Quantifying proprioceptive reflexes during position control of the human arm

This study aimed to analyse the dynamic properties of the muscle spindle feedback system of shoulder muscles during a posture task. External continuous force disturbances were applied at the hand while subjects had to minimize their hand displacements. The results were analysed using two frequency response functions (FRFs) from which the model parameters were derived, being 1) the mechanical admittance and 2) the reflexive impedance. These FRFs were analysed by a neuromusculoskeletal model that implicitly separates the reflexive feedback properties (position, velocity and acceleration feedback gains) from intrinsic muscle visco-elasticity. The results show substantial changes in estimated reflex gains under conditions of variable bandwidth of the applied force disturbance or variable degrees of external damping. Position and velocity feedback gains were relatively larger when the force disturbance contained only low frequencies. With increasing damping of the environment, acceleration feedback gain decreased, velocity feedback gain remained almost constant and position feedback gain increased. It is concluded that under the aforementioned circumstances, the reflex system increases its gains to maximize the mechanical resistance to external force disturbances while preserving sufficient stability.     

Galvanic vestibular stimulation elicits consistent head-neck motion in seated subjects

Humans actively stabilize the head-neck system based on vestibular, proprioceptive and visual information. Galvanic vestibular stimulation (GVS) has been used previously to demonstrate the role of vestibular feedback in standing balance. This study explores the effect of GVS on head-neck kinematics and evaluates the approach to investigate the vestibular contribution to head-neck stabilization. GVS was applied to 11 seated subjects using seven different stimuli (single sinusoids and multisines) at amplitudes of 0.5-2 mA and frequencies of 0.4-5.2 Hz using a bilateral bipolar configuration while 3-D head and torso kinematics were recorded using motion capture. System identification techniques were used evaluating coherence and frequency response functions (FRFs). GVS resulted in significant coherence in roll, yaw and lateral translation, consistent with effects of GVS while standing as reported in the literature. The gain of the FRFs varied with frequency and no modulation was observed across the stimulus amplitudes, indicating a linear system response for the stimulations considered. Compared to single sine stimulation, equivalent FRFs were observed during unpredictable multisine stimulation, suggesting the responses during both stimuli to be of a reflexive nature. These results demonstrate the potential of GVS to investigate the vestibular contribution to head-neck stabilization.     

Nonlinear Spatial Filtering of Multichannel Surface Electromyogram Signals During Low Force Contractions

This study introduces the application of nonlinear spatial filters to help identify single motor unit discharge from multiple channel surface electromyogram (EMG) signals during low force contractions. The nonlinear spatial filters simultaneously take into account the instantaneous amplitude and frequency information of a signal. This property was used to enhance motor unit action potentials (MUAPs) in the surface EMG record. The advantages of nonlinear spatial filtering for surface MUAP enhancement were investigated using both simulation and experimental approaches. The simulation results indicate that when compared with various linear spatial filters, nonlinear spatial filtering achieved higher SNR and higher kurtosis of the surface EMG distribution. Over a broad range of SNR and kurtosis levels for the input signal, nonlinear spatial filters achieved at least 32 times greater SNR and 11% higher kurtosis for correlated noise, and at least 15 times greater SNR and 1.7 times higher kurtosis for independent noise, across electrode array channels. The improvements offered by nonlinear spatial filters were further documented by applying them to experimental surface EMG array recordings. Compared with linear spatial filters, nonlinear spatial filters achieved at least nine times greater SNR and 25% higher kurtosis. It follows that nonlinear spatial filters represent a potentially useful supplement to linear spatial filters for detection of motor unit activity in surface EMG at low force contractions.     

星地双基地SAR时频同步技术研究

本文研究了只依靠直达波信号的星地双基地SAR的时频同步误差估计方法并对估计精度进行了讨论。首先对直达波信号进行建模和分析,再对传统的基于幅度的多普勒中心频率的估计方法在双基地SAR情况下进行了估计结果的修正,从而提出了一种时频同步误差的估计方法。最后推导并分析了接收信号的信噪比、系统载频和带宽等因素与估计精度的定量关系。结果表明,当先验信息较少时,仅通过直达波数据进行同步误差的估计是可行的。由于误差估计精度由信号的信噪比、信号带宽和载频频率等因素共同决定。因此,需要对系统参数进行合理的设计,以实现高精度的误差估计,从而实现同步误差的补偿,提高双基地SAR的成像质量。      

Robust disturbance rejection for improved dynamic stiffness of a magnetic suspension stage

Magnetic suspension is an attractive approach in realizing ultraprecision multiple-degree-of-freedom actuation for precision engineering. However, improving the dynamic stiffness of magnetic-suspension systems is an engineering challenge due to their noncontact nature. Two disturbance rejection algorithms that improve the dynamic stiffness of a magnetic-suspension stage (MSS) are presented in this paper. For rejection of narrow-band disturbances with unknown frequencies, an internal model principle-based control together with a frequency estimation algorithm based on adaptive-notch filtering is proposed. A chattering-free sliding mode (CFSM) disturbance rejection algorithm is developed in order to reject wide-band disturbances. The CFSM disturbance rejection scheme includes a continuous approximation of the switching function to avoid chattering, an integral control term to reduce the switching magnitude, and a derivative control term to elevate the bandwidth of disturbance rejection. Experimental results verified that the disturbances can be effectively rejected with the two developed algorithms. Consequently, the dynamic stiffness of the MSS is greatly improved.     

The effect of electrode arrangement on spectral distance measuresfor discrimination of EMG signals

The proper electrode placement in applying cepstral coefficients for electromyogram (EMG) signature discrimination was investigated. The authors measured EMG signals of different motions with two electrode arrangements simultaneously. Electrode pairs were located separately on dominant muscles (S-type arrangement) and closely in the region between muscles (C-type arrangement). The application of the cepstral method to signals derived from a C-type arrangement did not achieve the same discrimination as with a S-type arrangement. The authors used a simplified model to elucidate the poor performance in C-type signals. The bandwidth of signals obtained from S-type placement is wider than that from C-type. Narrower bandwidth decreases the importance of the more discriminative parts for both autoregressive (AR) and cepstral methods. The cepstral method is more sensitive to such variation, so the degradation in performance is more serious for the cepstral method. Second, the amplitude of C-type signal is lower than the S-type; therefore, the C-type signal is more sensitive to the disturbance of noise, especially in the high-frequency band. As high-frequency noise increases, the spectral difference between different EMG signals is gradually dominated by the low-frequency part, which is more informative. Thus, the performances of both methods are improved with increasing high-frequency noise. The improving rate of the AR method is faster than the cepstral method; therefore, its discriminative efficiency may exceed the cepstral method with C-type arrangement     

基于QPF的LFM信号参数估计算法性能分析

基于二次相位函数的LFM信号参数估计算法计算量小、估计精度高,在雷达机动目标检测、目标运动参数估计和电子对抗等应用系统中有较好的应用前景,本文对该方法的性能和参数选取问题进行了研究,推导了输出信噪比与输入信噪比及信号长度关系的表达式,补充了文献中均方误差理论分析的高信噪比条件,给出了一种工程应用中保证可靠检测和高估计精度所需数据长度的确定方法,最后分析了QPF算法对多分量LFM信号环境的适用性.     

一种实用的通信信号信噪比盲估计方法

提出了一种简单实用的无线通信信号信噪比盲估计方法。信号功率分布函数中的拐点是与信号频带有关的重要信息参数,通过检测该参数可精确估计信号的带宽和信噪比。对该方法的信号参数适应能力进行了理论分析和计算机仿真,结果表明,新方法无需任何先验信息,运算量小、精度高,适于硬件实现。     

Estimation of muscle fiber conduction velocity with a spectral multidip approach

We propose a novel method for estimation of muscle fiber conduction velocity from surface electromyographic (EMG) signals. The method is based on the regression analysis between spatial and temporal frequencies of multiple dips introduced in the EMG power spectrum through the application of a set of spatial filters. This approach leads to a closed analytical expression of conduction velocity as a function of the auto- and cross-spectra of monopolar signals detected along the direction of muscle fibers. The performance of the algorithm was compared with respect to that of the classic single dip approach on simulated and experimental EMG signals. The standard deviation of conduction velocity estimates from simulated single motor unit action potentials was reduced from 1.51 m/s [10 dB signal-to-noise ratio (SNR)] and 1.06 m/s (20 dB SNR) with the single dip approach to 0.51 m/s (10 dB) and 0.23 m/s (20 dB) with the proposed method using 65 dips. When 200 active motor units were simulated in an interference EMG signal, standard deviation of conduction velocity decreased from 0.95 m/s (10 dB SNR) and 0.60 m/s (20 dB SNR) with a single dip to 0.21 m/s (10 dB) and 0.11 m/s (20 dB) with 65 dips. In experimental signals detected from the abductor pollicis brevis muscle, standard deviation of estimation decreased from (mean +/- SD over 5 subjects) 1.25 +/- 0.62 m/s with one dip to 0.10 +/- 0.03 m/s with 100 dips. The proposed method does not imply limitation in resolution of the estimated conduction velocity and does not require any iterative procedure for the estimate since it is based on a closed analytical formulation.     

一种基于奇异值分解的改进信噪比盲估计算法

针对空间分解类信噪比(SNR)估计算法中子空间维数估计复杂度较高,低信噪比下估计偏差较大的问题,提出了一种改进的子空间维数估计算法。该算法首先利用样本自相关矩阵的奇异值序列进行后向差分得到梯度序列,对梯度序列每一项与后5项之和的比值进行搜索,最大比值所对应的奇异值序号作为信号子空间维数,最后计算信噪比。合适数据长度下的仿真结果表明：在信噪比-5 dB~20 dB范围内,常规通信信号的信噪比估计平均偏差小于0.5 dB,标准差小于1 dB;该算法提升了低信噪比下的估计性能,运算量较小,无需知道调制方式、载波频率、符号率等先验信息,在低信噪比时对信噪比时变的跟踪估计更为准确,且对复杂高阶调制信号同样适用。     

欠采样条件下基于DCS的LFM信号带宽估计方法

针对传统方法不适用于欠采样条件下线性调频(LFM)信号在低信噪比(SNR)条件下带宽估计问题,提出一种基于分布式压缩感知(DCS)的带宽估计方法,利用同一信源多个脉冲的联合稀疏特性进行LFM信号带宽估计。首先构建LFM欠采样信号模型,其次利用DCS算法对LFM带宽进行联合稀疏重构,然后分析了所提LFM信号带宽估计方法性能,最后利用仿真验证了方法的可行性和有效性。     

Pivot friction compensation using an accelerometer and adisturbance observer for hard disk drives

This paper considers a pivot friction compensator using the combination of an accelerometer and a disturbance observer. Noting that the pivot torque bias due to uncertain disturbances and nonlinearities such as pivot friction is approximately the difference between the scaled voice-coil motor (VCM) current and the scaled carriage angular acceleration, a disturbance observer to estimate the bias can be constructed using the above two continuously measured signals. By feeding back the bias estimate into the VCM amplifier, the frequency response from the VCM current to the carriage angular acceleration is linearized to be a constant gain within the observer bandwidth. The proposed cancellation scheme provides wider bandwidth bias rejection and better settling performance than traditional bias compensation schemes. Experiments have confirmed that the cancellation scheme is effective in the frequency range 0-700 Hz     

Simultaneous and proportional force estimation in multiple degrees of freedom from intramuscular EMG

This letter investigates simultaneous and proportional estimation of force in 2 degree-of-freedoms (DoFs) from intramuscular electromyography (EMG). Intramuscular EMG signals from three able-bodied subjects were recorded along with isometric forces in multiple DoF from the right arm. The association between five EMG features and force profiles was modeled using an artificial neural network. Correlation coefficients between the measured and the estimated forces were 0.85 ± 0.056 and 0.88?± 0.05 without and with post processing, respectively. The results showed that force can be estimated in 2 DoFs with high accuracy and that the degree of performance depended on the force function (task) to be estimated.     

多载波基带信号相参时差估计算法与分析

时差估计精度与信号在频域上的分布情况以及信号能量和噪声有关。多载波信号的频率信息和能量在频域上分布区间大,通过多载波信号的相参积累,可以有效利用信号在整个区间内的频域信息和能量来提高时差参数的估计精度,克服单载波信号带宽窄能量低导致的时差估计精度不高的问题.本文针对多载波基带信号的时差估计问题,在单载波基带信号互相关函数分析的基础上,推导了多载波基带信号互相关函数,并分析了其相位关系,通过相位补偿实现了多载波基带信号互相关函数的相参积累,并理论分析了多载波信号时差参数估计性能与信号各参数的关系。蒙特卡洛仿真表明,提出的多载波基带信号相参时差估计算法性能明显优于单载波信号的估计性能,性能改善情况与理论分析一致。      

Adaptive fuzzy impedance control of exoskeleton robots with electromyography-based convolutional neural networks for human intended trajectory estimation

Among various uses of exoskeleton robots, the rehabilitation of stroke patients is a more recent application. There is, however, considerable environmental uncertainty in such systems including uncertain robot dynamics, unwanted user reflexes, and, most importantly, uncertainty in user intended trajectory. Hence, it is challenging to develop transparent, stable, and wide-scale exoskeleton robots for rehabilitation. This paper proposes an adaptive fuzzy impedance controller (AFIC) and a convolutional neural network (CNN) which uses electromyographic (EMG) signals for early detection of human intention and better integration with a lower limb exoskeleton robot. Specifically, the primary purpose of the AFIC is to manage the mechanical interaction between human, robot, and environment and to deal with uncertainties in internal control parameters. CNN uses EMG signals, inertial measurement units, foot force sensing resistors, joint angular sensors, and load cells to deal with signal uncertainties and noise through automatic feature processing in order to detect user’s desired joint angles with high accuracy. EMG is particularly effective here since it reflects the human intention to move faster than the other mechanical sensors. In the experimental procedure, signals were sampled at 500 Hz as two healthy individuals walked normally at 0.3, 0.4, 0.5, and 0.6 m/s for eight minutes while wearing a robot with zero inertia. Approximately 70% of the data is used for training and 30% for testing the network. The estimated angle from the trained network is then used as the desired angle in the AFIC loop, which controls the robot online as the desired trajectory. Pearson correlation coefficient and normalized root mean square error are computed to evaluate the accuracy and robustness of the proposed angle estimation with CNN and AFIC algorithms. Experimental results show that the proposed approach successfully obtains the torque of the robot joints despite uncertainties in changing the walking speed.     

Blind Joint Estimation for OFDM Time-Frequency Parameters

A novel blind joint estimation of orthogonal frequency division multiplexing (OFDM) time-frequency parameters is conceived in low signal-to-noise ratio (SNR) and multipath channel conditions. The oversampling factor is estimated by employing a new-designed cosine roll-off filter whose cut-off frequency is considered as the approximation of the sampling signal’s spectrum. The useful data length is estimated by means of the improved varying time-delay autocorrelation, and its final estimated value is defined as a power of 2, which has the minimum Euclidean distance with the peak position. The estimated useful data length is further utilized to refine the previous estimation of the oversampling factor. The bandwidth of OFDM signals is estimated by adopting the spectrum approximation method based on the estimated time-parameters. The simulation results demonstrate that the proposed method is robust to noise and multipath channel conditions without any requirement of a prior knowledge.     

一种提高海洋SAR定位精度的方法

在无参考点海洋SAR定位方法中,多普勒中心频率估计对定位精度有着重要的影响。该文从理论和仿真两个角度研究了信噪比对多普勒中心频率估计的影响,给出了多普勒中心频率和信噪比的理论及仿真关系曲线。在此基础上针对海洋回波信号较弱的特点,在海洋SAR系统设计中增加一个多普勒测量模式。和普通成像模式相比,该模式通过降低带宽的方式来提高回波的信噪比,从而提高了定位精度。     

一种改进的Fitz载波频偏估计方法及其仿真

为了解决低信噪比条件下载波频偏估计中估计范围和估计精度的矛盾,在比较分析现有经典估计方法的基础上,提出了一种改进的Fitz载波频偏估计方法,利用自相关序列差分代替自相关序列相位估计频偏。此方法将频偏估计范围提高到数据速率的一半,同时又保持了原有Fitz方法的低信噪比门限。通过仿真验证了改进频偏估计方法对大频偏和低信噪比的适用性。     

Fast detection and DOA estimation of the unknown wideband signal sources

The direction of arrival (DOA) estimation analysis requires prior knowledge of frequency‐related information of the incident wideband signals, eg, center frequency and bandwidth, which are not available in many cases. This research is based on applications where DOA estimation of the wideband signal source is unknown, eg, in astronomy and unauthorized transmissions. Therefore, this paper has two major contributions. The first contribution is to identify the frequency spectrum of the wideband signals transmitted from an unknown source. The method use edge detection prestage to identify the frequency spectrum of the received signal. The second contribution is to estimate the DOA of the wideband signal at higher accuracy while keeping a minimum computational cost. The estimation of the DOAs was analyzed by measuring the orthogonal relationship between the signal and the noise subspaces of multiple frequency components of the sources. The introduced method utilizes subband as a reference frequency based on the extracted frequency‐related information rather than examining the complete incoming signal spectrum and exploits the spatial information of a few subbands. The introduced algorithm is implemented based on the well‐known method, test of orthogonality of projected subspaces (TOPS). Tests are conducted on a range of wideband signals with extreme values of signal‐to‐noise ratio (SNR). Considerable performance improvement is obtained.     

分数阶Fourier变换对LFM信号的特征参数估计能力仿真评估

将分数阶傅里叶变换（FrFT）对线性调频（LFM）信号处理方法应用到雷达侦察信号分选与参数估计中,研究FrFT对LFM信号在低信噪比下的检测与参数估计能力。设定了雷达侦察信号背景,制定了仿真验证流程,考察了FrFT对LFM信号的调频率和中心频率的估计能力,对比了不同信噪比下的参数估计运算时间。仿真结果验证了该算法可以完成低信噪比条件下雷达侦察LFM信号特征参数的估计。