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.

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.

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.

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.

Fractal analysis of surface electromyography signals: a novel power spectrum-based method.

This paper presents a novel power spectrum-based method for fractal analysis of surface electromyography signals. This method, named the bi-phase power spectrum method, provides a bi-phase power-law which represents a multi-scale statistically self-affine signal. This form of statistical self-affinity provides an accurate approximation for stochastic signals originating from a strong non-linear combination of a number of similar distributions, such as surface electromyography signals which are formed by the summation of a number of single muscle fiber action potentials.

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.