Muscle activation and coactivation during five-time-sit-to-stand movement in patients undergoing total knee arthroplasty

Quadriceps weakness is prevalent with knee osteoarthritis (OA) and after total knee arthroplasty (TKA). To compensate for quadriceps dysfunction, patients often alter movement strategies. Little is known about muscle coordination during sit-to-stand (concentric) and stand-to-sit (eccentric) movements in the acute postoperative period. This investigation characterized the distribution of muscle activation between the concentric and eccentric phases during a five-time-sit-to-stand (FTSTS) movement in late stage OA and one month after TKA. Patients and healthy participants performed a FTSTS while recording bilateral ground reaction forces (GRFs) and electromyography (EMG). Concentric and eccentric ensemble averages of the GRF and EMG were calculated for the concentric and eccentric phases. Coactivation indices, integrated EMG, and GRF were calculated for each limb and phase. Patients demonstrated higher eccentric coactivation than the healthy group. Postoperative loading was higher in the nonsurgical limb. Postoperative quadriceps activity was lower in the concentric phase and higher in the eccentric phase than the healthy group. Higher coactivation in the patients resulted from sustained distribution of quadriceps activity throughout the eccentric phase. This indicated an inability to coordinate muscle firing when rapidly lowering to a chair and occurred despite unloading of the surgical limb. Although these patterns may serve as a protective strategy, they may also impede recovery of muscle function after TKA.     

Child-Adult differences in antagonist muscle coactivation: A systematic review

Antagonist coactivation is the simultaneous activation of agonist and antagonist muscles during a motor task. Age-related changes in coactivation may contribute to observed differences in muscle performance between children and adults. Our aim was to systematically summarize age-related differences in antagonist muscle coactivation during multi-joint dynamic and single-joint isometric and isokinetic contractions. Electronic databases were searched for peer-reviewed studies comparing coactivation in upper or lower extremity muscles between healthy children and adolescents/young adults. Of the 1083 studies initially identified, 25 met eligibility criteria. Thirteen studies examined multi-joint dynamic movements, 10 single-joint isometric contractions, and 2 single-joint isokinetic contractions. Of the studies investigating multi-joint dynamic contractions, 83% (11/13 studies) reported at least one significant age-related difference: In 84% (9/11 studies) coactivation was higher in children, whereas 16% (2/11 studies) reported higher coactivation in adults. Among single-joint contractions, only 25% (3/12 studies) reported significantly higher coactivation in children. Fifty six percent of studies examined females, with no clear sex-related differences. Child-adult differences in coactivation appear to be more prevalent during multi-joint dynamic contractions, where generally, coactivation is higher in children. When examining child–adult differences in muscle function, it is important to consider potential age-related differences in coactivation, specifically during multi-joint dynamic contractions.     

<Superscript>1</Superscript>H-NMR metabonomics analysis of sera differentiates between mammary tumor-bearing mice and healthy controls

Global analysis of ¹H-NMR spectra of serum is an appealing approach for the rapid detection of cancer. To evaluate the usefulness of this method in distinguishing between mammary tumor-bearing mice and healthy controls, we conducted ¹H-NMR metabonomic analyses on serum samples obtained from the following: 10 mice inoculated with a highly-metastatic mammary carcinoma cell line, 10 mice inoculated with a “normally” metastatic mammary carcinoma cell line, and 10 healthy controls. Following standard spectral processing and subsequent data reduction, we applied unsupervised Principal Component Analysis (PCA) to determine if unique metabolic fingerprints for different categories of metastatic breast cancer in serum exist. The PCA method correctly separated sera of tumor-bearing mice from that of normal healthy controls, as shown using the scores plot which indicated that sera classes from tumor-bearing mice did not share multivariate space with that from healthy controls. In addition, this technique was capable of distinguishing between classes of varying metastatic ability in this system. Metabolites apparently responsible for separation between diseased and healthy mice include lactate, taurine, choline, and sugar moieties. Results of this study suggest that ¹H-NMR spectra of mouse serum analyzed using PCA statistical methods indicate separation of tumor-bearing mice from healthy normal controls, justifying further study of the use of ¹H-NMR metabonomics for cancer detection using serum.     

Alternative approach to modal gait analysis through the Karhunen-Loève decomposition: An application in the sagittal plane

This article uses the Karhunen-Loève decomposition (KL) technique, also known as proper orthogonal decomposition (POD) or principal component analysis (PCA), to introduce the concept of gait mode, which can be used as a tool to identify gait differences among subjects or groups and to approximate gait curves. The KL is a statistical pattern analysis technique for finding dominant structures in an ensemble of data. This technique can be used to decompose a spatiotemporal signal into time-independent, orthogonal, spatial components and time-dependent amplitudes. This study demonstrates the existence of a common gait mode through the analysis of the kinematics of 57 young, healthy subjects, and how they can be used to identify different walking patterns, for instance differentiating male and female subjects.     

Revealing cryptic spatial patterns in genetic variability by a new multivariate method

Increasing attention is being devoted to taking landscape information into account in genetic studies. Among landscape variables, space is often considered as one of the most important. To reveal spatial patterns, a statistical method should be spatially explicit, that is, it should directly take spatial information into account as a component of the adjusted model or of the optimized criterion. In this paper we propose a new spatially explicit multivariate method, spatial principal component analysis (sPCA), to investigate the spatial pattern of genetic variability using allelic frequency data of individuals or populations. This analysis does not require data to meet Hardy-Weinberg expectations or linkage equilibrium to exist between loci. The sPCA yields scores summarizing both the genetic variability and the spatial structure among individuals (or populations). Global structures (patches, clines and intermediates) are disentangled from local ones (strong genetic differences between neighbors) and from random noise. Two statistical tests are proposed to detect the existence of both types of patterns. As an illustration, the results of principal component analysis (PCA) and sPCA are compared using simulated datasets and real georeferenced microsatellite data of Scandinavian brown bear individuals (Ursus arctos). sPCA performed better than PCA to reveal spatial genetic patterns. The proposed methodology is implemented in the adegenet package of the free software R.     

Low back muscle action potential conduction velocity estimated using high-density electromyography

While a decreasing spectral content of surface electromyography reflects low back muscle fatigue development, reliability of these decreases may be insufficient. Decreasing frequency content is largely determined by decreasing average motor unit action potential conduction velocities (CV), which is considered a more direct measure of muscle fatigue development. However, for the low back muscles it has been proven difficult to identify propagating potentials and consequently estimate the CV. The aim of this study was to estimate the low back muscle CV from high-density multi-channel electromyography by using peak-delay and cross-correlation methods. Fourteen healthy male participants without a history of low-back pain performed a 30 degrees lumbar flexion trial until exhaustion while standing. For 10 out of the 14 participants (118 out of 560 sites) realistic CV estimates were obtained using both methods, the majority likely over the iliocostalis lumborum muscle. Between-method CV differences appeared to be small. Close to the spine a considerable number of sites (79) yielded systematically overestimated low back muscle CV values. Estimating low back muscle CV may allow additional insight into low back muscle fatigue development and potentially improve its monitoring using (high-density) surface electromyography.     

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.     

Influence of electrode type on neuromuscular activation patterns during walking in healthy subjects

The role of muscle activation in both pathological and spastic populations is of interest for understanding central nervous system function. Muscle activation patterns may provide insight into pathological changes compared to healthy controls. To gain a better understanding of surgical interventions, gait muscle activation patterns are studied before and after surgery. Previous studies using surface electromyography have indicated that muscle activation onset, time to peak, and peak amplitude may be helpful in assessing the neuromuscular control strategy that underlies pathological populations. Geometric artifact may influence electromyographic variables as recorded by different electrode types and electrode placement. The purpose of this investigation was to compare surface and fine-wire activation patterns during gait to elucidate the influence electrode type has on electromyographic variables. Lower leg surface and fine-wire electromyographic activity was recorded simultaneously during gait to assess if electrode type (fine-wire vs. surface) affects muscle onset, time to peak, peak amplitude, and activation patterns. No significant differences were recorded between surface and fine-wire electrodes for muscle onset or time to peak activation. Activation patterns revealed similarity between electrodes. Some significant differences were detected in peak amplitude. Non-invasive surface electrodes provide an adequate representation of timing variables for primary ankle muscles during gait.     

Kinematic,kinetic and electromyographic differences between young adults with and without chronic ankle instability during walking

The objective of this study was to quantify the kinematic, kinetic and electromyography differences between individuals with and without chronic ankle instability (CAI) during comfortable (CW) and fast (FW) walking. Twenty-one individuals with CAI and 21 healthy controls were recruited to walk at CW and FW speeds. The dependent variables were gluteus medius, vastus lateralis, gastrocnemius lateralis, gastrocnemius medialis, peroneus longus and tibialis anterior muscles mean activity, ankle and knee angles and moments. Kinematic, kinetic and electromyography variables were compared between groups with a one-dimensional statistical non-parametric mapping analysis. The CAI group exhibited no significant difference for ankle angles and moments compared to the control group. However, the CAI group showed less external knee rotation from 56 to 100% (CW) and 51 to 98% (FW) and more knee abduction moment from 1 to 6% and 7 to 9% (CW) and 1 to 2% (FW) of the stance phase. Less gluteus medius muscle activity was also observed from 6 to 9% and 99 to 100% (CW) of the stance phase for the CAI group. These results suggest proximal biomechanical compensations and will help better understand the underlying deficits associated with CAI. They also indicate that regardless of walking speeds, individuals with CAI exhibit similar differences compared to healthy participants.     

Subspace projection approaches to classification and visualization of neural network-level encoding patterns

Recent advances in large-scale ensemble recordings allow monitoring of activity patterns of several hundreds of neurons in freely behaving animals. The emergence of such high-dimensional datasets poses challenges for the identification and analysis of dynamical network patterns. While several types of multivariate statistical methods have been used for integrating responses from multiple neurons, their effectiveness in pattern classification and predictive power has not been compared in a direct and systematic manner. Here we systematically employed a series of projection methods, such as Multiple Discriminant Analysis (MDA), Principal Components Analysis (PCA) and Artificial Neural Networks (ANN), and compared them with non-projection multivariate statistical methods such as Multivariate Gaussian Distributions (MGD). Our analyses of hippocampal data recorded during episodic memory events and cortical data simulated during face perception or arm movements illustrate how low-dimensional encoding subspaces can reveal the existence of network-level ensemble representations. We show how the use of regularization methods can prevent these statistical methods from over-fitting of training data sets when the trial numbers are much smaller than the number of recorded units. Moreover, we investigated the extent to which the computations implemented by the projection methods reflect the underlying hierarchical properties of the neural populations. Based on their ability to extract the essential features for pattern classification, we conclude that the typical performance ranking of these methods on under-sampled neural data of large dimension is MDA>PCA>ANN>MGD.     

Patterns of trunk muscle activation during walking and pole walking using statistical non-parametric mapping

This study used surface electromyography (EMG) to investigate the regions and patterns of activity of the external oblique (EO), erector spinae longissimus (ES), multifidus (MU) and rectus abdominis (RA) muscles during walking (W) and pole walking (PW) performed at different speeds and grades. Eighteen healthy adults undertook W and PW on a motorized treadmill at 60% and 100% of their walk-to-run preferred transition speed at 0% and 7% treadmill grade. The Teager-Kaiser energy operator was employed to improve the muscle activity detection and statistical non-parametric mapping based on paired t-tests was used to highlight statistical differences in the EMG patterns corresponding to different trials. The activation amplitude of all trunk muscles increased at high speed, while no differences were recorded at 7% treadmill grade. ES and MU appeared to support the upper body at the heel-strike during both W and PW, with the latter resulting in elevated recruitment of EO and RA as required to control for the longer stride and the push of the pole. Accordingly, the greater activity of the abdominal muscles and the comparable intervention of the spine extensors supports the use of poles by walkers seeking higher engagement of the lower trunk region.     

Electromyographic patterns of individuals suffering from lateral tennis elbow.

This study investigated the applicability of using surface electromyography (EMG) as a tool for differentiating between persons suffering from lateral tennis elbow and the healthy age-matched adults. Temporal muscle activation patterns of the tennis elbow group were evaluated to determine if they varied between subject groups and if noted variations might be interpreted as arresting or exacerbating the injury. Sixteen subjects (Healthy Controls, n = 6; Tennis Elbow, n = 10) were tested under simulated tennis playing conditions. All subjects were males (Healthy group (CON) 38.8 +/- 13.1, Injured group (INJ) 40.8 +/- 10.8 yrs). EMG response data, temporal and spatial muscle activities, of the forearm extensors (Ext), the forearm flexors (Flex) and the triceps (Tri) were recorded for each subject during a single test session using all combinations of three different velocities on three different racket head impact locations. Data were collected at a frequency of 1000 Hz. Statistical analysis was performed using a 2 x 3 x 3 (Health status x Impact velocity x Impact location) ANOVA with repeated measures. Results indicated statistically significant differences (p < 0.05) between the CON and INJ subject groups for the response variables associated with forearm extensor muscle activation. During simulated play, the INJ group employed an earlier, longer, and greater activation of Ext than the CON group, such changes may be considered detrimental to the healing process. These results support the use of surface EMG to quantify differences in muscle activation strategies employed by individuals suffering from soft tissue muscle microtrauma injuries and healthy controls.     

Detection of individual motor units of the puborectalis muscle by non-invasive EMG electrode arrays

PURPOSE: The purpose of the study was to demonstrate that anatomical features of individual motor units of the puborectalis muscle can be detected with non-invasive electromyography (EMG) and to evaluate differences in electrophysiological properties of the puborectalis muscles in a small group of healthy and pathologic subjects. METHODS: Multichannel EMG was recorded by means of a flexible probe applied on the gloved index finger and carrying an array of eight equally spaced (1.15 mm) electrodes. A multichannel EMG amplifier provided seven outputs corresponding to the pairs of adjacent electrodes. Tests were performed in three different positions (dorsal, left and right) over the puborectalis muscle on 20 subjects (nine healthy, seven constipated and four incontinent patients). Motor unit action potentials (MUAPs) generated at the innervation zone of a MU and propagating along the muscle fibers generated repetitive characteristic patterns on the seven output channels allowing identification of anatomical features of the motor units. RESULTS: MUAPs were observed travelling in either one or both directions with the array in dorsal position, and mainly in ventral-to-dorsal direction in either lateral position. MUAP amplitude was lower in constipated and incontinent patients with respect to healthy subjects. The conduction velocity estimated on the identified MUAPs was lower for constipated patients with respect to healthy subjects suggesting different mechanical properties of the active motor units. CONCLUSIONS: This technique allows the extraction of relevant information about the anatomical features (innervation zone position and overlapping of motor unit branches) of the puborectalis muscle and its electrophysiological properties and maybe can be applied as an novel methodology for assessing the anorectal function in patients.     

A metabolomics approach to characterise and identify various Mycobacterium species

We investigated the potential use of gas chromatography mass spectrometry (GC-MS), in combination with multivariate statistical data processing, to build a model for the classification of various tuberculosis (TB) causing, and non-TB Mycobacterium species, on the basis of their characteristic metabolite profiles. A modified Bligh-Dyer extraction procedure was used to extract lipid components from Mycobacterium tuberculosis, Mycobacterium avium, Mycobacterium bovis, and Mycobacterium kansasii cultures. Principle component analyses (PCA) of the GC-MS generated data showed a clear differentiation between all the Mycobacterium species tested. Subsequently, the 12 compounds best describing the variation between the sample groups were identified as potential metabolite markers, using PCA and partial least-squares discriminant analysis (PLS-DA). These metabolite markers were then used to build a discriminant classification model based on Bayes' theorem, in conjunction with multivariate kernel density estimation. This model subsequently correctly classified 2 "unknown" samples for each of the Mycobacterium species analysed, with probabilities ranging from 72 to 100%. Furthermore, Mycobacterium species classification could be achieved in less than 16 h, and the detection limit for this approach was 1×10(3)bacteriamL(-1). This study proves the capacity of a GC-MS, metabolomics pattern recognition approach for its possible use in TB diagnostics and disease characterisation.     

High day-to-day repeatability of lower extremity muscle activation patterns and joint biomechanics of dual-belt treadmill gait: A reliability study in healthy young adults

PurposeThe reliability of lower extremity muscle activation patterns has not been clearly studied in a dual-belt instrumented treadmill environment. The primary study objective was to quantify the day-to-day reliability of quadriceps, hamstrings, gastrocnemius and gluteus medius activation patterns in healthy young adult gait. Secondarily, the reliability of spatiotemporal, and knee/hip motion and moment-based gait outcomes was assessed.Scope: 20 young adults were recruited and tested on two separate days. Using standardized procedures, participants were prepared for surface electromyography and lower extremity motion capture. All individuals walked on a dual-belt instrumented treadmill while muscle activation, segment motions and ground reaction forces were recorded. Sagittal plane motion and net external sagittal and frontal plane moments were calculated. Discrete biomechanical and muscle activation measures were calculated, and non-negative matrix factorization extracted amplitude and temporal muscle activation features. Intraclass Correlation Coefficients, Standard Error of Measurement and Minimum Detectable Change were calculated.ConclusionsHigh to excellent Intraclass correlation coefficients were found between visits for most primary and secondary outcomes. The absolute and relative reliability, including Minimum Detectable Change values, provided in this study support the use of dual-belt instrumented treadmill walking as an acceptable medium to collect biomechanical and lower extremity EMG outcomes for future studies.     

An innovative application of the "flexible" GRID/PCA computational method: study of differences in selectivity between PGAs from Escherichia coli and a Providentia rettgeri mutant

The original GRID/PCA technique was adapted for the development of a tool potentially useful for the plan of a research strategy in rational enzyme design. The use of the MOVE directive of GRID made it possible to partially take into account protein flexibility, and the multivariate analysis was used as an instrument for focusing only on relevant information related to the differences in enzyme substrate selectivities. The comparison of two different penicillin G acylases, from Escherichia coli and from Providentia rettgeri, was used as a case study; these enzymes are very similar and their reported selectivities differ only for a couple of mutations around the active site. The "flexible" GRID/PCA method was able to correctly predict the observed selectivity differences caused not only by mutations of residues of the active site but also by long range effects on substrate selectivity due to sequence mutations on residues not directly involved in substrate recognition.     

Bivariate and multivariate growth allometry: statistical and biological considerations

Bivariate and multivariate analyses of 55 cranial dimensions were completed on ontogenetic series of Pygmy chimpanzees ( Pan paniscus ), Common chimpanzees ( Pan troglodytes ), and gorillas ( Gorilla gorilla ). Subanalyses described here were specifically designed to compare and crosscheck quantitative assessments of relative growth as determined using the bivariate and multivariate (principal components analysis—PCA) approaches. Results indicate a strong concordance between the bivariate and multivariate patterns, empirically supporting the claim that PCA provides an effective multivariate approach to analysing growth allometry. Comparison of bivariate and multivariate results also suggests that in multi-group PCA, the first component summarizes shape variation resulting from the sharing and extension of common patterns of growth allometry, while the second and subsequent components summarize shape variation resulting from divergent growth trajectories, reflected in bivariate comparisons as either vertical shifts and/or slope differences. Examination of non-normalized first component loadings, plus a comparison with estimates of logarithmic growth in the cranial dimensions, reveals that the non-normalized loadings are proportional to coefficients of specific growth. This finding further links the bivariate and multivariate approaches, grounding both in Huxley's theoretical notions of multiplicative and relative growth.     

Identifying tasks to elicit maximum voluntary contraction in the muscles of the forearm

Maximum voluntary contractions (MVCs) are often used for the normalisation of electromyography data to enable comparison of signal patterns within and between study participants. Recommendations regarding the types of tasks that are needed to collect MVCs for the muscles of the forearm have been made, specifically advocating the use of resisted moment tasks to get better estimates of forearm MVCs. However, a protocol detailing which specific tasks to employ has yet to be published. Furthermore, the effects of limb dominance on the collection of MVCs have not been considered previously. Muscle activity was monitored while 23 participants performed nine isometric, resisted tasks. The tasks that are likely to elicit MVC in the flexor carpi ulnaris, flexor carpi radialis, flexor digitorum superficialis, extensor carpi ulnaris, extensor carpi radialis, extensor digitorum communis, and pronator teres were identified. Thus, targeted protocols can be designed to mitigate against fatigue. Hand dominance had limited effect, with differences being found only in the finger flexors and extensors (p< 0.03). Thus, use of the contralateral flexor digitorum superficialis and extensor digitorum communis muscles to obtain baselines for activation levels and patterns may not be appropriate.