Fatigue estimation with a multivariable myoelectric mapping function

A novel approach to muscle fatigue assessment is proposed. A function is used to map multiple myoelectric parameters representing segments of myoelectric data to a fatigue estimate for that segment. An artificial neural network is used to tune the mapping function and time-domain features are used as inputs. Two fatigue tests were conducted on five participants in each of static, cyclic and random conditions. The function was tuned with one data set and tested on the other. Performance was evaluated based on a signal to noise metric which compared variability due to fatigue factors with variability due to nonfatiguing factors. Signal to noise ratios for the mapping function ranged from 7.89 under random conditions to 9.69 under static conditions compared to 3.34-6.74 for mean frequency and 2.12-2.63 for instantaneous mean frequency indicating that the mapping function tracks the myoelectric manifestations of fatigue better than either mean frequency or instantaneous mean frequency under all three contraction conditions.     

Muscle sounds are emitted at the resonant frequencies of skeletalmuscle

The changes in mechanical resonant frequency of whole muscles during twitch and tetanic contractions were compared to changes in frequency components of the pressure wave produced by muscles during contraction. Resonant frequencies were determined by imposing sinusoidal length changes on a muscle and observing transverse standing waves when the frequency of length change matched the muscle's resonant frequency or a harmonic of the resonant frequency. Acoustic signal instantaneous frequency spectrums were calculated using time-frequency transformations including the Wigner transform and the exponential distribution. During a tetanic muscle contraction, the peak instantaneous frequency initially increased and then became constant as the force plateau was reached. The resonant frequencies determined during the force plateau and during relaxation spanned the same range as the peak instantaneous frequency of the acoustic signal. These results suggest that the acoustic signal may be useful as a non-invasive monitor of muscle resonant frequency during contraction.     

Time-frequency parameters of the surface myoelectric signal forassessing 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.     

Electrical manifestations of muscle fatigue during concentric and eccentric isokinetic knee flexion-extension movements

The quantification of the progression of muscle fatigue during a sustained contraction is a valuable tool in several clinical applications, ranging from the evaluation of functional impairment to the development of specific rehabilitative and training protocols. In these fields, great importance is given to isokinetic contractions. The aim of this paper was twofold: first, to propose signal processing methods for assessing the spectral changes of the surface myoelectric signal due to fatigue during isokinetic concentric and eccentric knee flexion-extension movements at a given angular velocity (60 degrees/s); second, to analyze the electrical manifestations of muscle fatigue of four thigh muscles (vastus lateralis, vastus medialis, rectus femoris, and biceps femoris) in the two contraction modalities (i.e. concentric versus eccentric). We demonstrated that, when considering concentric contractions, localized muscle fatigue can be assessed by computing the mean frequency of the frequency marginal of the time-frequency distribution derived from the surface myoelectric signal collected during each contraction cycle. Stronger nonstationarities were observed in the surface myoelectric data recorded within each cyclical movement of the studied eccentric exercise. Thus we propose the computation of the instantaneous mean frequency of the signal based on an original cross-time-frequency algorithm, which proved more sensitive than the frequency marginal in tracking the spectral changes associated with localized muscle fatigue. We derived the average fatigue pattern of the investigated muscles from experimental data recorded from a sample population consisting of twenty healthy subjects and we statistically compared the two contraction modalities. Our results showed that the electrical manifestations of muscle fatigue during concentric contractions were higher than those found during eccentric contractions, although in the latter modality the torque exerted and the mechanical work produced by the subjects were larger than those recorded during the concentric exercise. The results presented in this paper have potential clinical application and they could play an important future role in investigations of muscle behavior during dynamic, highly fatiguing contractions.     

Multivariate analysis of muscular fatigue during bicycle ergometerexercise

The purpose of this study is to estimate the endurance threshold in terms of muscular fatigue during bicycle ergometer exercise. The problems to be solved are induced by dynamic movement and the physiological variation of muscle activity: that is, the progression and impairment of muscle activity occur simultaneously. First of all, the authors used multichannel recordings of myoelectric (ME) signals to reduce the effect by the movement of a bipolar surface electrode relative to the innervation zones. Second, since even the different types of ME parameters contain redundant information on muscular fatigue, the authors used the principal component analysis (PCA) to represent the meaningful information by small dimensions. Moreover, the authors proposed a total evaluation pattern to discriminate muscular fatigue from progression of muscle force at a glance. The total evaluation pattern shows the proportion of first principal component, the components of the first eigenvector, and the correlation coefficients as a function of the work load. The assessment using the total evaluation pattern divided 8 subjects into 3 groups, whereas these subjects were not identified by a specific ME parameter     

Fatigue analysis of the surface EMG signal in isometric constant force contractions using the averaged instantaneous frequency

The averaged instantaneous frequency (AIF) is proposed as an alternative method for the frequency analysis of surface electromyography (EMG) in the study of muscle fatigue during sustained, isometric muscle contractions. Results from performance analysis using experimental EMG signals demonstrate the low variability of the proposed frequency variable. Indeed, the AIF measure is shown to perform significantly better than the widely used mean and median frequency variables, in terms of robustness to the length of the analysis window.     

Dynamic properties of an all solid-state frequency-shifted feedbacklaser

Frequency-shifted feedback (FSF) laser exhibits outstanding features in its oscillation spectrum. We analyze build-up dynamic properties of the FSF laser by means of rate equation and analyze steady-state dynamic properties of the FSF laser by means of Wigner-Ville distribution of intracavity electric field. Furthermore, we analyze instantaneous oscillation frequency at peak spectral intensity and oscillation bandwidth of its spectrum using the formula of instantaneous spectral intensity derived from Wigner-Ville distribution of intracavity electric field. These analytical results are in good agreement with the experimental ones which have been observed by a diode-pumped Nd:YVO₄ FSF laser. It becomes clear that the FSF laser supports many frequency components simultaneously even though the gain medium is homogeneously broadened and has a continuously chirped frequency components of comb in which the creation of chirped frequency components are strongly correlated in phase because of a replica of the preceding components. Also, the instantaneous oscillation frequency is closely related to the detuning frequency which depends on the total net gain in the cavity and the gain bandwidth of atomic transition. The oscillation bandwidth is defined as the product of the saturation-broadened bandwidth and the total resonant modes contributing to FSF operation     

Decision-Theoretic Approach for Classification of Ricker Wavelets and Detection of Seismic Anomalies

Decision-theoretic pattern recognition methods are applied to classifying Ricker wavelets and to detecting waveform anomalies in seismograms. The methods include Bayes decision rule and linear and quadratic classifications. Envelope and instantaneous frequency are extracted as the two features of a seismic trace used as input into the classification schemes. A modified fixed-increment training procedure is employed to solve the decision boundary. The classification schemes successfully distinguish zero-phase Ricker wavelets of different peak frequencies from each other and from random noise.     

A muscular fatigue index based on the relationships betweensuperimposed M wave and preceding background activity

A practical muscle fatigue index is studied in this paper using the correlation between the instantaneous frequencies (IF's) of the superimposed M wave and the mean power frequency (MPF) of the preceding background activity. A superimposed M wave is an M wave elicited during a sustained contraction and was recently introduced for studying muscle fatigue. The authors investigated the details of the distribution of a feature vector (mpf, if) in two-dimensional space. Their experimental results showed that MPF and IF's were closely correlated during the first phase of a short-term high-level sustained voluntary contraction and then became uncorrelated or sometimes showed negative correlation as muscular fatigue progressed. Combining the correlation coefficients and conventional myoelectric (ME) parameters, such as the MPF and the average rectified value of ME signals, the authors propose a fuzzy rule based muscular fatigue index that can be used for managing the inevitable variability among individual subjects collected as a group. Introducing fuzzy inference seemed effective, but further studies including detailed investigation of the level of voluntary effort, the muscle fiber type composition, and metabolic by-products will be needed to customize the membership functions and fuzzy rules more appropriately in each practical field     

基于Hilbert-Huang变换的思维脑电分类技术研究

研究基于Hilbert-Huang变换的思维脑电分类方法.对思维脑电信号进行Hilbert-Huang时频预处理,经经验模式分解后,得到多阶固有模态分量.然后将经HHT变换后的时频窗口内的振幅标准差作为不同心理作业信号特征,再应用K-近邻对思维脑电信号进行分类决策.通过对Colorado州立大学EEG研究中心的三类思维脑电心理作业样本进行分类,平均正确率达到82.54%.经Hilbert-Huang变换得到的脑电信号特征,可以作为思维脑电分类的有效依据.     

改进的相位展开算法及其在瞬时频率估计中的应用

 研究了一种改进的相位展开算法及其在瞬时频率估计中的应用.首先讨论了噪声对相位展开的影响,发现当每个周期内的样本数为2个样本时相位展开具有最佳的性能;接着利用这个性质得到一种简单的相位展开算法,可以在较低信噪比条件下估计出信号的瞬时相位;随后把相位展开算法应用于正弦波频率估计,得到了改进的相位平均法,利用它可以在较低信噪比条件下得到宽带信号的瞬时频率曲线;最后通过MATLAB仿真对算法进行验证.     

基于Gamma深度信念网络的飞行员脑疲劳状态识别

飞行员疲劳状态识别面临两个重要问题,如何提取表征疲劳的特征以及如何对疲劳特征建模学习.首先提取脑电信号节律波,计算基于仿射伪平滑Wigner-Ville分布的瞬时频域信息,构建疲劳状态指标.其次,基于脑电信号各通道的周期性变化提出Gamma深度信念网络的疲劳状态分类算法,与采用卷积与池化运算的学习网络不同,Gamma深度信念网络没有将图像或信号按尺度分割,但在底部的隐藏层已经可以有效地学习特定区域的特征,且当层数增加时,可有效提取特征的区域增多,学习到的特征更为一般化.然后改进用于训练深度信念网络的Gibbs采样算法,提出向上向下Gibbs采样以推断网络参数.最后,实验结果显示,本文的Gamma深度信念网络在识别准确率、稳定性、迭代用时等方面均达到了令人满意的效果.     

Instantaneous frequency and energy distribution of a signal

A theory is derived on a signal representation in an instantaneous frequency vs. time plane. It is observed that the usual frequency vs. time representation does not give a specific pattern for the signal. It is shown that by switching the frequency axis to an instantaneous frequency axis, and by distributing the energy of the signal on an instantaneous frequency vs. time plane it is possible to build up a coherent theory. As an example, patterns of speech signals (sustained vowels) are represented.     

采用基于多相滤波的数字正交变换技术提取信号瞬时特征的方法

本文研究了通信信号瞬时特征的提取方法。采用中频直接采样、抽取和滤波的方法完成信号的正交分解,从而提取信号的瞬时包络和相位主值序列。利用信号相位去卷叠算法和线性规划法估计信号的去卷叠瞬时非线性相位,利用傅里叶变换的微分特性估计信号的瞬时频率。通过文中的方法可以有效估计信号的瞬时特征,将其运用于信号调制体制识别取得了较好的效果。     

Frequency Parameters of the Myoelectric Signal as a Measure of Muscle Conduction Velocity

Dunrng a sustained muscle contraction, the spectrum of the myoelectric signal is known to undergo compression as a function of time. Previous investigators have shown that the frequency compression is related to the decreasing conduction velocity of the muscle fibers. It is proposed that the frequency compression may be tracked by obtaining a continuous estimate of a characteristic frequency of the spectrum, such as the mean and median, or the ratio of low-frequency components to high-frequency components of the spectrum. A theoretical analysis was performed to investigate the restrictions in estimating the three parameters, as well as their sensitivity to the conduction velocity. The ratio parameter was found to be most sensitive to conduction velocity, but was the least reliable of the three. The median frequency was the least sensitive to noise. Therefore, from a theoretical point of view, the median frequency is the preferred parameter. A technique is described which determines an unbiased consistent estimate of the median frequency. The technique may be readily implemented in analog hardware.     

Doppler estimation using a coherent ultrawide-band random noiseradar

The University of Nebraska has developed an ultrawide-band (UWB) coherent random noise radar operating over the 1-2 GHz frequency range. The system achieves phase coherence by using heterodyne correlation of the received signal with a time-delayed frequency-shifted replica of the transmit waveform. Knowledge of the phase of the received signal and its time dependence due to target motion permits the extraction of the mean Doppler frequency from which the target speed can be inferred. Theoretical analysis, simulation studies, and laboratory measurements using a microwave delay line showed that it was possible to estimate the Doppler frequency from targets with linear as well as rotational motion. Field measurements using a photonic delay line demonstrated the success of this technique at a range of about 200 m at target speeds of up to 9 m/s. Analysis shows that the accuracy with which the Doppler frequency can be estimated depends not only on the phase performance of various components within the system, but also upon the random nature and bandwidth (BW) of the transmit waveform, and the characteristics of unsteady target motion     

A model for wafer scale variation of removal rate in chemical mechanical polishing based on elastic pad deformation

It is well known that within wafer non-uniformity (WIWNU), due to the variation in material, removal rate (MRR) in the whole wafer plays an important role in determining the quality of a wafer planarized by CMP. Various material removal models also suggest that the MRR is strongly influenced by the interface pressure. In the present work, an analytical expression for pressure distribution at the wafer and pad interface is developed. It is observed that depending on the wafer curvature and polishing conditions, the interface pressure may exhibit significant variation. The analytical model predictions are first verified against finite element method (FEM) simulations. The predicted analytical pressure profiles are then utilized in Preston's equation to estimate the MRR, and these MRR predictions are also compared to experimental observations. The analytical results suggest, that for a specified wafer curvature there exists a certain polishing condition (and vice versa) that will enable holding the WIWNU within a specified tolerance band. The proposed model facilitates the design space exploration for such optimal polishing conditions.     

基于过零点-极点估计的瞬时频率幅度算法

Hilbert-Huang变换(HHT)理论通过经验模态分解(EMD)提取信号的内蕴模态函数(IMF),并对IMF利用Hilbert变换得到信号的时频幅度谱和边际谱。在总结Hilbert变换理论和算法实现局限性的基础上,提出基于过零点-极点估计求取IMF瞬时频率、幅度算法,通过对离散信号插值运算精确求取过零点和极点位置,并据此求出相应点的瞬时频率和幅度,最后采用三次样条求取信号的瞬时频率幅度曲线。通过几个典型的例子对该算法进行检验,结果表明,与Hilbert变换结果比较,借助该算法得到信号的时频幅度谱和边际谱结果更精确、频率分辨率更好。     

Dispersion penalty analysis for VSR-1 optical links

This paper presents an approach to calculate dispersion penalty for VSR-1 optical links. Based on parameters of a specific VSR-1 link, dispersion penalties are computed for various modal dispersion bandwidths respectively. The worst-case eye closure is expressed numerically by using the signal waveform at time 0, and the signal waveform is obtained in frequency domain through FFT algorithm. By this approach,the dispersion penalty is determined by the shape of transfer functions of the various components in the links. To simplify the derivation of multimode fiber link transfer function,a Gaussian form of normalized impulse response is used. This calculation approach can be used to estimate the worst-case dispersion penalty of VSR-1 links in the link budget analysis.     

应用频率积分相位解调测量径向畸变

为了测量光学成像系统的径向畸变,采用载频条纹模板,应用瞬时频率积分法提取因径向畸变而产生的径向调制相位;推导了条纹径向调制相位与瞬时频率的关系式,并导出径向调制相位和径向畸变位移关系;采用小波频率估计提取畸变条纹径向瞬时频率,并对其进行积分获得畸变条纹的径向调制相位;应用径向调制相位和立方卷积插值算法对畸变图像进行了校正,得出了详细的理论分析和实验结果。结果表明,上述方法是可行的。