Mohammad A. Ahad

Electrical characteristics of rat skeletal muscle in immaturity, adulthood and after sciatic nerve injury, and their relation to muscle fiber size

Localized impedance methods can provide useful approaches for assessing neuromuscular disease. The mechanism of these impedance changes remains, however, uncertain. In order to begin to understand the relation of muscle pathology to surface impedance values, 8 immature rats, 12 mature rats and 8 mature rats that had undergone sciatic crush were killed. Measurement was made on tissue from the gastrocnemius muscle from each animal in an impedance cell, and the conductivity and relative permittivity of the tissue were calculated in both the longitudinal and transverse directions for frequencies of 2 kHz to 1 MHz. In addition, quantitative histological analysis was performed on the tissue. Significant elevations in transverse conductivity and transverse relative permittivity were found with animal growth, but longitudinal values showed no difference. After sciatic crush, both transverse and longitudinal conductivity increased significantly, with no change in the relative permittivity in either direction. The frequency dependence of the values also changed after nerve injury. In the healthy animals, there was a strong linear relation between measured conductivity and relative permittivity with cell area, but not for the sciatic crush animals. These results provide a first step toward developing a comprehensive understanding of how the electrical properties of muscle alter in neuromuscular disease states.

Electrical impedance myography at 50 kHz in the rat: Technique, reproducibility, and the effects of sciatic injury and recovery

OBJECTIVE To describe a refined technique for performing electrical impedance myography (EIM) in the rat and assess its reproducibility, long-term stability, and the effects of sciatic nerve injury. METHODS EIM at 50kHz was performed on the gastrocnemius-soleus complex of the rat hind limb in 12 rats, followed from 6 weeks of age for up to 6 months. Eight additional rats underwent sciatic nerve crush and 6 underwent a sham procedure. RESULTS The EIM variables of resistance, reactance and phase demonstrated substantial change with growth until approximately 14 weeks of age, at which point the measurements stabilized, giving mean values of 6.0+/-5.7Omega, 22.1+/-2.1Omega, and 16.5+/-1.1 degrees , respectively, at 16 weeks of age. Immediate reproducibility of technique was high with an intraclass correlation coefficient of 0.91 and higher for all three parameters. Sciatic crush produced marked reductions in the reactance and phase that reversed over a several week period. CONCLUSIONS These results support that 50kHz EIM can be performed effectively in adult rat models of neuromuscular disease with a straightforward experimental technique and that it is sensitive to neurogenic injury. SIGNIFICANCE EIM can serve as a new approach to the study of neuromuscular disease in the rat.

Assessment of Alterations in the Electrical Impedance of Muscle After Experimental Nerve Injury via Finite-Element Analysis

The surface measurement of electrical impedance of muscle, incorporated as the technique of electrical impedance myography (EIM), provides a noninvasive approach for evaluating neuromuscular diseases, including amyotrophic lateral sclerosis. However, the relationship between alterations in surface impedance and the electrical properties of muscle remains uncertain. In order to investigate this further, a group of healthy adult rats, a group of rats two weeks postsciatic crush, and a group of animals six months postcrush underwent EIM of the gastrocnemius-soleus complex. The animals were then killed and the conductivity and permittivity of the extracted muscle measured. Finite-element models based on MRI data were then constructed for each group. The characteristic EIM parameter, 50 kHz phase (±standard error), obtained with surface impedance measurements was 17.3° ± 0.3° for normal animals, 13.8° ± 0.7° for acutely injured animals, and 16.1° ± 0.5° for chronically injured animals. The models predicted parallel changes with phase values of 24.3°, 18.8°, and 21.2° for the normal, acute, and chronic groups, respectively. Other multifrequency impedance parameters showed similar alterations. These results confirm that surface impedance measurements taken in conjunction with anatomical data and finite-element models may offer a noninvasive approach for assessing biophysical alterations in muscle in neuromuscular disease states.

The effect of subacute denervation on the electrical anisotropy of skeletal muscle: Implications for clinical diagnostic testing

OBJECTIVE Applied electrical current flows preferentially along rather than across muscle fibers, a characteristic called anisotropy. In this study, we investigate the alteration in muscle anisotropy after denervation. METHODS Eight adult male rats underwent sciatic nerve crush and the gastrocnemius was harvested from 1 to 2.5 weeks later. Muscle from 12 additional healthy rats was also obtained. Multifrequency electrical impedance measurements were made on the tissue and its conductivity and relative permittivity (i.e., its polarizability) calculated. Anisotropy of the tissue was determined by calculating conductivity and permittivity differences, subtracting transverse from longitudinal values. Muscle fiber and blood vessel quantification were also performed. RESULTS The mean conductivity difference for sciatic crush animals was higher (p<0.05) than for the healthy animals across the frequency spectrum, due to a greater increase in longitudinal conductivity than in transverse conductivity. For example, at 10 kHz, the conductivity difference was 0.15S/m for healthy animals and 0.29 S/m for post-crush animals. Relative permittivity difference values, however, were similar between groups. There was a strong correlation of conductivity anisotropy to muscle fiber size but not to blood vessel area. CONCLUSIONS Anisotropy of muscle conductivity increases markedly after subacute denervation injury. SIGNIFICANCE This alteration in anisotropy has direct relevance to the clinical application of electrical impedance myography. We also speculate that it may impact other forms of diagnostic testing, including needle electromyography and magnetic resonance imaging.

Finite element analysis of electrical impedance myography in the rat hind limb

Electrical impedance myography (EIM) is a form of muscle assessment based on the surface application of electrical current and measurement of the resulting voltages over a muscle group of interest. In order to better understand the effect of pathological change in muscle, EIM has recently been applied to the rat. In this study, a finite element model of EIM is presented for the rat hind limb which incorporates the detailed anatomy of the leg based on computerized tomographic imaging and conductivity and permittivity values obtained from the rat gastrocnemius muscle. In addition, the angular anisotropy of the biceps femoris muscle has been included. The model successfully predicts the recorded surface impedances measured with EIM.

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.

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

A multiuser EEG based imaginary motion classification using neural networks

Using Electroencephalography (EEG) to detect imaginary motions from brain waves to interface human and computer is a very nascent and challenging field that started developing rapidly in the past few decades. This technique is termed as Brain Computer Interface (BCI). BCI is extremely important in case of people who are incapable of communicating due to spinal cord injury. This technique uses the brain signals to make decisions, control and communicate with the world using brain integration with peripheral devices and systems. In this paper, in order to classify imaginary motions, raw data are used to train a system of neural networks with a majority vote output. EEG data for 3 subjects are used from the BCI Competition III dataset V. Each subject has data collected in three sessions representing three different types of imaginary motions. Using an optimized set of electrodes, classification accuracy was optimized for the three users as a group. A cross validation method is applied to improve the reliability of the generated results. The optimization resulted in an electrode structure consisting of 15 electrodes with a relatively high classification accuracy of almost 80%.

Identifying least affected parameters in analyzing Electrical Impedance Myography with alteration in subcutaneous fat thickness via finite element model

Electrical Impedance Myography (EIM) is a neurophysiologic technique in which high- frequency, low-intensity electrical current is applied via surface electrodes over a muscle or muscle group of interest and the resulting electrical parameters (resistance, reactance and phase) are analyzed to isolate diseased muscles from healthy one. Beside muscle properties, some other factors like subcutaneous fat (SF) thickness, inter-electrode distance, muscle thickness etc. also impact the major EIM parameters. The purpose of this study is to explore the effect of SF thickness variation on different EIM parameters and propose a parameter which is least affected and also can detect muscle conditions. We analyzed four different parameters in this study for various SF thicknesses and none of them possesses constant profile with alteration in SF thickness. For example, resistance in normal condition varies 24.48% with per millimeter SF thickness variation while phase varies 4.01%. Further investigation shows that among the observed parameters percentage changes in reactance is minimum with fat thickness variation while effectively identifying different muscle conditions.

Analysis of multi-hop opportunistic communications in cognitive radio network

Cognitive wireless networks consist of cognitive radio devices which enable dynamic spectrum access for unlicensed secondary users. Multi-hop cognitive radio network (MHCRN) offers connectivity when transmitter and receiver are not within the communication range of each other using single hop. However, joint effect of multi-hop and dynamic spectrum access introduces many challenges in MAC and routing layer. Note that the devices through MAC layer make spectrum access decision without disturbing the licensed users. Effective routing protocols in MHCRN are required to provide shortest path between transmitter and receiver. In this paper, several MAC layer and routing layer problem and solutions are presented.