IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
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IEEE Trans Neural Syst Rehabil Eng · Oct 2017
Quasi-Periodicities Detection Using Phase-Rectified Signal Averaging in EEG Signals as a Depth of Anesthesia Monitor.
Phase-rectified signal averaging (PRSA) has been known to be a useful method to detect periodicities in non-stationary biological signals. Determination of quasi-periodicities in electroencephalogram (EEG) is a candidate for quantifying the changes in the depth of anesthesia (DOA). In this paper, DOA monitoring capacity of periodicities detected using PRSA was quantified by assessing EEG signals collected from 56 patients during surgery. ⋯ There is a larger mean AUC and correlation coefficient of quasi-periodicities compared with SampEn, DFA, and PE using expert assessment of conscious level and bispectral index as the gold standard, respectively. Quasi-periodicities detected using PRSA in EEG signals are a powerful monitor of DOA and perform more accurate and robust results compared with SampEn, DFA, and PE. The results do provide a valuable reference to researchers in the field of clinical applications.
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IEEE Trans Neural Syst Rehabil Eng · Oct 2017
Epidural Stimulation of Rat Spinal Cord at Lumbosacral Segment Using a Surface Electrode: A Computer Simulation Study.
Clinical research indicates that the epidural spinal cord stimulation (ESCS) at lumbosacral segment has shown potential for promoting locomotor recovery in patients with incomplete spinal cord injury. However, the underlying neural mechanism needs to be determined by animal experiments. In order to refine experimental protocols, we used a finite element simulation to investigate the activation of nerve fibers in a rat spinal cord model. ⋯ The spikes were initiated at sites along the nerve fibers depending on which component was closest to the cathode among the longitudinal part of the fiber, its entrance into spinal cord, or strong bending at the entry. Our simulation results show good agreement with the previous findings from animal studies. It is concluded that the computational ESCS model is a valuable tool to obtain a better insight into the immediately evoked electrophysiological phenomena in animal models, and provides further guidelines for conducting animal experiments to enhance the exploration of basic neural mechanisms.