A Preliminary Exploration of the Placental Position Influence on Uterine Electromyography Using Fractional Modelling

The uterine electromyogram, also called electrohysterogram (EHG), is the electrical signal generated by uterine contractile activity. The EHG has been considered an expanding technique for pregnancy monitoring and preterm risk evaluation. Data were collected on the abdominal surface. It has been speculated the effect of the placenta location on the characteristics of the EHG. In this work, a preliminary exploration method is proposed using the average spectra of Alvarez waves contractions of subjects with anterior and non-anterior placental position as a basis for the triple-dispersion Cole model that provides a best fit for these two cases. This leads to the uterine impedance estimation for these two study cases. Non-linear least square fitting (NLSF) was applied for this modelling process, which produces electric circuit fractional models’ representations. A triple-dispersion Cole-impedance model was used to obtain the uterine impedance curve in a frequency band between 0.1 and 1 Hz. A proposal for the interpretation relating the model parameters and the placental influence on the myometrial contractile action is provided. This is the first report regarding in silico estimation of the uterine impedance for cases involving anterior or non-anterior placental positions.

Critical analysis of electrohysterographic methods for continuous monitoring of intrauterine pressure

Monitoring the progression of uterine activity provides important prognostic information during pregnancy and delivery. Currently, uterine activity monitoring relies on direct or indirect mechanical measurements of intrauterine pressure (IUP), which are unsuitable for continuous long-term observation. The electrohysterogram (EHG) provides a non-invasive alternative to the existing methods and is suitable for long-term ambulatory use. Several published state-of-the-art methods for EHG-based IUP estimation are here discussed, analyzed, optimized, and compared. By means of parameter space exploration, key parameters of the methods are evaluated for their relevance and optimal values. We have optimized all methods towards higher IUP estimation accuracy and lower computational complexity. Their accuracy was compared with the gold standard accuracy of internally measured IUP. Their computational complexity was compared based on the required number of multiplications per second (MPS). Significant reductions in computational complexity have been obtained for all published algorithms, while improving IUP estimation accuracy. A correlation coefficient of 0.72 can be obtained using fewer than 120 MPS. We conclude that long-term ambulatory monitoring of uterine activity is possible using EHG-based methods. Furthermore, the choice of a base method for IUP estimation is less important than the correct selection of electrode positions, filter parameters, and postprocessing methods. The presented review of state-of-the-art methods and applied optimizations show that long-term ambulatory IUP monitoring is feasible using EHG measurements.

Classification of Two Class Motor Imagery Tasks Using Hybrid GA-PSO Based K-Means Clustering

Transferring the brain computer interface (BCI) from laboratory condition to meet the real world application needs BCI to be applied asynchronously without any time constraint. High level of dynamism in the electroencephalogram (EEG) signal reasons us to look toward evolutionary algorithm (EA). Motivated by these two facts, in this work a hybrid GA-PSO based K-means clustering technique has been used to distinguish two class motor imagery (MI) tasks. The proposed hybrid GA-PSO based K-means clustering is found to outperform genetic algorithm (GA) and particle swarm optimization (PSO) based K-means clustering techniques in terms of both accuracy and execution time. The lesser execution time of hybrid GA-PSO technique makes it suitable for real time BCI application. Time frequency representation (TFR) techniques have been used to extract the feature of the signal under investigation. TFRs based features are extracted and relying on the concept of event related synchronization (ERD) and desynchronization (ERD) feature vector is formed.

Estimation of internal uterine pressure by joint amplitude and frequency analysis of electrohysterographic signals

Monitoring the uterine contraction provides important prognostic information during pregnancy and parturition. The existing methods employed in clinical practice impose a compromise between reliability and invasiveness. A promising technique for uterine contraction monitoring is electrohysterography (EHG). The EHG signal measures the electrical activity which triggers the contraction of the uterine muscle. In this paper, a non-invasive method for intrauterine pressure (IUP) estimation by EHG signal analysis is proposed. The EHG signal is regarded as a non-stationary signal whose frequency and amplitude characteristics are related to the IUP. After acquisition in a multi-channel configuration, the EHG signal is therefore analyzed in the time-frequency domain. A first estimation of the IUP is then derived by calculation of the unnormalized first statistical moment of the frequency spectrum. The estimation accuracy is finally increased by identification of a second-order polynomial model. The proposed method is compared to root mean squared analysis and optimal linear filtering and validated by simultaneous measurement of the IUP on nine women during labor. The results suggest that the proposed EHG signal analysis provides an accurate estimate of the IUP.

Physiology and electrical activity of uterine contractions

Presently, there is no effective treatment for preterm labor. The most obvious reason for this anomaly is that there is no objective manner to evaluate the progression of pregnancy through steps leading to labor, either at term or preterm. Several techniques have been adopted to monitor labor, and/or to diagnose labor, but they are either subjective or indirect, and they do not provide an accurate prediction of when labor will occur. With no method to determine preterm labor, treatment might never improve. Uterine electromyography (EMG) methods may provide such needed diagnostics.

Quantitative analysis of contraction patterns in electrical activity signal of pregnant uterus as an alternative to mechanical approach

Monitoring of uterine contraction activity is an important diagnostic tool used during both pregnancy and labour. The strain the pregnant uterus exerts on the maternal abdomen is measured via external tocography. However, limitation of this approach has caused the development of another technique-electrohysterography--which is based on the recording of electrical uterine activity. A computer-aided system is presented, which allows the recording of electrohysterographic signals from the maternal abdomen and their on-line analysis both in time and frequency domains. As a research material, we acquired 108 traces during a 24 h period before labour from a group of patients between 37 and 40 weeks of gestation. The comparison study between electrohysterography and tocography was carried out thanks to the possibility of simultaneous recording of mechanical and electrical uterine activities. The obtained results show that both methods demonstrate high agreement in relation to the number of contractions recognized as being consistent. However, their agreement in relation to the quantitative description of recognized patterns has appeared to be unacceptable to consider these methods as fully alternative. The appropriate way of further development of electrohysterography seems to be spectral analysis. Several spectral parameters describing electrophysiological properties of uterine muscle can be obtained by the use of electrohysterographic signals.

Improved Maximum Frequency Estimation With Application to Instantaneous Mean Frequency Estimation of Surface Electromyography

The purpose of this study was to improve the maximum-frequency estimation. Three methods to estimate the maximum frequency of a bandlimited signal with additive white noise were compared. Two existing methods, the threshold-crossing method (TCM) and the hybrid method, were modified for time-frequency representations. A novel approach, the running-block threshold method (RBTM), was introduced. Based on calculation of detection probability (sensitivity) the RBTM improved the maximum-frequency estimate as compared with the TCM. The maximum-frequency estimation methods were also used to determine the integration interval for instantaneous mean-frequency (IMNF) estimation from synthesized surface electromyography containing white noise. Results showed that the IMNF estimate was improved by using any of the three methods and that the RBTM gave the best IMNF estimate.

Continuous wavelet transform in the evaluation of stretch reflex responses from surface EMG

OBJECTIVE

This is the first reported use of the continuous wavelet transform (CWT) of the surface EMG (sEMG) to extract the reflex response to muscle stretch. We used a modulus-based method to estimate instantaneous amplitude-envelopes from ridges of the CWT (referred in this work as sEMG intensity) to extract the dynamic reflex response from sEMG. We tested the method on tendon reflexes where excellent temporal resolution is required to identify the different latency components, and on the tonic stretch reflex (tonic SR) response to an ongoing perturbation that characteristically has a low signal to noise ratio.

METHODS

Eight subjects without neurological impairment were subjected to a series of archilles tendon taps and a 2 min continuous perturbation of the ankle using a pseudo-sinusoidal stretch profile containing frequencies from 0.1 to 8.0 Hz. The tendon reflexes were assessed in the soleus muscle at 10% of MVC and the tonic SR in tibialis anterior while the muscle was relaxed, at 5 and 10% of maximal voluntary contraction. Root mean square (RMS) and wavelet ridge extraction was applied to the sEMG signal to extract sEMG amplitudes (RMS) and intensities for all reflexes. To obtain the tonic SR, these estimates and those from the sEMG-RMS were subsequently cross-correlated with the perturbation record to yield 2 sets of estimates of reflex gain and coherence for comparison.

RESULTS

The sEMG intensities were highly correlated with the torques resulting from a ramped voluntary contraction. Following tendon taps, the method resolved the M1, M2, M3 response components at accurate latencies and with more complete reconstruction of the components than RMS-derived estimates. The wavelet ridge estimates extracted the tonic SR from resting and contracting muscles with significantly higher coherence than RMS estimates. Reflex gain, when estimated from sEMG intensity or sEMG-RMS, demonstrated similar relationships to the perturbation frequency and background contraction level. When the sEMG intensity reflex gain estimates from different subjects were pooled, they showed significantly lower variance about the mean than gain estimates derived from the rectified sEMG.

CONCLUSIONS

Wavelet-ridge extraction provides a valid approach to reflex evaluation from sEMG that does not depend on the absolute amplitude of the potentials measured at the EMG electrodes. This may have substantial advantages in more directly comparing responses between subjects on an absolute frequency scale without the need for normalisation against maximal contraction levels.

Time-frequency analysis of SEMG with special consideration to the interelectrode spacing

The surface electromyogram (SEMG) is a complex, nonstationary signal. The spectrum of the SEMG is dependent on the force of contraction being generated and other factors like muscle fatigue and interelectrode distance (IED). The spectrum of the signal is time variant. This paper reports the experimental research conducted to study the influence of force of muscle contraction and IED on the SEMG signal using time-frequency (T-F) analysis. Two T-F techniques have been used: Wigner-Ville distribution (WVD) and Choi-Williams distribution (CWD). The experiment was conducted with the help of ten healthy volunteers (five males and five females) who performed isometric elbow flexions of the active right arm at 20%, 50%, and 80% of their maximal voluntary contraction. The SEMG signal was recorded using surface electrodes placed at a distance of 18 and 36 mm over biceps brachii muscle. The results indicate that the two distributions were spread out across the frequency range at smaller IED. Further, regardless of the spacing, both distributions displayed increased spectral compression with time at higher contraction level.

Assessment of muscle fatigue during biking

The analysis of the surface myoelectric signal recorded while a muscle is performing a sustained contraction is a valuable tool for assessing the progression of localized fatigue. It is well known that the modifications of the spectral content of the myoelectric signal are mainly related to changes in the interstitial fluid pH, which, in turn, affect the membrane excitability of the active muscle fibers. This paper describes the effects of muscle fatigue on the surface myoelectric signal recorded from three thigh and leg muscles during biking, on a population consisting of 22 young healthy volunteers. The purpose of this study was to obtain normative data relative to an exercise protocol mild enough to be applicable, in the future, to pathological subjects as well. Each subject was asked to exercise 30 min on a cycloergometer at a constant velocity and against a constant torque. While subjects were biking, the surface myoelectric signal was recorded from the rectus femoris, the biceps femoris, and the gastrocnemius muscles. In this study, we considered two different aspects of muscle fatigue: first, the localized muscle fatigue as shown by the decrement of the instantaneous frequency of the myoelectric signal during the exercise; second, the modifications of the muscle ON-OFF timing, which could be explained as a strategy for increasing endurance by modifying the role of different muscles during the exercise. The first aspect was studied by obtaining the spectral characteristics of the signals by means of bilinear time-frequency transforms and by applying an original estimator of the instantaneous frequency of stochastic processes based on cross time-frequency transforms. Our results demonstrated that none of the subjects showed significant signs of localized muscle fatigue, since the decrement of the instantaneous frequency during the exercise was always lower than 5% of its initial value. Muscle ON-OFF timing was obtained by applying to the raw myoelectric signal a double threshold statistical detector to identify the time intervals during which the observed muscles were active. This demonstrated that the subjective feeling of fatigue each subject reported during the exercise did not cause a change of the activation strategy of the observed muscles. It is concluded that the experimental protocol herein described and the signal processing procedures adopted are appropriate for monitoring different effects of muscle fatigue during biking. Moreover, data obtained from our sample population can be considered as a reference for studying the manifestations of muscle fatigue in pathological subjects asked to follow a similar experimental protocol.

Methods and devices for the management of term and preterm labor

In this review, we outline studies showing that the uterus (myometrium) and cervix pass through a conditioning step in preparation for labor. This step is not easily identifiable with present methods designed to assess the uterus or cervix. In the uterus, this seemingly irreversible step consists of changes in the electrical properties that make muscle more excitable and responsive and produce forceful contractions. In the cervix, the step consists of softening of the connective tissue components. Progesterone and nitric oxide appear to have important roles in these processes. The progress of labor can be assessed noninvasively using electromyographic (EMG) signals from the uterus (the driving force for contractility) recorded from the abdominal surface. Uterine EMG bursts detected in this manner characterize uterine contractile events during human and animal pregnancy. A low uterine EMG activity, measured transabdominally throughout most of pregnancy, rises dramatically during labor. EMG activity also increases substantially during preterm labor in humans and rats and may be predictive of preterm labor. A quantitative method for assessing the cervix is also described. A collascope estimates cervical collagen content from a fluorescent signal generated when collagen crosslinks are illuminated with an excitation light of about 340 nm. The system has proved useful in rats and humans at various stages of pregnancy and indicates that cervical softening occurs progressively in the last one-third of pregnancy. In rats, collascope readings correlate with resistance measurements made in the isolated cervix, which may help to assess cervical function during pregnancy and indicate controls and treatments.

Mean frequency and signal amplitude of the surface EMG of the quadriceps muscles increase with increasing torque--a study using the continuous wavelet transform

The continuous wavelet transform (CWT), a time-frequency method, was used when calculating mean frequency of the power spectrum (MNF) and signal amplitude (RMS) of the surface EMG to investigate their relationships to force during a gradually increasing knee extension (ramp). Based upon the CWT, MNF was redefined to include time dependence on the EMG signal frequency contents, the short-time MNF (STMNF). Surface EMG was recorded from vastus lateralis, rectus femoris and vastus medialis in 21 clinically healthy subjects during a brief, gradually increasing contraction up to 100% of a maximum voluntary contraction (MVC), with a duration of approximately 10 s. The relationships between the EMG variables and force using linear regression were determined for each subject. For vastus lateralis, we also investigated if certain aspects of the muscle morphology (i.e., proportions and areas of different fibre types) influenced the EMG-force relationship. For the majority of subjects (17-18 out of 21 subjects) there were significant positive correlations between STMNF and force in the three muscles. No sex differences were found in intercepts or regression coefficients of STMNF. The muscle morphology had a significant influence on the STMNF-force intercept and the regression coefficient. Positive and highly significant linear correlations between RMS and force were found for all subjects and all three muscles.In conclusion, time frequency methods can be applied when investigating EMG during brief contractions associated with non-stationarity. In a great majority of the subjects, and in the three muscles, significant linear force dependencies were found for STMNF. Thus, when evaluating muscle fatigue, e.g., in ergonomic situations, it is important to consider the force level as one factor that can influence the results. Morphological variables (fibre proportions and fibre areas) influenced the STMNF-force relationship in vastus lateralis.

Time-frequency analysis of myoelectric signals during dynamic contractions: a comparative study

In this paper, we introduce the nonstationary signal analysis methods to analyze the myoelectric (ME) signals during dynamic contractions by estimating the time-dependent spectral moments. The time-frequency analysis methods including the short-time Fourier transform, the Wigner-Ville distribution, the Choi-Williams distribution, and the continuous wavelet transform were compared for estimation accuracy and precision on synthesized and real ME signals. It is found that the estimates provided by the continuous wavelet transform have better accuracy and precision than those obtained with the other time-frequency analysis methods on simulated data sets. In addition, ME signals from four subjects during three different tests (maximum static voluntary contraction, ramp contraction, and repeated isokinetic contractions) were also examined.

Active contractions of the cervix in the latent phase of labour

OBJECTIVE

To study the activity of the human uterine cervix at the onset of labour and further characterise cervical asynchronous electromyographic (EMG) activity in the latent phase.

DESIGN

Prospective observational study.

SETTING AND PARTICIPANTS

Clinical hospital in Ljubljana.

PARTICIPANTS

Forty-seven healthy nulliparous women with relatively unripe cervices requiring induction of labour.

METHODS

Simultaneous registration of a cervical EMG and of the intrauterine pressure at the very early stage of labour; subsequent EMG signal processing to determine its time, amplitude and frequency parameters.

MAIN OUTCOME MEASURES

Simultaneous comparison of the cervical EMG and the mechanical activity of the uterine corpus to deduce electrical properties of the cervical smooth muscle tissue and its activity.

RESULTS

EMG bursts, asynchronous with the contractions of the uterine corpus, were registered in 20 out of 47 women. In 14 women bursts appeared independent of uterine corpus contractions and in six they followed the peak of contractions. The bursts had low average median frequency (0.3 Hz). In seven women bursts were superimposed onto a background EMG (median frequency = 1.2 Hz).

CONCLUSIONS

Bursts in the cervical EMG may appear asynchronously with the uterine contractions. Bursts not related to contractions suggest active and independent cervical muscle activity. The bursts which follow contractions may be an active response of the cervical musculature to passive stretching during a contraction. The EMG frequency content suggests two different contraction mechanisms or a different origin of the EMG in the cervix.