Physiologically based simulation of clinical EMG signals

An algorithm that generates electromyographic (EMG) signals consistent with those acquired in a clinical setting is described. Signals are generated using a model constructed to closely resemble the physiology and morphology of skeletal muscle, combined with line source models of commonly used needle electrodes positioned in a way consistent with clinical studies. The validity of the simulation routines is demonstrated by comparing values of statistics calculated from simulated signals with those from clinical EMG studies of normal subjects. The simulated EMG signals may be used to explore the relationships between muscle structure and activation and clinically acquired EMG signals. The effects of motor unit (MU) morphology, activation, and neuromuscular junction activity on acquired signals can be analyzed at the fiber, MU and muscle level. Relationships between quantitative features of EMG signals and muscle structure and activation are discussed.     

Singularity characteristics of needle EMG IP signals

Clinical electromyography (EMG) interference pattern (IP) signals can reveal more diagnostic information than their constituents, the motor unit action potentials (MUAPs). Singularities and irregular structures typically characterize the mathematically defined content of information in signals. In this paper, a wavelet transform method is used to detect and quantify the singularity characteristics of EMG IP signals using the Lipschitz exponent (LE) and measures derived from it. The performance of the method is assessed in terms of its ability to discriminate healthy, myopathic and neuropathic subjects and how it compares with traditionally used Turns Analysis (TA) methods and a method recently developed by the authors, interscale wavelet maximum (ISWM). Highly significant intergroup differences were found using the LE method. Most of the singularity measures have a performance similar to that of ISWM and considerably better than that of TA. Some measures such as the ratio of the mean LE value to the number of singular points in the signal have considerably superior performance to both methods. These findings add weight to the view that wavelet analysis methods offer an effective way forward in the quantitative analysis of EMG IP signal to assist the clinician in the diagnosis of neuromuscular disorders.     

Clustering analysis and pattern discrimination of EMG linearenvelopes

A technique has been developed for performing pattern analysis of EMG activities generated during locomotion. In this development it was found that the shapes of the EMG linear envelopes (LE) are mainly determined by their phase spectra; their magnitude spectra are much less important. Autoregressive (AR) parametric models and discrete Fourier transform (DFT) approaches were tested and compared. The latter was proved to be a better way to describe the EMG LE's. Feature extraction and clustering were performed by doing DFT of EMG LE's, extracting part of the phase and magnitude spectra (in less important degree) as features, and using the percent powers to weigh the corresponding harmonics. The approach was applied to the clustering analysis of EMG LE's of normal and anterior cruciate ligament (ACL) injured subjects during walking.     

A note on spectral shaping of minimum-shift-keying-type signals

Recently proposed minimum-shift-keying (MSK)-type modulation schemes are shown to be members of a previously suggested of offset quadrature-carrier modulation techniques called continuous-shift-keying (CSK).     

The mean power spectral density of Markov chain driven signals

Many signals ocurring in data communications can be described by Markovian models. Expressions for the mean power spectral density function of a signal driven by a stationary discrete-parameter finite-state Markov chain are derived and discussed, both for irreducible and reducible chains. Two examples are presented to illustrate the application of the results.     

Investigation on parametric analysis of dynamic EMG signals by amuscle-structured simulation model

In the analysis of electromyographic (EMG) signals during dynamic movement, we have proposed an estimation algorithm for the time-varying parameters of an autoregressive model. The parameters correspond to less biased time-varying reflection coefficients. We determined the less biased estimation using a locally quasi-stationary model and named these parameters "k parameters." We estimated k parameters up to the fifth order for the surface EMG signals of a masseter muscle during rapid open-close movement of the lower jaw, a ballistic contraction, and fatigue. According to the results, the time courses of the k parameters displayed remarkable properties. In order to study the behavior of k parameters physiologically, we produced a muscle-structured simulation model based on anatomical and physiological data. The simulation results suggested that the behavior of the third parameter is related to the number of active motor units (MU's) at the shallow layer of a muscle. The detailed recruitment mechanism in terms of the MU's types has not yet been solved. Although further study is required, the parametric analysis using k parameters offers a new perspective for evaluation of muscle dynamics during several movements.     

The spectral characteristics of navigation alternative binary offset carrier modulated signals (AltBOC signals)

Analytical expressions are obtained for spectral densities and energy spectra of single elements and single periods of modulating functions of alternative binary offset carrier modulated signals (AltBOC signals) for new-generation satellite radio navigation systems (SRNSs) (in particular, the Galileo system). The spectral characteristics are presented and analyzed for an elementary (two-component) AltBOC signal, a complete AltBOC with a time-variable envelope (a four-component complete AltBOC signal), and a complete AltBOC with a constant envelope (an eight-component complete AltBOC signal) in the case when the multiplicity coefficient of meander pulses has an arbitrary value. Plots are depicted, and the properties of energy spectra of single elements of modulating functions of all groups of AltBOC signals are discussed in the cases of the following modulation types: AltBOC(10, 10), AltBOC(15, 10), AltBOC(20, 10), and AltBOC(25, 10).     

Methods of spectral identification of hydroacoustic signals

It is considered methods of spectral identification of hydroacoustic signals based on comparison of \(\bar x_\alpha \) (f) dependences on spectrum frequency f of quantiles \(\bar x_\alpha \) (f) of hydroacoustic signals Fourier (Hartley) spectrum. The identification results are robust to abnormal interferences in channels of hydroacousic signals spreading, registration and reproduction.     

An AR spectral analysis of non-stationary signals

A method of estimating an adaptive spectral density is described. At each time-sample of the signal an autoregressive (AR) filter is calculated by a covariance method. The length of the memory is adapted to the stationarity of the signal by a minimum prediction error power criterion. Advantages of a pole trajectories representation in the time frequency domain are illustrated. The evolution of the prediction error power and of the length of the memory versus time gives information about the stationarity of the signal. Resolution and precision obtained by this AR method are better than those obtained by a Fourier Transform method.     

红外光谱信号预处理的新方法

要实现快速、准确地检测远距离污染气体红外光谱,对光谱进行预处理,消除高频噪声以及低频扰动,提取光谱特征信息是其中重要的一环。提出了一种对光谱信号进行预处理改进的高低通综合滤波法。该方法采用平滑滤波法去除高频噪声,采用阈值拟合技术处理低频扰动。阈值拟合技术的应用使整个光谱预处理过程完全自动化。实验结果表明,高低通综合滤波法可以使光谱预处理问题得到有效解决。该方法具有自适应功能,操作简便,运行可靠。     

Doppler polarisation spectral resolution of radar signals

This letter presents some results on dual-channel Doppler spectral analysis of radar signals received by two circularly and orthogonally polarised radar channels. These results were produced from an analysis of experimental data obtained, in the presence of both aircraft target and clutter, by an S-band ATC radar suitably modified for dual polarisation reception. The results illustrate that dual channel processing can improve the target resolution with respect to the single-channel processing, when using maximum entropy spectral estimation methods.     

Cyclic spectral analysis of continuous-phase modulated signals

Continuous-phase modulated (CPM) signals play a prominent role in modern communication systems due to their desirable constant-modulus property and the ability to control their power and bandwidth efficiencies. Popular CPM signals include the classical minimum-shift keyed (MSK) signal, the LREC family of signals also known as continuous-phase frequency-shift-keyed (CPFSK) signals, and Gaussian MSK, which is used in state-of-the-art GSM and PCS mobile communication systems. CPM signals, like virtually all man-made communication signals, are known to exhibit cyclostationarity, which implies that their probabilistic parameters, such as mean, second moment, and higher order cumulants, are almost-periodic functions of time. A novel representation of CPM signals as a sum of PAM signals is presented for both integer and noninteger modulation index cases. Then, the Nth-order cyclostationarity properties of binary CPM signals are derived in terms of Nth-order temporal and spectral moment and cumulant functions. Moreover, the case of M-ary CPM signals is briefly addressed. The results are illustrated with simulations involving MSK, LREC, and GMSK signals     

Exploitation of spectral redundancy in cyclostationary signals

It is shown that the cyclostationarity attribute, as it is reflected in the periodicities of (second-order) moments of the signal, can be interpreted in terms of the property that allows generation of spectral lines from the signal by putting it through a (quadratic) nonlinear transformation. The fundamental link between the spectral-line generation property and the statistical property called spectral correlation, which corresponds to the correlation that exists between the random fluctuations of components of the signal residing in distinct spectral bands, is explained. The effects on the spectral-correlation characteristics of some basic signal processing operations, such as filtering, product modulation, and time sampling, are examined. It is shown how to use these results to derive the spectral-correlation characteristics for various types of man-made signals. Some ways of exploiting the inherent spectral redundancy associated with spectral correlation to perform various signal processing tasks involving detection and estimation of highly corrupted man-made signals are described     

Boundary element analysis of the directional sensitivity of theconcentric EMG electrode

Employing the boundary element method, the authors improve earlier models of the concentric electromyography (EMG) electrode by including an accurate geometric representation of the electrode, as well as the mutual electrical influence between the electrode surfaces. A three-dimensional sensitivity function is defined from which information about the preferential direction of sensitivity, blind spots, phase changes, rate of attenuation, and range of pick-up radius can be derived. The study focuses on the intrinsic features linked to the geometry of the electrode. The results show that the cannula perturbs the potential distribution significantly. The preferential directions of sensitivity are determined by the amount of geometric offset between the individual sensitivity functions of the core and the cannula. The sensitivity function also reveals a complicated pattern of phase changes in the pick-up range. Rotation of the electrode about its axis was found to alter the duration, the peak-to-peak amplitude, and the risetime of waveforms recorded from a moving dipole     

基于谱相关的CBOC信号参数盲估计

针对低信噪比下组合二进制偏移载波(CBOC)调制信号的参数盲估计问题,提出了利用谱相关对CBOC信号进行参数估计方法。首先给出了CBOC信号模型,然后根据CBOC信号的数据通道和导频通道之间有良好的正交性特点,详细推导出其谱相关函数可以化简为两个BOC信号谱相关函数的叠加,最后根据CBOC信号循环频率截面的特点进行峰值检索后,实现对伪码速率、载频速率和副载波速率的盲估计。推导结果和计算机仿真分析表明,该方法可以实现在低信噪比下对伪码速率、载频速率和副载波速率的有效估计。     

Unified study on characteristic spectrum representation of signals and spectral decomposition for stationary random signals

The unified relationship between the signal characteristic spectrum representation and the spectral decomposition for the stationary random signal was deeply studied. By using the relations among the differential operators, the integral operator and the Green's function of the characteristic differential equation, the inverse relationship between the Hermitian differential operator and the Hermitian integral operator were given, the characteristic differential equation and corresponding characteristic integral equation were demonstrated, and the spectral representations of both Hermitian differential and integral operators and the general spectral representations for both operators were provided. Based on the superposition method of the stochastic simple harmonic vibration and the Hilbert space unitary operator method for the stationary random signal spectral decomposition, the connection and unification on mathematics of the signal characteristic spectral representation and the stationary random signal spectral decomposition are revealed.     

Analysis of EMG signals by means of the matched wavelet transform

The authors apply the wavelet transform to the analysis of EMG signals. Exploiting the fact that, under certain conditions, the signal can be considered as the sum of scaled and delayed versions of a single prototype, we have chosen the mother wavelet so as to match the known shape of the basic component. Moreover, the input signal has been Shannon interpolated in order to improve the low scale resolution. The results in terms of MUAP detection and resolution are very encouraging, even in the presence of high levels of noise     

线性调频信号经电离层后距离旁瓣的抑制

电离层探测系统采用线性调频脉冲信号,信号在传输过程中其频谱会受到电离层污染和射频干扰影响,导致距离旁瓣增大和噪声基底抬高,影响回波检测.推导了考虑电离层传输函数的频谱校正表达式,对回波谱进行频谱较正后采用加权技术,与单独采用加权技术主旁瓣抑制比可提高10 dB左右,信干比可提高9 dB左右,同时主瓣扩展系数和信噪比损失与单独采用加权技术相同,大大提高了主旁瓣抑制比和抗干扰能力,提高了回波检测能力.     

Decomposition of intramuscular EMG signals using a heuristic fuzzy expert system

Although increasingly sophisticated algorithms have been proposed to decompose intramuscular electromyography signals into the concurrent activities of individual motor units (MUs), the human operator is still able to improve decomposition results by visual inspection. The rationale for this paper was to combine components from previous decomposition procedures in an expert systems approach utilizing fuzzy logic and attempting to replicate the thought process of an accomplished decomposer in order to minimize the user interaction subsequently needed to enhance decomposition results. The decomposition procedure is discussed and examples are given of the type of information it can yield. The method has been used to identify the discharge activities of up to 15 MUs with up to 95$%$ accuracy.      

Independence of myoelectric control signals examined using a surface EMG model

The detection volume of the surface electromyographic (EMG) signal was explored using a finite-element model, to examine the feasibility of obtaining independent myoelectric control signals from regions of reinnervated muscle. The selectivity of the surface EMG signal was observed to decrease with increasing subcutaneous fat thickness. The results confirm that reducing the interelectrode distance or using double-differential electrodes can increase surface EMG selectivity in an inhomogeneous volume conductor. More focal control signals can be obtained, at the expense of increased variability, by using the mean square value, rather than the root mean square or average rectified value.