Mohammed Ferdjallah

Correlation of muscle fatigue indices between intramuscular and surface EMG signals

The root mean square (RMS), the average rectified value (ARV), and the mean frequency (MNF) are indices of muscle fatigue. In this paper, the relationship between the muscle fatigue and these metrics was examined. The correlation among the muscle fatigue indices was also considered by plotting the normalized metrics of surface versus intramuscular EMG. The EMG data was divided into equal segments, and the metrics were calculated in each segment. The calculated metrics were plotted in time domain, and linear regression analysis was performed to find the tendencies and relationships between surface and intramuscular metrics. As the muscle fatigue progressed, the slope of RMS and ARV increased, while that of MNF deceased. For the normalized RMS, ARV, and MNF, the surface versus intramuscular EMG was plotted, and their correlations were examined. Compared with normalized RMS and AR Vplots, the normalized MNF showed a slower change-rate.

Muscle Fatigue Analysis for Healthy Adults Using TVAR Model with Instantaneous Frequency Estimation

The objective of this paper is to design a nonstationary time-varying autoregressive (TVAR) cascaded model to analyze electromyography (EMG) signals by using instantaneous frequency for muscle fatigue assessment. EMG is commonly used in the muscle fatigue study during muscle contractions by analyzing myoelectric signal spectrum. To validate the findings, our results are compared with the conventional short time Fourier transform (STFT) method. STFT has limitations in joint time frequency resolution for long intervals, whereas TVAR models overcome these limitations for nonstationary signals. In this study, EMG data recorded from the rectus femoris muscle are used to characterize muscular fatigue. Characterizations are done by using mean frequencies (MNF). According to our results, the new method has a better accuracy in signal representation, frequency resolution and joint time distribution

A new approach for muscle fatigue analysis in young adults at different MVC levels

Spectral parameters such as the mean and the median frequencies have been documented to be reliable outcome variables for the assessment of muscle fatigue. However when recorded for long intervals, electromyography signals become non-stationary. Short-time Fourier transform (STFT) has been extensively used for computing the electromyography time-varying spectrum, but the joint time-frequency resolutions of the STFT is inherently limited. A new time varying auto regressive (TVAR) model is proposed to analyze EMG signals which does not have joint time frequency resolution limitations. The objective of this paper is to examine surface EMG signals of healthy young subjects at different levels of maximum voluntary contractions (MVC) and to analyze spectral shifts in mean frequencies (MNF) using STFT and TVAR models. Our results show, TVAR has a better accuracy in signal representation and high frequency resolution. Further, spectral estimation can be obtained even for shorter data sequence. In this study, continuous stream of EMG data sets from lower extremity muscles are used to characterize muscular fatigue at different MVC level. EMG data were recorded from the Rectus Femoris muscles during isometric contractions

Adaptive autoregressive model for the analysis of center of pressure in healthy subjects during quiet standing

Postural stability is defined as the ability to maintain or control body center of mass (CoM) in relation to the base of support to prevent falls and complete desired movements. The center of pressure (CoP) is an indirect measure of postural sway and measured in anterior-posterior (A-P) and medial-lateral (M-L) planes. The objective of this paper is to design a second order adaptive autoregressive (AR) model to estimate the model parameters and investigate the mean and peak frequencies from CoP data collected in both eyes open (EO) and eyes closed (EC) trials in healthy subjects. The performance of the AR model was compared to that of the fast Fourier transform (FFT). Peak frequency was observed to provide a better resolution than mean frequency. The second order adaptive AR model designed in this study offered an important metric, namely peak frequency, for postural stability analysis. It also provided means to estimate biomechanical parameters for postural stability, which would be the focus of further research

Time varying stochastic channel modeling of wireless DS-CDMA ad-hoc networks using different mobility models

The time varying nodes mobility and environmental changes in traditional ad-hoc channel creates limitation in signal propagation. In this study, a stochastic dynamic ad-hoc channel model is introduced with state space representation to overcome these limitations. The models parameters are computed from the approximation of Doppler spectrum. The performance of this stochastic ad-hoc direct sequence spread spectrum (DS-CDMA) wireless network in a flat fading channel is also investigated in this article. It is documented that the shape of the Doppler spectrum in a cellular network is considerably different than that of an ad-hoc network because of double mobility and speed. In this paper, the performance in terms of capacity and bit error rate (BER) under varying degrees of double mobility is demonstrated using simulation technique for stochastic ad-hoc model. As the degree of double mobility increases when the maximum Doppler shift is fixed, we observe that the capacity (number of users that can be supported) of DS-CDMA ad-hoc networks is higher than that of cellular networks because double mobility mitigates fading.

Adaptive IIR constrained LMS algorithm for multiple narrowband interference rejection

One of the common problems in digital signal processing is the filtering of signals in the presence of a narrow-band interference. Adaptive IIR digital multiple hand-rejection filters use pole-zero placement on the unit circle method, which is designed by a unique second-order filter structure. With unconstrained LMS algorithm, zeroes may converge to their optimum positions in certain cases, where the poles do not converge without a forcing condition. In this paper, a new design of adaptive digital band-rejection filter, constrained least-mean-squares (CLMS), is applied by adapting both poles and zeroes for the elimination of a narrow-band white Gaussian noise.

Nerve conduction topography in geriatric hand assessment.

Motor nerve conduction is a noninvasive clinical test used to diagnose nerve problems such as carpal tunnel syndrome or peripheral neuropathy. Current techniques use a single-site recording over a superficial muscle. This traditional approach does not account for the electrical contributions from the other muscles innervated by the nerve being stimulated, which need to be considered with thumb carpometacarpal (CMC) degenerative joint disease (DJD) because these electrical contributions may change the anatomic relationship of the thenar muscles. This study recorded from 15 sites over the thenar eminence during motor nerve conduction studies of the median nerve of 12 young subjects with normal thenar anatomy and 25 elderly subjects with thumb CMC DJD. The maximum compound muscle action potential (CMAP) values did not occur in the same electrode position for the two groups, and traditional single-site recording would have resulted in smaller amplitudes and longer latencies for the elderly than the values noted with the multiple-site recordings. This pilot study of nerve conduction topography mapping with multiple-site recording illustrates that single-site studies may be misleading and supports further exploration of multichannel grid electrodes for topographic display and analysis of the CMAP.

Proposed model for skeletal muscle: Estimation of fiber location using ultrasonic effect

Electromyography (EMG) used to discover diseases of the muscles, spinal cord, and peripheral nerves is a diagnostic test, which records the electrical responses of skeletal muscles while at rest and during voluntary action and electrical stimulation. A novel method, ultrasound modulated EMG, is proposed in this study as a mode of determining the location of fiber producing action potential. Frequency dependent attenuation of ultrasound is observed in skeletal muscle. The attenuation at different ultrasonic frequencies, which modulate EMG signal, assists to locate the source.

A New Tvar Modeling in Cascaded Form for Nonstationary Signals

In the nonstationary process identification, a time varying autoregressive (TVAR) model may possess temporal model instability in the conventional direct form. In this study, we propose a new TVAR cascaded form to overcome model instability. The model stability in TVAR the cascaded form is accomplished through the parameterization of time varying poles using pole tracking and monitoring methods. Our simulation on synthetic data demonstrates that the TVAR cascaded form stability can easily be achieved, monitored, and controlled. The performance evaluation of TVAR cascaded model has shown that the Cartesian coordinate with orthogonal representation performs better than other pole representation

Design of Two-Dimensional Grid Electrodes Considering Spatial Characteristics of SEMG Signal

Surface grid electrode is a noninvasive technique, which can be utilized for topographic analysis of EMG signals. Grid electrode increases the uptake area and provides a better picture of spatial and temporal characteristics of muscle activity. Determination of clinical parameters such as muscle conduction velocity, location of innervation zone, firing pattern, size and location of motor unit, are some of the challenging applications of multi-electrode array. However, an optimum grid electrode requires detail examination regarding the dimension and inter-electrode distance of the array. In this paper a systematic approach is presented for selecting a grid spacing to reduce spatial aliasing. The characteristics of isotropic layers of subcutaneous fat and skin tissues are incorporated in a computer muscle model in order to analyze their effects on complete potential profile and grid spacing. The variation of spatial cutoff frequency and corresponding inter electrode distance with depth of muscle fiber inside the muscle are simulated in both time and frequency domain for three different levels of accuracy