Properties of the surface electromyogram following traumatic spinal cord injury: a scoping review

Traumatic spinal cord injury (SCI) disrupts spinal and supraspinal pathways, and this process is reflected in changes in surface electromyography (sEMG). sEMG is an informative complement to current clinical testing and can capture the residual motor command in great detail—including in muscles below the level of injury with seemingly absent motor activities. In this comprehensive review, we sought to describe how the sEMG properties are changed after SCI. We conducted a systematic literature search followed by a narrative review focusing on sEMG analysis techniques and signal properties post-SCI. We found that early reports were mostly focused on the qualitative analysis of sEMG patterns and evolved to semi-quantitative scores and a more detailed amplitude-based quantification. Nonetheless, recent studies are still constrained to an amplitude-based analysis of the sEMG, and there are opportunities to more broadly characterize the time- and frequency-domain properties of the signal as well as to take fuller advantage of high-density EMG techniques. We recommend the incorporation of a broader range of signal properties into the neurophysiological assessment post-SCI and the development of a greater understanding of the relation between these sEMG properties and underlying physiology. Enhanced sEMG analysis could contribute to a more complete description of the effects of SCI on upper and lower motor neuron function and their interactions, and also assist in understanding the mechanisms of change following neuromodulation or exercise therapy.

Fast Spectral Approximation of Structured Graphs with Applications to Graph Filtering

To analyze and synthesize signals on networks or graphs, Fourier theory has been extended to irregular domains, leading to a so-called graph Fourier transform. Unfortunately, different from the traditional Fourier transform, each graph exhibits a different graph Fourier transform. Therefore to analyze the graph-frequency domain properties of a graph signal, the graph Fourier modes and graph frequencies must be computed for the graph under study. Although to find these graph frequencies and modes, a computationally expensive, or even prohibitive, eigendecomposition of the graph is required, there exist families of graphs that have properties that could be exploited for an approximate fast graph spectrum computation. In this work, we aim to identify these families and to provide a divide-and-conquer approach for computing an approximate spectral decomposition of the graph. Using the same decomposition, results on reducing the complexity of graph filtering are derived. These results provide an attempt to leverage the underlying topological properties of graphs in order to devise general computational models for graph signal processing.

A computer simulation study on the influence of motor unit regionalization on the generation of surface myoelectric signals

The present study aims to analyze the influence of motor unit regionalization within the muscle cross-sectional area on time- and frequency-domain properties of surface myoelectric EMG signal. Computer simulations were performed using a phenomenological model of the neuromuscular system. Different contraction intensities were simulated, and the RMS and median frequency of the EMG were calculated for different muscle cross-sectional area morphologies. The level of MU regionalization was adjusted in the model. Results showed that experimental force-EMG relations could be appropriately simulated by the model, irrespective of the muscle cross-sectional area morphology and the level of MU regionalization. However, the best fit between simulation and experimental data is influenced by the level of MU regionalization.

Numerical investigation on the gas–liquid entraining and separating effects on self-priming performance in a flow-ejecting centrifugal pump

To investigate the influence of entraining and separating effect of gas–liquid two-phase on self-priming performance in the flow-ejecting centrifugal pump, three different schemes of adding the baffle plate behind the guide vane were proposed. Experiments on self-priming performance for three different guide vane schemes were carried out, and numerical calculations on entraining property in the ejector and separating property in the chamber were analyzed by means of the Eulerian–Eulerian multiphase flow model. Meanwhile, the frequency domain properties of pressure pulsation and the pump performance curves were obtained to further verify the feasibility of the scheme in practical application. The results show that the simulation analysis agreed well with the test results. The area and magnitude of high velocity region and vorticities in the ejector of scheme 2 are remarkably larger than those of other schemes. Gas–liquid separation efficiency in a pump chamber also significantly improves when the baffle plate behind the guide vane is mounted at an appropriate position. Furthermore, different guide vane schemes have certain impact on the characteristics of internal and unsteady flow pulsation phenomena in model pump but are within the acceptable operation range. The head and efficiency of scheme 2 are also slightly higher than those of the prototype in the full operation range.

Observational Data: Detailed Characteristics in the Frequency Domain

This chapter details the frequency-domain properties of observational data on stars. It is from the analysis of the frequency spectrum of the observations that the asteroseismic parameters are usually extracted. The chapter looks at each of the intrinsic stellar contributions in turn, always with an eye to how each must be handled in the asteroseismic analysis. It also considers the impact on the analysis of gaps in the data. In performing the analyses, this chapter begins by covering practical fundamentals associated with estimation of the frequency spectra, which underpin everything that follows. In addition, this chapter will be making use of Fourier transforms in studying the data.