Jacques Duchêne

Uterine electromyography: A critical review

On the basis of a literature review, this work summarizes uterine animal and human electromyographic information obtained at cellular, myometrial, and abdominal levels during gestation and parturition. We show that both internal and external electromyograms occur in phase with intrauterine pressure increase and exhibit similar spectra, including a slow wave (0.01 < frequency < 0.03 Hz) probably because of mechanical artifacts and a fast wave whose frequency content can be subdivided into a low-frequency band always present in every contraction and a high-frequency band related to efficient parturition contractions. Application of classic spectral techniques to electromyogram envelopes has identified group propagation but not pacemaker areas. However, no time delay or classic propagation has been demonstrated by applying the same spectral techniques to the electromyogram itself, probably because of the nonlinearity and three-dimensional nature of the propagating process.

Uterine EHG Processing for Obstetrical Monitorng

The temporal and spectral properties of the human uterine electromyogram are first described, related to two different situations: pregnancy and parturition. Thus, a parameter set is selected, and a discriminant analysis is performed, in order to obtain the best discriminant vector for these two situations. A dynamic control of the efficiency of the contractions during labor is described. The good results of this dynamic control permit us to propose a monitoring device providing information on contraction rate and efficiency.

Evaluation of driver discomfort during long-duration car driving ☆

The evolution of indices of fatigue, discomfort, and performance of subjects seated for long duration (150 min) in car seats were studied (n=11). Four experimental configurations were used: with and without vibration for two seats (U, uncomfortable; C, comfortable). Surface electromyography (SEMG) data were recorded bilaterally from cervical erector spinae and external oblique muscles. Discomfort increased significantly during the trial, regardless of the experimental condition (p<0.05). Performance was significantly worse for seat U with vibration (p<0.05). The median frequency of SEMG signals did not change between experimental conditions or across time. It would appear that, either the level of discomfort experienced was insufficient to change either performance or SEMG measures, or that the large parameter estimation variance of the SEMG signals might have masked any underlying spectral change. Further refinement of the SEMG signal processing methodology may be necessary to be able to detect fatigue of postural muscles.

A model of EMG generation

Simulation models are unavoidable in experimental research when the point is to develop new processing algorithms to be applied on real signals in order to extract specific parameter values. Such algorithms have generally to be optimized by comparing true parameter values to those deduced from the algorithm. Only a simulation model can allow the user to access and control the actual process parameter values. This constraint is especially true when dealing with biomedical signals like surface electromyogram (SEMG). This work is an attempt to produce an efficient SEMG simulation model as a help for assessing algorithms related to SEMG features description. It takes into account the most important parameters which could influence these characteristics. This model includes all transformations from intracellular potential to surface recordings as well as a fast implementation of the extracellular potential computation. In addition, this model allows multiple graphically-programmable electrode-set configurations and SEMG simulation in both voluntary and elicited contractions.

Variability of some SEMG parameter estimates with electrode location

Muscular action potential conduction velocity (CV) and mean power frequency (MPF) are commonly used parameters to describe the surface electromyographic signal (SEMG). The discrepancies concerning the behavior and interpretation of these main parameters in the literature have motivated this work. Our objective was to evaluate within- and between-individual reproducibility, sensitivity and variation of CV and MPF depending on the electrode location with respect to various contraction modalities. The results present evidence for significant influence of electrode location on CV and MPF, not only in their initial values but also in their changes during fatiguing efforts. This influence appears to be subject-dependent. This variability seems to be essentially due to the relative displacements of myotendinous and neuromuscular junctions with respect to the electrode set. Moreover, this study shows that MPF can be seen as force-dependent under certain conditions and that the CV-MPF relationship is strongly influenced by methodological factors. In conclusion, it seems irrelevant to derive reliable SEMG parameter estimates without considering electrode location. There is a strong need for proper standardization based on anatomical and methological aspects before attempting any individual characterization. Finally, we suggest a procedure for assessment of measurement quality.

Fractal time series analysis of postural stability in elderly and control subjects.

BackgroundThe study of balance using stabilogram analysis is of particular interest in the study of falls. Although simple statistical parameters derived from the stabilogram have been shown to predict risk of falls, such measures offer little insight into the underlying control mechanisms responsible for degradation in balance. In contrast, fractal and non-linear time-series analysis of stabilograms, such as estimations of the Hurst exponent (H), may provide information related to the underlying motor control strategies governing postural stability. In order to be adapted for a home-based follow-up of balance, such methods need to be robust, regardless of the experimental protocol, while producing time-series that are as short as possible. The present study compares two methods of calculating H: Detrended Fluctuation Analysis (DFA) and Stabilogram Diffusion Analysis (SDA) for elderly and control subjects, as well as evaluating the effect of recording duration.MethodsCentre of pressure signals were obtained from 90 young adult subjects and 10 elderly subjects. Data were sampled at 100 Hz for 30 s, including stepping onto and off the force plate. Estimations of H were made using sliding windows of 10, 5, and 2.5 s durations, with windows slid forward in 1-s increments. Multivariate analysis of variance was used to test for the effect of time, age and estimation method on the Hurst exponent, while the intra-class correlation coefficient (ICC) was used as a measure of reliability.ResultsBoth SDA and DFA methods were able to identify differences in postural stability between control and elderly subjects for time series as short as 5 s, with ICC values as high as 0.75 for DFA.ConclusionBoth methods would be well-suited to non-invasive longitudinal assessment of balance. In addition, reliable estimations of H were obtained from time series as short as 5 s.

Evolution in impedance at the electrode-skin interface of two types of surface EMG electrodes during long-term recordings

The evolution in impedance at the electrode-skin interface of Beckman and Red Dot electrodes was assessed during long-term recordings. Impedance was measured between each pair of electrodes, arranged in a bipolar configuration on tibialis anterior (n=13). A waveform constructed of sinusoids of known frequencies, evenly distributed on a log scale from 1-16,384 Hz, was applied through the electrodes, and the result recorded by a DAQ system. SEMG signals were recorded at 1000 Hz during isometric dorsiflexion contractions of 30 s, performed every 15 min for 2 h. Impedance data were acquired at 65,536 Hz immediately before and after SEMG recordings. Large individual differences in impedance levels were observed at low frequencies. At high frequencies, impedance values depended only on the electrode type. Impedance decreased steadily with time for Beckman electrodes (p < 0.05), but did not decrease significantly for Red Dot electrodes. The magnitude of the reduction over time varied widely between individuals, and was related to the initial impedance values. The impedance-bandwidth product remained constant for each electrode type (95% confidence intervals 146.2-148.2 and 126.1-127.8 for Beckman and Red Dot electrodes respectively). When skin impedance is electrically modelled with a simple network containing a resistor and a capacitor, the capacitance varies with the properties of the electrode used, whereas resistance is dependent on the subject. Furthermore, the EMG spectrum is unaffected by impedance provided skin preparation is sufficient to reduce the impedance below 55 komega.

Intrinsic Mode Entropy for Nonlinear Discriminant Analysis

Several methods of measuring entropy of time series have been developed and applied on physiological signals in order to distinguish data sets according to their underlying nonlinear dynamics. These methods are not well adapted for studying the time series in different scales, in the presence of dominant local trends and low-frequency components. In this letter, intrinsic mode entropy (IMEn) is proposed as an entropy measure over multiple oscillation levels. Robustness to local trends is ensured with this new measure, enabling an efficient characterization of the underlying nonlinear dynamics of the time series considered. IMEn is obtained by computing the Sample Entropy (SampEn) of the cumulative sums of the intrinsic mode functions extracted by the empirical mode decomposition method. An example of an application of IMEn is then presented, with the method able to successfully discriminate between two groups of subjects (elderly versus control) for signals of postural stability

Classifying NIR spectra of textile products with kernel methods

This paper describes the use of kernel methods to classify tissue samples using near-infrared spectra in order to discriminate between samples, either with or without elastane. The aim of this real-world study is to identify an alternative method to classify textile products using near-infrared (NIR) spectroscopy in order to improve quality control, and to aid in the detection of counterfeit garments. The principles behind support vector machines (SVMs), of which the main idea is to linearly separate data, are recalled progressively in order to demonstrate that the decision function obtained is a global optimal solution of a quadratic programming problem. Generally, this solution is found after embedding data in another space F with a higher dimension by the means of a specific non-linear function, the kernel. For a selected kernel, one of the most important and difficult subjects concerning SVM is the determination of tuning parameters. Generally, different combinations of these parameters are tested in order to obtain a machine with adequate classification ability. With the kernel alignment method used in this paper, the most appropriate kernel parameters are identified rapidly. Since in many cases, data are embedded in F, a linear principal component (PC) analysis (PCA) can be considered and studied. The main properties and the algorithm of k-PCA are described here. This paper compares the results obtained in prediction for a linear classifier built in the initial space with the PCs from a PCA and those obtained in F with non-linear PCs from a k-PCA. In the present study, even if there are potentially discriminating wavelengths seen on the NIR spectra, linear discriminant analysis and soft independent modelling of class analogy results show that these wavelengths are not sufficient to build a machine with correct generalisation ability. The use of a non-linear method, such as SVM and its corollary methods, kernel alignment and k-PCA, is then justified.

Uterine EMG spectral analysis and relationship to mechanical activity in pregnant monkeys

The objective is to analyse internal and external recordings of uterine EMG in order to reveal common features and to assess the relationship between electrical activity and intra-uterine pressure modification. Three monkeys participated in the study, one as a reference and the others for data. EMGs are recorded simultaneously, internally by unipolar wire electrodes and externally by bipolar Ag/AgCl electrodes. Intra-uterine pressure is recorded as a mechanical index. Except for delay measurements, parameters are derived from spectral analysis and relationships between recordings are assessed by studying the coherence. Spectral analysis exhibits two basic activities in the analysed frequency band, and frequency limits are defined as relevant parameters for electrical activity description. Parameter values do not depend on the internal electrode location. Internal and external EMGs present a similar spectral shape, despite differences in electrode configuration and tissue filtering. It is deduced that external uterine EMG is a good image of the genuine uterine electrical activity. To some extent, it can be related to an average cellular electrical activity.