. Records from both free ranging and tethered animals were analyzed. 1. We analyzed individual joint movements using a tethered preparation. Stimuli from 4 different angles around the animal were used. For all wind angles, the femur-tibia (FT) joint on the mesothoracic leg that is ipsilateral to the wind source extended while the contralateral mesothoracic FT joint flexed. This moved both of these legs laterally toward the wind source. In freely moving animals the FT movements provide forces that turn the animal away from the wind source. 2. The ipsilateral mesothoracic coxa-femur (CF) joint extended for all wind angles. The contralateral mesothoracic CF joint extended in response to most winds from the rear, but switched to flexion in response to wind from the side and front. As a result of these joint movements, rear wind resulted in rearward movements of the contralateral mesothoracic leg, while side and front wind resulted in more forward movements of that leg. 3. The CF and FT joints for both ipsilateral and contralateral metathoracic legs extended to wind from the rear and switched to flexion as the wind was placed at more anterior positions around the animal. In freely moving animals, extension of these joints would push the animal forward. Flexion would pull the animal backward. 4. Several of the joints showed correlations between rate of movement and initial joint angle. That is, joints that were already flexed at the onset of stimulation tended to move at a faster rate to a final position than joints that started at a more extended position. 5. Metathoracic FT and CF joints showed a high degree of positive correlation during the escape movements. Indeed, many curves showing movement of metathoracic FT and CF joints with time were virtually identical.     

Fractal dimension analysis and mathematical morphology of structural changes in actin filaments imaged by electron microscopy

In this work, we examined structural changes of actin filaments interacting with myosin visualized by quick freeze deep-etch replica electron microscopy (EM) by using a new method of image processing/analysis based on mathematical morphology.In order to quantify the degree of structural changes, two characteristic patterns were extracted from the EM images. One is the winding pattern of the filament shape (WP) reflecting flexibility of the filament, and the other is the surface pattern of the filament (SP) reflecting intra-molecular domain-mobility of actin monomers constituting the filament. EM images were processed by morphological filtering followed by box-counting to calculate the fractal dimensions for WP (D_WP) and SP (D_SP). The result indicates that D_WP was larger than D_SP irrespective of the state of the filament (myosin-free or bound) and that both parameters for myosin-bound filaments were significantly larger than those for myosin-free filaments. Overall, this work provides the first quantitative insight into how conformational disorder of actin monomers is correlated with the myosin-induced increase in flexibility of actin filaments along their length as suggested by earlier studies with different techniques. Our method is yet to be improved in details, but promising as a powerful tool for studying the structural change of protein molecules and their assemblies, which can potentially be applied to a wide range of biological and biomedical images.     

Fractal analysis of plant spatial patterns: a monitoring tool for vegetation transition shifts

Spatial heterogeneity, like species diversity, is an important ecosystem property. We examine the effects of land use on the diversity and spatial distribution of plants in five semi-arid communities of eastern Spain using non-linear methods to assess the spatialtemporal dynamics of plant populations. Specifically, we are interested in detecting long-term structural changes or drift in an ecosystem before it is too late to prevent irreversible degradation. Fractal analysis is used to characterize the complexity of plant spatial patterns and Information Theory indices are used to measure change in information flow with land use changes and soil substrate. We found that grazing favored diversity and heterogeneity of species distribution on the impoverished gypsum and saline substrate community, as opposed to the detrimental effect of grazing in the Alpha steppe community. Indeed, old-field succession after 30 years of abandonment showed a recovery of species diversity but not the spatial structure of the vegetation. Further, Information Fractal Dimension, representing the unpredictability of plant spatial patterns in the landscape, increased as we moved from a highly diverse to a less diverse community, revealing the change to a more scattered and homogeneous spatial plant distribution. The Information Fractal Dimension is a good estimator of ecosystem disturbance, independent of scale, and thus can be used to monitor ecosystem dynamics.     

A distance-based dynamical transition analysis of time series signals and application to biological systems

This study demonstrates an application of distance-based numerical measures to the phase space of time series signals, in order to obtain a temporal analysis of complex dynamical systems. This method is capable of detecting alterations appearing in the characters of the deterministic dynamical systems and provides a simple tool for the real-time analysis of time series data obtained from a complex dynamical system even with black box functionality. The study presents a possible application of the method in the dynamical transition analysis of real EEG records from epilepsy patients.     

The effect of local skin cooling before a sustained,submaximal isometric contraction on fatigue and isometric quadriceps femoris performance: A randomized controlled trial

The central- and peripheral mechanisms by which heat strain limits physical performance are not fully elucidated. Nevertheless, pre-cooling is often used in an attempt to improve subsequent performance. This study compared the effects of pre-cooling vs. a pre-thermoneutral application on central- and peripheral fatigue during 60% of isometric maximum voluntary contraction (MVC) of the right quadriceps femoris muscle. Furthermore, the effects between a pre-cooling and a pre-thermoneutral application on isometric MVC of the right quadriceps femoris muscle and subjective ratings of perceived exertion (RPE) were investigated. In this randomized controlled trial, 18 healthy adults voluntarily participated. The participants received either a cold (experimental) application (+8 °C) or a thermoneutral (control) application (+32 °C) for 20 min on their right thigh (one cuff). After the application, central (fractal dimension – FD) and peripheral (muscle fiber conduction velocity – CV) fatigue was estimated using sEMG parameters during 60% of isometric MVC. Surface EMG signals were detected from the vastus medialis and lateralis using bidimensional arrays. Immediately after the submaximal contraction, isometric MVC and RPE were assessed. Participants receiving the cold application were able to maintain a 60% isometric MVC significantly longer when compared to the thermoneutral group (mean time: 78 vs. 46 s; p=0.04). The thermoneutral application had no significant impact on central fatigue (p>0.05) compared to the cold application (p=0.03). However, signs of peripheral fatigue were significantly higher in the cold group compared to the thermoneutral group (p=0.008). Pre-cooling had no effect on isometric MVC of the right quadriceps muscle and ratings of perceived exertion. Pre-cooling attenuated central fatigue and led to significantly longer submaximal contraction times compared to the pre-thermoneutral application. These findings support the use of pre-cooling procedures prior to submaximal exercises of the quadriceps muscle compared to pre-thermoneutral applications.     

A method for microbial cell surface fingerprinting based on surface plasmon resonance

A method for microbial cell surface fingerprinting using surface plasmon resonance (SPR) is suggested. Four different Escherichia coli mutants have been used as model cells. Cell surface fingerprints were generated by registration of the interaction between the cell mutants and four different surfaces, with different physical and chemical properties, when a cell suspension was flown over the surface. Significant differences in fingerprint pattern between some of the mutants were observed. At the same time, the physical properties of the cell surfaces were determined using microelectrophoresis, contact angle measurements and aqueous two-phase partitioning and compared to the SPR fingerprints. The generated cell surface fingerprints and the physical property data were evaluated with multivariate data analysis that showed that the cells were separated into individual groups in a similar way using principal component analysis plots (PCA).     

Intramolecular masking of nuclear localization signals: analysis of importin binding using a novel AlphaScreen-based method

Active nuclear import of proteins requires the recognition of a nuclear localization sequence (NLS) by members of the importin (IMP) family of proteins. We have developed a modified AlphaScreen-based assay able to estimate the solution binding affinities of such interactions using biotinylated IMPs and His6-tagged NLS-containing proteins. We describe this assay in detail as well as its application in documenting the phenomenon of intramolecular masking of NLSs using recombinant green fluorescent protein (GFP) fusion proteins containing sequences from the SV40 large tumor T antigen (T-ag). We also use it to examine, for the first time, IMP binding to the cancer cell-specific proapoptotic factor viral protein 3 (VP3) from the chicken anemia virus (CAV). High-affinity binding of the IMPalpha/beta heterodimer to the T-ag NLS was observed when the GFP tag was fused to its N terminus but not to its C terminus. Effects of flanking residues were also observed in GFP-T-ag fusion derivatives containing the Thr128 NLS-inactivating mutation, whereby the absence of flanking sequences N terminal to the T-ag NLS appeared to decrease the specificity of the mutation in terms of oblating IMPalpha/beta binding. IMPbeta, but not IMPalpha or the IMPalpha/beta heterodimer, was found to bind to CAV VP3 with high affinity. Interestingly, GFP-VP3(74-121) bound to IMPbeta with threefold higher affinity than the full-length protein, GFP-VP3(1-121), implying that the NLS is masked to a significant extent in the context of full-length protein. This may represent a regulatory mechanism to control nuclear import in a tumor cell-specific fashion.     

Distributed moment histogram: A neurophysiology based method of agonist and antagonist trunk muscle activity prediction

A neurocortical-based technique of muscle recruitment is presented to solve the muscle indeterminacy problem for lumbar torso modeling. Cortical recordings from behaving primates have established motor cortex cells that respond to a wide range of task directions, but are tuned to a preferred direction. A characteristic activity pattern of these neurons seems to be associated with effort direction. It was hypothesized that a model which recruits muscles based on a similar distribution would predict antagonistic muscle activity with greater realism than a widely referenced optimization formulation. The predictions of the Distributed Moment Histogram (DMH) method were evaluated under common speed (<30^os⁻¹) sagittal plane lifting conditions using five subjects. The predicted forces showed high correspondence with agonist and antagonist myoelectric patterns. The mean coefficient of determination for the erector spinae was r²=0.91, and 0.41 for the latissimus. For the antagonistic muscles, the rectus abdominus was found to be electrically silent (<3% MVC) and no activity was predicted by the method. The external oblique muscle was observed to be minimally active (<16% MVC), and the DMH method predicted its mostly constant activity with a mean standard error of 1.6% MVC. The realistic antagonistic predictions supported the hypothesis and justify this cortical based technique as an alternative for muscle tension estimation in biomechanical torso modeling. A primary advantage of this method is its computational simplicity and direct physiologic analogy     

A motion analysis marker-based method of determining centre of pressure during two-legged hopping

The fixed position of force plates has led researchers to pursue alternative methods of determining centre of pressure (CoP) location. To date, errors reported using alternative methods to the force plate during dynamic tasks have been high. The aim of this study was to investigate the accuracy of a motion analysis marker-based system to determine CoP during a two-legged hopping task. Five markers were attached to the left and right feet of eight healthy adults (5 females, 3 males, age: 25.0±2.8 years, height: 1.75±0.07 m, mass: 71.3±11.3 kg). Multivariate forward stepwise and forced entry linear regression was used with data from five participants to determine CoP position during quiet standing and hopping at various frequencies. Maximum standard error of the estimate of CoP position was 12 mm in the anteroposterior direction and 8 mm in the mediolateral. Cross-validation was performed using the remaining 3 participants. Maximum root mean square difference between the force plate and marker method was 14 mm for mediolateral CoP and 20 mm for anteroposterior CoP during 1.5 Hz hopping. Differences reduced to a maximum of 7 mm (mediolateral) and 14 mm (anteroposterior) for the other frequencies. The smallest difference in calculated sagittal plane ankle moment and timing of maximum moment was during 3.0 Hz hopping, and largest at 1.5 Hz. Results indicate the marker-based method of determining CoP may be a suitable alternative to a force plate to determine CoP position during a two-legged hopping task at frequencies greater than 1.5 Hz.     

Heterogeneity of muscle activation in relation to force direction: A multi-channel surface electromyography study on the triceps surae muscle

Several skeletal muscles can be divided into sub-modules, called neuromuscular compartments (NMCs), which are thought to be controlled independently and to have distinct biomechanical functions. We looked for distinct muscle activation patterns in the triceps surae muscle (TS) using surface electromyography (EMG) during voluntary contraction. Nine subjects performed isometric and isotonic plantar flexions combined with forces along pre-defined directions. Besides the forces under the ball of the foot, multi-channel surface EMG was measured with electrodes homogeneously distributed over the entire TS. Using principal component analysis, common (global) components were omitted from the EMG signals, thereby estimating muscle activity sufficiently accurate to track fine fluctuations of force during an isotonic contraction (r = 0.80 ± 0.09). A subsequent cluster analysis showed a topographical organization of co-activated parts of the muscle that was different between subjects. Low and negative correlations between the EMG activity within clusters were found, indicating a substantial heterogeneity of TS activation. The correlations between cluster time series and forces at the foot in specific directions differed substantially between clusters, showing that the differentially activated parts of the TS had specific biomechanical functions.     

Dynalets: A new method for modelling and compressing biological signals. Applications to physiological and molecular signals

The biological information coming from electrophysiologic sensors like ECG, pulse sensor or from molecular signal devices like NMR spectrometry has to be visualized and manipulated in a compressed way for an efficient medical use by clinicians, if stored in scientific data bases or in personalized patient records repositories. Here, we define a new transform called Dynalet based on Liénard ordinary differential equations susceptible to model the mechanism at the source of the studied signal, and we propose to apply this new technique first to the modelling and compression of real biological periodic signals like ECG and pulse rhythm. We consider that the cardiovascular activity results from the summation of cellular oscillators located in the cardiac sinus node and we show that, as a result, the van der Pol oscillator (a particular Liénard system) fits well the ECG signal and the pulse signal. The reconstruction of the original signal (pulse or ECG) using Dynalet transform is then compared with that of Fourier, counting the number of parameters to be set for obtaining an expected signal-to-noise ratio. Then, we apply the Dynalet transform to the modelling and compression of molecular spectra obtained by protein NMR spectroscopy. The reconstruction of the original signal (peak) using Dynalet transform is again compared with that of Fourier. After reconstructing visually the peak, we propose to periodize the signal and give it to hear, the whole process being called the protein “stethoscope”.     

A Bayesian change-point analysis of electromyographic data: detecting muscle activation patterns and associated applications

Many facets of neuromuscular activation patterns and control can be assessed via electromyography and are important for understanding the control of locomotion. After spinal cord injury, muscle activation patterns can affect locomotor recovery. We present a novel application of reversible jump Markov chain Monte Carlo simulation to estimate activation patterns from electromyographic data. We assume the data to be a zero-mean, heteroscedastic process. The variance is explicitly modeled using a step function. The number and location of points of discontinuity, or change-points, in the step function, the inter-change-point variances, and the overall mean are jointly modeled along with the mean and variance from baseline data. The number of change-points is considered a nuisance parameter and is integrated out of the posterior distribution. Whereas current methods of detecting activation patterns are deterministic or provide only point estimates, ours provides distributional estimates of muscle activation. These estimates, in turn, are used to estimate physiologically relevant quantities such as muscle coactivity, total integrated energy, and average burst duration and to draw valid statistical inferences about these quantities.     

Feasibility of using combined EMG and kinematic signals for prosthesis control: A simulation study using a virtual reality environment

Transhumeral amputation has a significant effect on a person’s independence and quality of life. Myoelectric prostheses have the potential to restore upper limb function, however their use is currently limited due to lack of intuitive and natural control of multiple degrees of freedom. The goal of this study was to evaluate a novel transhumeral prosthesis controller that uses a combination of kinematic and electromyographic (EMG) signals recorded from the person’s proximal humerus. Specifically, we trained a time-delayed artificial neural network to predict elbow flexion/extension and forearm pronation/supination from six proximal EMG signals, and humeral angular velocity and linear acceleration. We evaluated this scheme with ten able-bodied subjects offline, as well as in a target-reaching task presented in an immersive virtual reality environment. The offline training had a target of 4° for flexion/extension and 8° for pronation/supination, which it easily exceeded (2.7° and 5.5° respectively). During online testing, all subjects completed the target-reaching task with path efficiency of 78% and minimal overshoot (1.5%). Thus, combining kinematic and muscle activity signals from the proximal humerus can provide adequate prosthesis control, and testing in a virtual reality environment can provide meaningful data on controller performance.     

Evaluation of self-similar features in time series of serum growth hormone and prolactin levels by fractal analysis: Effect of delayed sleep and complexity of diurnal variation

We assayed the diurnal concentrations of growth hormone (GH) and prolactin (PRL) in 6 healthy male volunteers to evaluate the self-similar features in the time series of each hormone on the basis of fractal theory and to determine the fractal dimension as an index of the complexity of the diurnal variation. In addition, we assessed the effects of a 6-hour delay in the sleep period on the complexity of the diurnal variaton of these hormones. There was a statistically significant fractal feature in the serum levels of GH both under the nocturnal-sleep and delayed-sleep conditions in all subjects. The time series of the serum PRL concentrations also showed a statistically significant fractal feature under the nocturnal-sleep and delayed-sleep conditions in all subjects. The fractal dimensions of the patterns of the GH or PRL levels were 1.879 and 1.929 or 1.754 and 1.785 under the nocturnal-sleep and delayed-sleep conditions, respectively. Two-way ANOVA revealed no significant difference in the fractal dimension between the two sleep conditions but did reveal a significant difference between the fractal dimensions of the GH and PRL levels. These results showed (1) that delayed sleep had no significant effect on the complexity of the diurnal pattern of these hormones, and (2) that the diurnal pattern of the GH levels was more complex than that of the PRL levels.