Muscle fatigue during cross country sprint assessed by activation patterns and electromyographic signals time-frequency analysis.

The aims of this study were as follows: (i) analysis of activation patterns during the spurt of two heats of a cross country skiing sprint with the double poling technique and (ii) quantification of muscle fatigue of the investigated muscles. Eight elite skiers were tested and surface electromyographic signals (EMG) were recorded from seven muscles of the upper and lower limbs. For each subject and each muscle, the activation intervals were calculated for relying on a double-threshold statistical detector and the average rectified value was calculated on each activation interval. The detected activations were processed by a time-frequency algorithm in order to assess the progression of muscle fatigue. The EMG activation patterns and EMG amplitude highlighted no significant difference between the two spurts, despite a generally lower speed in the second spurt. The frequency analysis showed that upper body muscles are the first to be affected by fatigue and that clear signs of muscle fatigue appear right from the first spurt of the sprint simulation (i.e., biceps and triceps brachii) with a decrease in the instantaneous mean frequency. Biceps brachii activations and fatigue demonstrated the involvement of this muscle in propulsion.

The Effect of Number of Gait Cycles on Principal Activation Extraction.

To cope with the high intra-subject variability of muscle activation intervals, a large amount of gait cycles is necessary to clearly document physiological or pathological muscle activity patterns during human locomotion. The Clustering for Identification of Muscle Activation Pattern (CIMAP) algorithm has been proposed to help clinicians obtaining a synthetic and clear description of normal and pathological muscle functions in human walking. Moreover, this algorithm allows the extraction of Principal Activations (PAs), defined as those muscle activations that are strictly necessary to perform a specific task and occur in every gait cycle. This contribution aims at assessing the impact of the number of gait cycles on the extraction of the PAs. Results demonstrated no statistically significant differences between PAs extracted considering different numbers of gait cycles, revealing, on average, similarity values higher than 0.88.Clinical Relevance-This contribution demonstrates the potential applicability of the CIMAP algorithm to the analysis of subjects affected by neurological disorders, for whom the assessment of motor functions may be of the uttermost importance and only a reduced number of gait cycles can be acquired.

Muscle synergies for the control of single-limb stance with and without visual information in young individuals.

PURPOSE: Single-limb stance is a demanding postural task featuring a high number of daily living and sporting activities. Thus, it is widely used for training and rehabilitation, as well as for balance assessment. Muscle activations around single joints have been previously described, however, it is not known which are the muscle synergies used to control posture and how they change between conditions of normal and lack of visual information. METHODS: Twenty-two healthy young participants were asked to perform a 30 s single-limb stance task in open-eyes and closed-eyes condition while standing on a force platform with the dominant limb. Muscle synergies were extracted from the electromyographical recordings of 13 muscles of the lower limb, hip, and back. The optimal number of synergies, together with the average recruitment level and balance control strategies were analyzed and compared between the open- and the closed-eyes condition. RESULTS: Four major muscle synergies, two ankle-dominant synergies, one knee-dominant synergy, and one hip/back-dominant synergy were found. No differences between open- and closed-eyes conditions were found for the recruitment level, except for the hip/back synergy, which significantly decreased (p = 0.02) in the closed-eyes compared to the open-eyes condition. A significant increase (p = 0.03) of the ankle balance strategy was found in the closed-eyes compared to the open-eyes condition. CONCLUSION: In healthy young individuals, single-limb stance is featured by four major synergies, both in open- and closed-eyes condition. Future studies should investigate muscle synergies in participants with other age groups, as well as pathological conditions.

How to Improve Robustness in Muscle Synergy Extraction.

The muscle synergy theory was widely used in literature to assess the modular organization of the central nervous system (CNS) during human locomotion. The extraction of muscle synergies may be strongly influenced by the preprocessing techniques applied to surface electromyographic (sEMG) signals. The aim of this contribution is to assess the robustness improvement in muscle synergy extraction obtained using an innovative pre-processing technique with respect to the standard procedure. The new pre-processing technique that we propose is based on the extraction of principal muscle activation intervals (necessary to accomplish a specific biomechanical task during gait) from the original sEMG signals, discarding the secondary muscle activation intervals (activations that occur only in some strides with auxiliary functions). Results suggest that the extraction of the principal activation intervals from sEMG provide a more consistent and stable description of the modular organization of the CNS with respect to the standard pre-processing procedure.

Asymmetry Index in Muscle Activations.

Gait asymmetry is typically evaluated using spatio-temporal or joint kinematics parameters. Only a few studies addressed the problem of defining an asymmetry index directly based on muscle activity, extracting parameters from surface electromyography (sEMG) signals. Moreover, no studies used the extraction of the muscle principal activations (activations that are necessary for accomplishing a specific motor task) as the base to construct an asymmetry index, less affected by the variability of sEMG patterns. The aim of this paper is to define a robust index to quantitatively assess the asymmetry of muscle activations during locomotion, based on the extraction of the principal activations. SEMG signals were analyzed combining statistical gait analysis (SGA) and a clustering algorithm that allows for obtaining the muscle principal activations. We evaluated the asymmetry levels of four lower limb muscles in: (1) healthy subjects of different ages (children, adults, and elderly); (2) different populations of orthopedic patients (adults with megaprosthesis of the knee after bone tumor resection, elderly subjects after total knee arthroplasty, and elderly subjects after total hip arthroplasty); and (3) neurological patients (children with hemiplegic cerebral palsy and elderly subjects affected by idiopathic normal pressure hydrocephalus). The asymmetry index obtained for each pathological population was then compared to that of age-matched controls. We found asymmetry levels consistent with the expected impact of the different pathologies on muscle activation during gait. This suggests that the proposed index can be successfully used in clinics for an objective assessment of the muscle activation asymmetry during locomotion.

Accuracy of the Orientation Estimate Obtained Using Four Sensor Fusion Filters Applied to Recordings of Magneto-Inertial Sensors Moving at Three Rotation Rates.

Magneto-Inertial technology is a well-established alternative to optical motion capture for human motion analysis applications since it allows prolonged monitoring in free-living conditions. Magneto and Inertial Measurement Units (MIMUs) integrate a triaxial accelerometer, a triaxial gyroscope and a triaxial magnetometer in a single and lightweight device. The orientation of the body to which a MIMU is attached can be obtained by combining its sensor readings within a sensor fusion framework. Despite several sensor fusion implementations have been proposed, no well-established conclusion about the accuracy level achievable with MIMUs has been reached yet. The aim of this preliminary study was to perform a direct comparison among four popular sensor fusion algorithms applied to the recordings of MIMUs rotating at three different rotation rates, with the orientation provided by a stereophotogrammetric system used as a reference. A procedure for suboptimal determination of the parameter filter values was also proposed. The findings highlighted that all filters exhibited reasonable accuracy (rms errors <; 6.4°). Moreover, in accordance with previous studies, every algorithm's accuracy worsened as the rotation rate increased. At the highest rotation rate, the algorithm from Sabatini (2011) showed the best performance with errors smaller than 4.1° rms.

Influence of pre-processing in the extraction of muscle synergies during human locomotion.

The extraction of muscle synergies in human locomotion may be biased by the kind of pre-processing applied to electromyographic (EMG) data. The aim of this contribution is to analyze the differences in the muscle synergies extracted using a standard pre-processing procedure and a new procedure. The new procedure is based on the selection of the muscle's principal activations (necessary actuations of the muscle to accomplish its specific biomechanical task during gait), discarding secondary activations (with an auxiliary function in motor control). EMG signals were recorded from 12 muscles of a healthy volunteer who was asked to walk, at self-selected pace, for 5 minutes. A dataset of 193 gait cycles was collected and divided into 19 epochs of 10 concatenated gait cycles. The application of the new pre-processing procedure provided 5 instead of 6 muscle synergies accurately reconstructing the original EMG data matrix, and clearer and more stable neural activation commands. The new preprocessing procedure may be easily extended to the extraction of muscle synergies in other cyclic movements, such as running, stair climbing, cyclo-ergometer exercising, and swimming.

Developing medical device software in compliance with regulations.

In the last decade, the use of information technology (IT) in healthcare has taken a growing role. In fact, the adoption of an increasing number of computer tools has led to several benefits related to the process of patient care and allowed easier access to social and health care resources. At the same time this trend gave rise to new challenges related to the implementation of these new technologies. Software used in healthcare can be classified as medical devices depending on the way they are used and on their functional characteristics. If they are classified as medical devices they must satisfy specific regulations. The aim of this work is to present a software development framework that can allow the production of safe and high quality medical device software and to highlight the correspondence between each software development phase and the appropriate standard and/or regulation.

Inference of motor unit recruitment order in voluntary and electrically elicited contractions.

The relationship between surface myoelectric signal parameters and the level of voluntary or electrically elicited contractions was studied in 32 experiments on the tibialis anterior muscle of 22 healthy human subjects. Contractions were performed at 20 and 80% of the maximum voluntary contraction torque. Two levels of stimulation current were used, yielding, respectively, a maximum M wave and an M wave approximately 30% of the maximum. A four-bar electrode probe was used to detect single- and double-differential signals from which mean and median frequency of the power spectrum and average muscle fiber conduction velocity were estimated. Measurements obtained from voluntary contractions showed a positive correlation between contraction levels and both conduction velocity and spectral parameters. Conduction velocity increased by 21.2 +/- 10.9% when voluntary contraction level increased from 20 to 80% of the maximal value. Spectral parameters increased by similar amounts. Tetanic electrical stimulation was applied to a muscle motor point for 20 s via surface electrodes. Rectangular current pulses with 0.1-ms width and frequencies of 20, 25, 30, 35, and 40 Hz were used. Four types of behavior were observed with increasing stimulation level: 1) the two spectral parameters and conduction velocity both increased with stimulation in 15 experiments, 2) the two spectral parameters decreased and conduction velocity increased in 8 experiments, 3) the two spectral parameters and conduction velocity both decreased in 6 experiments, and 4) the two spectral parameters increased and conduction velocity decreased in 3 experiments. Conduction velocity increased with increasing stimulation current in 72% of the experiments, indicating a recruitment order similar to that of voluntary contractions, although it decreased in the other 28% of the cases, indicating a reverse order of recruitment. Contrary to what is observed in direct stimulation of nerves, motor units are not in general recruited in reverse order of size during electrical stimulation of a muscle motor point. This discrepancy may be the result of geometric factors or a lack of correlation between axonal branch diameter and the diameter of the parent motoneuron axon. Changes of conduction velocity and spectral parameters in opposite directions may be the result of the combined effect of the motor unit recruitment order and of the different tissue filtering function associated with the geometric location of the recruited motor units within the muscle.

Myoelectric manifestations of fatigue in voluntary and electrically elicited contractions.

The time course of muscle fiber conduction velocity and surface myoelectric signal spectral (mean and median frequency of the power spectrum) and amplitude (average rectified and root-mean-square value) parameters was studied in 20 experiments on the tibialis anterior muscle of 10 healthy human subjects during sustained isometric voluntary or electrically elicited contractions. Voluntary contractions at 20% maximal voluntary contraction (MVC) and at 80% MVC with duration of 20 s were performed at the beginning of each experiment. Tetanic electrical stimulation was then applied to the main muscle motor point for 20 s with surface electrodes at five stimulation frequencies (20, 25, 30, 35, and 40 Hz). All subjects showed myoelectric manifestations of muscle fatigue consisting of negative trends of spectral variables and conduction velocity and positive trends of amplitude variables. The main findings of this work are 1) myoelectric signal variables obtained from electrically elicited contractions show fluctuations smaller than those observed in voluntary contractions, 2) spectral variables are more sensitive to fatigue than conduction velocity and the average rectified value is more sensitive to fatigue than the root-mean-square value, 3) conduction velocity is not the only physiological factor affecting spectral variables, and 4) contractions elicited at supramaximal stimulation and frequencies greater than 30 Hz demonstrate myoelectric manifestations of muscle fatigue greater than those observed at 80% MVC sustained for the same time.

Electrically evoked myoelectric signals.

Electrical stimulation of the nervous system is attracting increasing attention because of the possibilities it offers for physiological investigations, clinical diagnosis, muscle function assessment, noninvasive muscle characterization, and functional control of paralyzed extremities. Parameters of the myoelectric signal evoked by surface stimulation of a muscle motor point or by stimulation of a nerve trunk by means of implanted electrodes provide information about muscle performance and properties if the stimulation artifact is properly removed or suppressed. Comparison of these parameters with those obtained during voluntary contractions provides additional insight into muscle physiology. The relationships between myoelectric signal amplitude parameters, spectral parameters, and conduction velocity are discussed with special reference to muscle fatigue. This review focuses on a few methodological aspects concerning electrical stimulation of the peripheral nervous system, detection, and processing of the electrically evoked myoelectric signals in skeletal muscles. The state of the art of the following issues is discussed: (1) properties of voluntary and electrically evoked myoelectric signals; (2) techniques for evoking and detecting myoelectric signals; (3) techniques for suppression of stimulation artifacts; (4) effect of stimulation waveforms and electrode properties; (5) signal processing techniques for electrically evoked myoelectric signals; (6) physiological significance of myoelectric signal variables; (7) order of recruitment of motor units during electrical stimulation; (8) myoelectric manifestations of fatigue in electrically stimulated muscles; (9) assessment of crosstalk by electrical stimulation; and (10) applications in sport, rehabilitation, and geriatric medicine.

A statistical method for the measurement of muscle activation intervals from surface myoelectric signal during gait.

The aim of this work is to present an original double-threshold detector of muscle activation, specifically developed for gait analysis. This detector operates on the raw myoelectric signal and, hence, it does not require any envelope detection. Its performances are fixed by the values of three parameters, namely, false-alarm probability (Pfa), detection probability, and time resolution. Double-threshold detectors are preferable to single-threshold ones because, for a fixed value of the Pfa, they yield higher detection probability; furthermore, they allow the user to select the couple false alarm-detection probability with a higher degree of freedom, thus, adapting the performances of the detector to the characteristics of the myoelectric signal of interest and of the experimental situation. In this paper, first we derive the detection algorithm and describe different strategies for selecting its parameters, then we present the performances of the proposed procedure evaluated by means of computer simulations, and finally we report an example of application to myoelectric signals recorded during gait. The characterization of the proposed double-threshold detector demonstrates that, in most practical situations, the bias of the estimates of the on-off transitions is smaller than 10 ms, the standard deviation may be kept lower than 15 ms, and the percentage of erroneous patterns is below 5%. These results show that this detection approach is satisfactory in research applications as well as in the clinical practice.

On-line estimation of myoelectric signal spectral parameters and nonstationarities detection.

In this communication, we present a method for detecting nonstationarities of random time series with an approximately Gaussian distribution of amplitudes. This method is suitable for real time implementation. Here we report some results obtained by applying them to a time series of spectral parameters of surface myoelectric signals, collected during voluntary isometric contractions of human muscles. Moreover, we describe the computerized system that we used to implement our detector of nonstationarity. This system is based on the TMS 320C25 DSP chip and realizes on-line estimation and display of spectral parameters, as well as detection of their nonstationarities, featuring a sampling frequency up to 20 k samples/s. A friendly user interface, fully menu driven, allows the user to select different options during the system's operation by means of hot keys. The accuracy of the system was tested by comparing its estimates with those of an off-line system, previously characterized, which we took as a reference. The estimates of spectral parameters obtained by means of the two systems were always consistent. The on-line stationarity detector was able to recognize rates of variation of the spectral parameters as small as 1%/s during contractions lasting 10-15 s. This sensitivity makes it suitable for clinical application. The set of results herein presented has been selected to highlight the main characteristics of the system.

Time-frequency parameters of the surface myoelectric signal for assessing muscle fatigue during cyclic dynamic contractions.

The time-dependent shift in the spectral content of the surface myoelectric signal to lower frequencies has proven to be a useful tool for assessing localized muscle fatigue. Unfortunately, the technique has been restricted to constant-force, isometric contractions because of limitations in the processing methods used to obtain spectral estimates. A novel approach is proposed for calculating spectral parameters from the surface myoelectric signal during cyclic dynamic contractions. The procedure was developed using Cohen class time-frequency transforms to define the instantaneous median and mean frequency during cyclic dynamic contractions. Changes in muscle length, force, and electrode position contribute to the nonstationarity of the surface myoelectric signal. These factors, unrelated to localized fatigue, can be constrained and isolated for cyclic dynamic contractions, where they are assumed to be constant for identical phases of each cycle. Estimation errors for the instantaneous median and mean frequency are calculated from synthesized signals. It is shown that the instantaneous median frequency is affected by an error slightly lower than that related to the instantaneous mean frequency. In addition, we present a sample application to surface myoelectric signals recorded from the first dorsal interosseous muscle during repetitive abduction/adduction of the index finger against resistance. Results indicate that the variability of the instantaneous median frequency is related to the repeatability of the biomechanics of the exercise.

Time-frequency methods applied to muscle fatigue assessment during dynamic contractions.

This paper discusses the assessment of the electrical manifestations of muscle fatigue during dynamic contractions. In the past, the study of muscle fatigue was restricted to isometric constant force contractions because, in this contraction paradigm, the myoelectric signal may be considered as wide sense stationary over epochs lasting up to two or three seconds, and hence classic spectral estimation techniques may be applied. Recently, the availability of spectral estimation techniques specifically designed for nonstationary signal analysis made it possible to extend the employment of muscle fatigue assessment to cyclic dynamic contractions, thus increasing noticeably its possible clinical applications. After presenting the basics of time-frequency distributions, we introduce instantaneous spectral parameters well suited to tracking spectral changes due to muscle fatigue, discuss the issues of quasi-stationarity and quasi-cyclostationarity, and present different strategies of signal analysis to be utilized with cyclic dynamic contractions. We present preliminary results obtained by analyzing data collected from paraspinal muscles during repetitive lift movements, from the first dorsal interosseus during abduction-adduction movements of the index finger, and from knee flexors and extensors during isokinetic exercise. In conclusion, data herein reported demonstrate that the described techniques allow for evidencing the electrical manifestations of muscle fatigue in different paradigms of cyclic dynamic contractions. We believe that the extension of the objective assessment of the electrical manifestations of muscle fatigue from static to dynamic contractions may increase considerably the interest of researchers and clinicians and open new application fields, as ergonomics and sports medicine.

EMG assessment of back muscle function during cyclical lifting.

A new approach to estimating the frequency compression of the surface EMG signal during cyclical dynamic exercise is described. The basic properties of the method are first developed using simulated EMG signals. Spectral compression is measured by defining the instantaneous median frequency from time-frequency representations of the signal derived from a transformation of the Cohen class. The technique is then used to process real EMG signals from paraspinal muscles during repetitive lifting. Our purpose was to use this new procedure to identify (a) whether changes in the instantaneous median frequency among concurrently active paraspinal muscles during repetitive trunk extension produces a 'fatigue pattern' that is indicative of normal functioning, and (b) whether this pattern is different when the subject produces a sustained isometric trunk extension. Four healthy subjects (26 +/- 4 years; 3 males, 1 female) were tested in both a Back Analysis System, for the production of a sustained static isometric contraction, and a LIDO-Lift Controller (Loredan), for repetitive lifting and lowering of a weighted box. EMG signals were recorded concurrently from six bilateral lumbar paraspinal regions during these tasks. The results demonstrate that static and dynamic tasks result in very different patterns of EMG spectral changes, suggestive of differences in load-sharing and underlying metabolic fatigue processes. Unlike the linear decrease in median frequency observed for static contractions, during dynamic contractions instantaneous median frequency behavior is non-linear and more complex. Examples are provided in which distinct periods of instantaneous median frequency decay are followed by periods of recovery during a single trial of repetitive lifting. It is hypothesized that this difference reflects a complex strategy of utilizing muscle load-sharing during strenuous dynamic exercise to provide periods of metabolic recovery that limit localized fatigue. New analysis procedures to characterize this complex behavior are needed to enhance the technique for assessment of impairment in patients with lower back pain.

Automatic classification of time-frequency plots applied to the center-of-pressure rotational components.

Time-frequency plots are widely applied to the non-stationary analysis of signals. These plots may be difficult to interpret, particularly when large data sets have to be considered. The aim of this work is to propose an automatic procedure of feature selection and clustering to be applied to time-frequency plots. We focus on the application of this procedure to plots obtained from a non-stationary analysis of the center-of-pressure signals acquired in upright bipedal stance. From a data set of 168 time-frequency plots we obtained 5 different clusters, each characterized by a few distinctive features. We were able to interpret the results of the clustering relating them to the physiological mechanisms underlying postural sway.

Rotary spectra analysis applied to static stabilometry.

Static stabilometry is a technique aimed at quantifying postural sway during quiet standing in the upright position. Many different models and many different techniques to analyze the trajectories of the Centre of Pressure (CoP) have been proposed. Most of the parameters calculated according to these different approaches are affected by a relevant intra- and inter-subject variability or do not have a clear physiological interpretation. In this study we hypothesize that CoP trajectories have rotational characteristics, therefore we decompose them in clockwise and counter-clockwise components, using the rotary spectra analysis. Rotary spectra obtained studying a population of healthy subjects are described through the group average of spectral parameters, i.e., 95% spectral bandwidth, mean frequency, median frequency, and skewness. Results are reported for the clockwise and the counter-clockwise components and refer to the upright position maintained with eyes open or closed. This study demonstrates that the approach is feasible and that some of the spectral parameters are statistically different between the open and closed eyes conditions. More research is needed to demonstrate the clinical applicability of this approach, but results so far obtained are promising.

Normative EMG activation patterns of school-age children during gait.

Gait analysis is widely used in clinics to study walking abnormalities for surgery planning, definition of rehabilitation protocols, and objective evaluation of clinical outcomes. Surface electromyography allows the study of muscle activity non-invasively and the evaluation of the timing of muscle activation during movement. The aim of this study was to present a normative dataset of muscle activation patterns obtained from a large number of strides in a population of 100 healthy children aged 6-11 years. The activity of Tibialis Anterior, Lateral head of Gastrocnemius, Vastus Medialis, Rectus Femoris and Lateral Hamstrings on both lower limbs was analyzed during a 2.5-min walk at free speed. More than 120 consecutive strides were analyzed for each child, resulting in approximately 28,000 strides. Onset and offset instants were reported for each observed muscle. The analysis of a high number of strides for each participant allowed us to obtain the most recurrent patterns of activation during gait, demonstrating that a subject uses a specific muscle with different activation modalities even in the same walk. The knowledge of the various activation patterns and of their statistics will be of help in clinical gait analysis and will serve as reference in the design of future gait studies.