Mehran Talebinejad

A Lempel-Ziv complexity measure for muscle fatigue estimation.

This paper presents a Lempel-Ziv complexity measure for analysis of surface electromyography signals. The Lempel-Ziv measure provides a metric for the number of distinct deterministic patterns and the rate of their creation in signals. We propose a ternary Lempel-Ziv measure, improving upon the binary Lempel-Ziv measure, and making it more suited for the analysis of biological signals. The Lempel-Ziv measure is evaluated with a muscle fatigue experiment in which participants perform static, cyclic, and random contractions. Results show this complexity measure shows a greater correlation to a steadily increasing muscle fatigue level compared to the conventional median frequency. This measure is computationally easy to compute and does not require power spectrum estimation and signal stationarity assumptions.

Fatigue estimation using a novel multi-fractal detrended fluctuation analysis-based approach

This paper presents a novel multi-fractal detrended fluctuation analysis-based approach for fatigue estimation. This approach exploits the statistical self-similarity and long-range correlation of surface electromyography signals at different time scales in which the myoelectric manifestation of fatigue is more significant compared to the influence of varying force, muscle length (joint angle), and innervation zone. This approach provides a fatigue index which outperforms the conventional median frequency during cyclic and random contractions. This type of analysis is promising an efficient framework for analysis of surface electromyography signals with several potential applications.

Effects of TMS coil geometry on stimulation specificity

Transcranial magnetic stimulation has become an established tool in experimental cognitive neuroscience and has more recently been applied clinically. The current spatial extent of neural activation is several millimeters but with greater specificity, transcranial magnetic stimulation can potentially deliver real time feedback to reinforce or extinguish behavior by exciting or inhibiting localized neural circuits. The specificity of transcranial magnetic stimulation is a function of the stimulation coil geometry. In this paper, a practical multilayer framework for the design of miniaturized stimulation coils is presented. This framework is based on a magnet wire fabricated from 2500 braided ultrafine wires. Effects of coil bending angle on stimulation specificity are examined using realistic finite element method simulations. A novel stimulation coil with one degree of freedom is also proposed that shows improved specificity over the conventional fixed coils. This type of coil could be potentially used as a feedback system for a bidirectional brain machine interface.

Multiplicative multi-fractal modeling of electromyography signals for discerning neuropathic conditions

In this paper, we present a new method for multi-scale analysis of electromyography signals based on an interesting fractal process known as multiplicative cascade multi-fractal. Using simulated needle electromyography signals, we show this method provides a means for discrimination of normal and neuropathic electromyography signals. We also present experimental results that show the new parameters, computed using multiplicative cascade multi-fractal modeling, are more robust than the conventional signal parameter, number of turns, in the presence of additive noise. Results of multiplicative cascade multi-fractal modeling are consistent with other multi-scale approaches; advantages and differences are high lighted.

Effects of force and joint angle on fractal parameters of the myoelectric signal.

In this paper we investigate the effect of force and joint angle on myoelectric signal parameters. In recent years, methods that have been previously used to analyze nonlinear chaotic dynamical systems have been applied to myoelectric signals. Nonlinear myoelectric signal parameters that have been used include the fractal dimension, estimated using the Katz method and Box-Counting methods, and the spectral slopes. Previous research has only examined effects of contractile force, whereas this research also includes joint angle effects. Results of this research suggest that the Katz and Box-Counting approaches used to estimate fractal dimension are not well suited for time functions, such as myoelectric signals. Results from the spectral slope parameters suggest that these parameters can track joint angle effects. A generalized model approach building upon the spectral slope method is proposed for future work

A Computationally Efficient HMM-Based Handwriting Verification System

In this paper, we present a novel framework for HMM- based handwriting verification in which the training is performed using a one-shot algorithm for segmentation and HMM parameter estimation using a constrained k-means clustering procedure, instead of the recursive expectation maximization algorithm. This new framework allows training based on a single observation set which results in a straight forward reference model construction and elimination of computationally expensive re-training. Results of a human study using this verification system for handwritten signature and password verification demonstrate that this new efficient approach is still able to maintain high accuracy of 99 % while only three training sets were used.