The effects of four time-varying factors on the mean frequency of a myoelectric signal.

Daily activities involve dynamic muscle contractions that yield nonstationary myoelectric signals (MESs). The purpose of this work was to determine the individual effects of four time-varying factors (the number and firing rate of active motor units, muscle force and joint angle) on the mean frequency of a MES. Previous theoretical and experimental work revealed that although changes in the number and firing rate of active motor units contribute to the nonstationarities of the signal, they do not significantly affect the mean frequency. In the experimental work, 12 subjects performed 25 static contractions, one for each force (20, 30, 40, 50 and 60% of maximum voluntary contraction) and elbow joint angle (50, 70, 90, 110 and 130 degrees extension) combination. A MES was recorded from the surface of the biceps brachii during each contraction. The results indicated that muscle force only weakly affects the mean frequency. Also shown was that alteration in muscle geometry resulting from changes in elbow joint angle does significantly affect the mean frequency. Knowing this is important for the assessment of muscle fatigue during dynamic contractions.     

肌肉动态收缩期间表面肌电信号的时频分析

介绍了用于肌肉动态收缩期间非平稳表面肌电信号的时频分析方法。用短时傅里叶变换、Wigner-Ville分布及Choi-Williams分布计算了表面肌电信号的时频分布,用于信号频率内容随时间演化的可视化观察。通过计算瞬时频谱参数,对肌肉疲劳的电表现进行量化描述。分析了反复性的膝关节弯曲和伸展运动期间从股外侧肌所记录的表面肌电信号。发现和在静态收缩过程中观察到的平均频率线性下降不同,在动态收缩期间瞬时平均频率的变化过程是非线性的并且更为复杂,且与运动的生物力学条件有关。研究表明将时频分析技术应用于动态收缩期间的表面肌电信号可以增加用传统的频谱分析技术不能得到的信息。     

Automatic detection of surface EMG activation timing using a wavelet transform based method

The problem of the identification of the muscle contraction timing by using surface electromyographic signal is addressed. The timing detection of the muscular activation in dynamic conditions has a real clinical diagnostic impact. Widely used single threshold methods still rely on the experience of the operator in manually setting that threshold. A new approach to detect the muscular activation intervals, that is based on discontinuities detection in the wavelet domain, is proposed. Accuracy and precision of the algorithm were assessed by using a set of simulated signals obtaining values lower than 11.0 and 8.7 ms for biases and standard deviations of the estimation, respectively. Moreover an experimental application of the algorithm was carried out recruiting a population of 10 able-bodied subjects and processing the myoelectric signals recorded from the lower limb during an isokinetic exercise. The algorithm was able to reveal correctly the timing of muscular activation with performance comparable to the state-of-the-art methods. The detection algorithm is automatic and user-independent, it manages the detection of both onset and offset activation, it can be fruitfully applied even in presence of noise and, therefore, it can be used also by unskilled operators.     

Geometrical factors in surface EMG of the vastus medialis and lateralis muscles.

Surface EMG signals detected in dynamic conditions are affected by a number of artefacts. Among them geometrical factors play an important role. During movement the muscle slides with respect to the skin because of the variation of its length. Such a shift can considerably modify sEMG amplitude. The purpose of this work is to assess geometrical artefacts on sEMG during isometric contractions at different muscle lengths.The average rectified value (ARV) of 15 single differential signals was obtained by means of a linear array of 16 bar electrodes from the vastus medialis and lateralis muscles. The knee angle was changed from 75 degrees to 165 degrees in steps of 30 degrees and voluntary isometric contractions at a low, medium and high force level were performed for each angle. The ARV pattern was normalized with respect to the mean activity to compare signals from different joint angles. From the data collected it was possible to separate the geometrical changes from the changes due to different intensities of activation.In three out of five subjects, we found (within the resolution of our measures) a 1 cm shift for the vastus medialis muscle while no shift was observed for the other two subjects. For the vastus lateralis muscle a 1 cm shift was found in two out of four subjects. Such a shift produces the main contribution to geometrical artefacts. To avoid such artefacts the innervation zones should be located and the EMG electrodes should not be placed near them.     

An estimation of the influence of force decrease on the mean power spectral frequency shift of the EMG during repetitive maximum dynamic knee extensions.

Frequency analysis of myoelectric (ME) signals, using the mean power spectral frequency (MNF), has been widely used to characterize peripheral muscle fatigue during isometric contractions assuming constant force. However, during repetitive isokinetic contractions performed with maximum effort, output (force or torque) will decrease markedly during the initial 40-60 contractions, followed by a phase with little or no change. MNF shows a similar pattern. In situations where there exist a significant relationship between MNF and output, part of the decrease in MNF may per se be related to the decrease in force during dynamic contractions. This study estimated force effects on the MNF shifts during repetitive dynamic knee extensions. Twenty healthy volunteers participated in the study and both surface ME signals (from the right vastus lateralis, vastus medialis, and rectus femoris muscles) and the biomechanical signals (force, position, and velocity) of an isokinetic dynamometer were measured. Two tests were performed: (i) 100 repetitive maximum isokinetic contractions of the right knee extensors, and (ii) five gradually increasing static knee extensions before and after (i). The corresponding ME signal time-frequency representations were calculated using the continuous wavelet transform. Compensation of the MNF variables of the repetitive contractions was performed with respect to the individual MNF-force relation based on an average of five gradually increasing contractions. Whether or not compensation was necessary was based on the shape of the MNF-force relationship. A significant compensation of the MNF was found for the repetitive isokinetic contractions. In conclusion, when investigating maximum dynamic contractions, decreases in MNF can be due to mechanisms similar to those found during sustained static contractions (force-independent component of fatigue) and in some subjects due to a direct effect of the change in force (force-dependent component of fatigue). In order to compare MNF shifts during sustained static and repetitive dynamic contractions it is necessary to estimate the force-dependent component of fatigue of dynamic contractions. Our results are preliminary and have to be confirmed in larger experiments using single dynamic contractions when determining the MNF-force relationship of the unfatigued situation.     

Non-invasive detection of the single motor unit action potential by averaging the spatial potential distribution triggered on a spatially filtered motor unit action potential.

For research as well as diagnostic applications the non-invasive detection of the activity of single motor units is of interest. The most direct information is expected to be found in monopolarly recorded data. But when an array of surface electrodes is used for the monopolar recordings of the potential distribution on the skin, in most cases an additional invasive needle electrode is utilized to detect the exact points in time when a certain motor unit is firing. With this supplementary information, an averaging of the monopolar EMG tracings can be performed. In this paper, a completely non-invasive methodology is presented which replaces the invasive needle by a spatial filtering procedure. The EMG signals from the m. biceps brachii are recorded monopolarly with an electrode array. Afterwards, a spatial filtering procedure, called normal double differentiating filter, is applied to the data. The EMG signals obtained are investigated by means of an amplitude threshold to distinguish the activity of different motor units. The point of the maximum amplitude of the selected peaks then is used as trigger point to average the monopolar EMG data. The time courses of the motor unit action potential signals found after applying the described procedure show similar shapes, while two different components are to be identified: corresponding to the spread of the excitation, one is referring to stationary, the other to travelling events. These results justify the possibility to replace the needle electrode to obtain a trigger event in the future by the non-invasive spatial filtering procedure.     

Multi-channel surface EMG classification using support vector machines and signal-based wavelet optimization

The study proposes a method for supervised classification of multi-channel surface electromyographic signals with the aim of controlling myoelectric prostheses. The representation space is based on the discrete wavelet transform (DWT) of each recorded EMG signal using unconstrained parameterization of the mother wavelet. The classification is performed with a support vector machine (SVM) approach in a multi-channel representation space. The mother wavelet is optimized with the criterion of minimum classification error, as estimated from the learning signal set. The method was applied to the classification of six hand movements with recording of the surface EMG from eight locations over the forearm. Misclassification rate in six subjects using the eight channels was (mean ± S.D.) 4.7 ± 3.7% with the proposed approach while it was 11.1 ± 10.0% without wavelet optimization (Daubechies wavelet). The DWT and SVM can be implemented with fast algorithms, thus, the method is suitable for real-time implementation.     

Reference signal extraction from corrupted ECG using wavelet decomposition for MRI sequence triggering: application to small animals

Background  

Present developments in Nuclear Magnetic Resonance (NMR) imaging techniques strive for improved spatial and temporal resolution performances. However, trying to achieve the shortest gradient rising time with high intensity gradients has its drawbacks: It generates high amplitude noises that get superimposed on the simultaneously recorded electrophysiological signals, needed to synchronize moving organ images. Consequently, new strategies have to be developed for processing these collected signals during Magnetic Resonance Imaging (MRI) examinations. The aim of this work is to extract an efficient reference signal, from an electrocardiogram (ECG) that was contaminated by the NMR artefacts. This may be used for image triggering and/or cardiac rhythm monitoring.     

The amplitude distribution of surface EMG in static and intermittent static muscular performance.

A measure of the variation of load on individual muscles or parts of muscles may be obtained by estimating the amplitude probability distribution function (APDF) of the myoelectric signal. In a study of elbow flexor muscular performance in static and intermittent static low level muscular contractions, the APDF was computed from the surface EMG obtained from the belly of the brachial biceps muscle. The APDF was also computed from the simultaneously recorded force signal. The APDF of the myoelectric signal and of the force signal were similar, indicating that the APDF of the myoelectric signal closely reflects the muscular load in non-fatiguing muscular contractions. The effect of the time constant in lowpass filtering when processing the surface EMG-signals was also studied. A suitable time constant appears to be in the range of 50-100 ms.     

Adaptive filtering for ECG rejection from surface EMG recordings.

Surface electromyograms (EMG) of back muscles are often corrupted by electrocardiogram (ECG) signals. This noise in the EMG signals does not allow to appreciate correctly the spectral content of the EMG signals and to follow its evolution during, for example, a fatigue process. Several methods have been proposed to reject the ECG noise from EMG recordings, but seldom taking into account the eventual changes in ECG characteristics during the experiment. In this paper we propose an adaptive filtering algorithm specifically developed for the rejection of the electrocardiogram corrupting surface electromyograms (SEMG). The first step of the study was to choose the ECG electrode position in order to record the ECG with a shape similar to that found in the noised SEMGs. Then, the efficiency of different algorithms were tested on 28 erector spinae SEMG recordings. The best algorithm belongs to the fast recursive least square family (FRLS). More precisely, the best results were obtained with the simplified formulation of a FRLS algorithm. As an application of the adaptive filtering, the paper compares the evolutions of spectral parameters of noised or denoised (after adaptive filtering) surface EMGs recorded on erector spinae muscles during a trunk extension. The fatigue test was analyzed on 16 EMG recordings. After adaptive filtering, mean initial values of energy and of mean power frequency (MPF) were significantly lower and higher respectively. The differences corresponded to the removal of the ECG components. Furthermore, classical fatigue criteria (increase in energy and decrease in MPF values over time during the fatigue test) were better observed on the denoised EMGs. The mean values of the slopes of the energy-time and MPF-time linear relationships differed significantly when established before and after adaptive filtering. These results account for the efficacy of the adaptive filtering method proposed here to denoise electrophysiological signals.     

Application of wavelet coherence to the detection of uterine electrical activity synchronization in labor

This paper introduces the use of a method based on wavelet transform to detect the correlation between two uterine electrical activity bursts, recorded at different places on the pregnant abdomen during the same uterine contraction. The method used in this work is called wavelet coherence. The results of this study show that the wavelet analysis can successfully detect and quantify the temporal and spectral interactions between uterine bursts of electrical activity. They also indicate that the coherence is higher in the lower frequencies of the uterine electromyogram signal (EHG), and that it is possible to apply the method to non-segmented uterine signals. We find the method to give promising results permitting to evidence the coherence present in EHGs during a uterine contraction.     

基于小波包熵的运动意识任务分类研究

提出了以小波包熵作为脑电特征向量的左右手运动意识任务分类方法,对被测试者想象左右手运动时的脑电小波包熵动态变化情况及分析窗口长度的选择进行了研究.结果表明,小波包熵能很好地反映左右手运动想象的脑电特征变化,用线性判别式算法对脑电特征进行识别,分类正确率达到92.14%.由于小波包熵的计算比较简单,稳定性好,识别率高,为大脑运动意识任务的分类提供了新思路.     

Derivation of some parameters of myoelectric signals recorded during sustained constant force isometric contractions.

Mathematical expressions are derived for some parameters of the myoelectric (ME) signal recorded during a constant force isometric contraction. The expressions are developed from a stochastic model for the motor-unit action-potential trains obtained from empirical results. The following parameters: (a) the mean rectified value, (b) the mean integrated rectified value, (c) the root-mean-square value, and (d) the power density spectrum are described as functions of contraction time and constant force of an isometric muscle contraction. The calculated parameters are compared to their corresponding empirically obtained measurements which have been reported in the literature. A discussion on the behavior of the parameters during increasing contraction time is presented. Synchronization of the motor-unit action-potential trains is shown to have a pronounced effect on the parameters of the myoelectric signal. This result should be considered when analyzing long records of myoelectric signals.     

Multivariate classification of animal communication signals: A simulation-based comparison of alternative signal processing procedures using electric fishes

Evolutionary studies of communication can benefit from classification procedures that allow individual animals to be assigned to groups (e.g. species) on the basis of high-dimension data representing their signals. Prior to classification, signals are usually transformed by a signal processing procedure into structural features. Applications of these signal processing procedures to animal communication have been largely restricted to the manual or semi-automated identification of landmark features from graphical representations of signals. Nonetheless, theory predicts that automated time-frequency-based digital signal processing (DSP) procedures can represent signals more efficiently (using fewer features) than can landmark procedures or frequency-based DSP – allowing more accurate classification. Moreover, DSP procedures are objective in that they require little previous knowledge of signal diversity, and are relatively free from potentially ungrounded assumptions of cross-taxon homology. Using a model data set of electric organ discharge waveforms from five sympatric species of the electric fish Gymnotus, we adopted an exhaustive simulation approach to investigate the classificatory performance of different signal processing procedures. We considered a landmark procedure, a frequency-based DSP procedure (the fast Fourier transform), and two kinds of time-frequency-based DSP procedures (a short-time Fourier transform, and several implementations of the discrete wavelet transform -DWT). The features derived from each of these signal processing procedures were then subjected to dimension reduction procedures to separate those features which permit the most effective discrimination among groups of signalers. We considered four alternative dimension reduction methods. Finally, each combination of reduced data was submitted to classification by linear discriminant analysis. Our results support theoretical predictions that time-frequency DSP procedures (especially DWT) permit more efficient discrimination of groups. The performance of signal processing was found to depend largely upon the dimension reduction procedure employed, and upon the number of resulting features. Because the best combinations of procedures are dataset-dependent and difficult to predict, we conclude that simulations of the kind described here, or at least simplified versions of them, should be routinely executed before classification of animal signals - especially unfamiliar ones.     

Insights gained into the interpretation of surface electromyograms from the gastrocnemius muscles: A simulation study

Interpretation of surface electromyograms (EMG) is usually based on the assumption that the surface representation of action potentials does not change during their propagation. This assumption does not hold for muscles whose fibers are oblique to the skin. Consequently, the interpretation of surface EMGs recorded from pinnate muscles unlikely prompts from current knowledge. Here we present a complete analytical model that supports the interpretation of experimental EMGs detected from muscles with oblique architecture. EMGs were recorded from the medial gastrocnemius muscle during voluntary and electrically elicited contractions. Preliminary indications obtained from simulated and experimental signals concern the spatial localization of surface potentials and the myoelectric fatigue. Specifically, the spatial distribution of surface EMGs was localized about the fibers superficial extremity. Strikingly, this localization increased with the pinnation angle, both for the simulated EMGs and the recorded M-waves. Moreover, the average rectified value (ARV) and the mean frequency (MNF) of interference EMGs increased and decreased with simulated fatigue, respectively. The degree of variation in ARV and MNF did not depend on the pinnation angle simulated. Similar variations were observed for the experimental EMGs, although being less evident for a higher fiber inclination. These results are discussed on a physiological context, highlighting the relevance of the model proposed here for the interpretation of gastrocnemius EMGs and for conceiving future experiments on muscles with pinnate geometry.     

Surface EMG alterations induced by underwater recording.

BACKGROUND AND PURPOSE: This study aims to verify if amplitude and spectral characteristics of surface EMG signal are modified due to recording in a wet environment. METHODS: Isometric contractions of the biceps brachii muscle of ten subjects were performed in several different set-up combinations, both in dry (D) and in water from hydrotherapy pools (PW), with (PWM) or without moving the pool water and with (T) or without water-resistant adhesive taping. RESULTS: In PW condition the amplitude of the recorded signal is reduced to 5-10% of the corresponding signal recorded in D condition. In PWM the power spectrum is drastically reduced and altered by the water movement that introduces an increase of spectral power in the frequency range 0-20 Hz. The use of T modality allows to record signals with both amplitude and spectral frequencies comparable with those obtained in the D conditions. DISCUSSION AND CONCLUSION: This work demonstrates the need for water resistant taping when EMG signals are recorded in water. Signals recorded without such a protective film are strongly affected in their amplitude and frequency characteristics by the conductivity and the movement of water.     

An algorithm for FHR estimation from foetal phonocardiographic signals

The long-term foetal surveillance is often to be recommended. Hence, the fully non-invasive acoustic recording, through maternal abdomen, represents a valuable alternative to the ultrasonic cardiotocography. Unfortunately, the recorded heart sound signal is heavily loaded by noise, thus the determination of the foetal heart rate raises serious signal processing issues. In this paper, we present a new algorithm for foetal heart rate estimation from foetal phonocardiographic recordings. A filtering is employed as a first step of the algorithm to reduce the background noise. A block for first heart sounds enhancing is then used to further reduce other components of foetal heart sound signals. A complex logic block, guided by a number of rules concerning foetal heart beat regularity, is proposed as a successive block, for the detection of most probable first heart sounds from several candidates. A final block is used for exact first heart sound timing and in turn foetal heart rate estimation. Filtering and enhancing blocks are actually implemented by means of different techniques, so that different processing paths are proposed. Furthermore, a reliability index is introduced to quantify the consistency of the estimated foetal heart rate and, based on statistic parameters; [,] a software quality index is designed to indicate the most reliable analysis procedure (that is, combining the best processing path and the most accurate time mark of the first heart sound, provides the lowest estimation errors). The algorithm performances have been tested on phonocardiographic signals recorded in a local gynaecology private practice from a sample group of about 50 pregnant women. Phonocardiographic signals have been recorded simultaneously to ultrasonic cardiotocographic signals in order to compare the two foetal heart rate series (the one estimated by our algorithm and the other provided by cardiotocographic device). Our results show that the proposed algorithm, in particular some analysis procedures, provides reliable foetal heart rate signals, very close to the reference cardiotocographic recordings.     

Spectro-temporal receptive fields of auditory neurons in the grassfrog

The nature of the stimulus-response relation for single auditory neurons is reflected in the properties of the Pre-Event Stimulus Ensemble: the ensemble of stimuli, preceding the occurrence of an action potential (neural event). This paper describes methods to analyse the spectro-temporal properties of this ensemble. These methods are based on the analytic signal representation of acoustic signals and functionals derived from it: the instantaneous amplitude and instantaneous frequency and the dynamic power spectrum. The procedures have been applied to a number of extra-cellular single unit recordings from the grassfrog, Rana temporatia L., recorded during presentation of an ensemble of tonal stimuli. The outcome of this analysis describes the spectro-temporal receptive field of the neuron under the present stimulus conditions. The procedure, based on the dynamic power spectrum is applicable to an arbitrary stimulus ensemble, thus allowing a comparison of the spectrotemporal receptive fields for different types of stimuli.     

sEMG wavelet-based indices predicts muscle power loss during dynamic contractions

The purpose of this study was to investigate the sensitivity of new surface electromyography (sEMG) indices based on the discrete wavelet transform to estimate acute exercise-induced changes on muscle power output during a dynamic fatiguing protocol. Fifteen trained subjects performed five sets consisting of 10 leg press, with 2 min rest between sets. sEMG was recorded from vastus medialis (VM) muscle. Several surface electromyographic parameters were computed. These were: mean rectified voltage (MRV), median spectral frequency (F_med), Dimitrov spectral index of muscle fatigue (FI_nsm5), as well as five other parameters obtained from the stationary wavelet transform (SWT) as ratios between different scales. The new wavelet indices showed better accuracy to map changes in muscle power output during the fatiguing protocol. Moreover, the new wavelet indices as a single parameter predictor accounted for 46.6% of the performance variance of changes in muscle power and the log-FI_nsm5 and MRV as a two-factor combination predictor accounted for 49.8%. On the other hand, the new wavelet indices proposed, showed the highest robustness in presence of additive white Gaussian noise for different signal to noise ratios (SNRs). The sEMG wavelet indices proposed may be a useful tool to map changes in muscle power output during dynamic high-loading fatiguing task.     

Correlation of myoelectric activity and muscle force during selected cat treadmill locomotion

The purpose of this investigation was to associate the force produced by the cat medial gastrocnemius (MG) during unrestrained treadmill locomotion with the corresponding myoelectric signals (MES's). An intervention analysis based on the autoregressive-integrated moving average (ARIMA) process was performed on records obtained at treadmill speeds of 0.67 ms-1 and 2.24 ms-1. Results indicate that the pattern of MG myoelectric activity during a single step cycle may be divided into two parts. The primary burst (E1 burst) of activity occurs before foot contact and represents an energy build up which is related to a major part of the MG force monitored at the tendon. During stance, a second burst of activity is depicted by an almost critically damped second order system, and is responsible for the residual tension observed. Thus in vivo forces can be linked to MES's provided that phase differences between electrical and mechanical responses are taken into account.