Dataset Information

A novel approach for automatic visualization and activation detection of evoked potentials induced by epidural spinal cord stimulation in individuals with spinal cord injury.

ABSTRACT: Voluntary movements and the standing of spinal cord injured patients have been facilitated using lumbosacral spinal cord epidural stimulation (scES). Identifying the appropriate stimulation parameters (intensity, frequency and anode/cathode assignment) is an arduous task and requires extensive mapping of the spinal cord using evoked potentials. Effective visualization and detection of muscle evoked potentials induced by scES from the recorded electromyography (EMG) signals is critical to identify the optimal configurations and the effects of specific scES parameters on muscle activation. The purpose of this work was to develop a novel approach to automatically detect the occurrence of evoked potentials, quantify the attributes of the signal and visualize the effects across a high number of scES parameters. This new method is designed to automate the current process for performing this task, which has been accomplished manually by data analysts through observation of raw EMG signals, a process that is laborious and time-consuming as well as prone to human errors. The proposed method provides a fast and accurate five-step algorithms framework for activation detection and visualization of the results including: conversion of the EMG signal into its 2-D representation by overlaying the located signal building blocks; de-noising the 2-D image by applying the Generalized Gaussian Markov Random Field technique; detection of the occurrence of evoked potentials using a statistically optimal decision method through the comparison of the probability density functions of each segment to the background noise utilizing log-likelihood ratio; feature extraction of detected motor units such as peak-to-peak amplitude, latency, integrated EMG and Min-max time intervals; and finally visualization of the outputs as Colormap images. In comparing the automatic method vs. manual detection on 700 EMG signals from five individuals, the new approach decreased the processing time from several hours to less than 15 seconds for each set of data, and demonstrated an average accuracy of 98.28% based on the combined false positive and false negative error rates. The sensitivity of this method to the signal-to-noise ratio (SNR) was tested using simulated EMG signals and compared to two existing methods, where the novel technique showed much lower sensitivity to the SNR.

SUBMITTER: Mesbah S

PROVIDER: S-EPMC5636093 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Epidural electrical stimulation can restore limb motor function after spinal cord injury by reactivating the surviving neural circuits. In previous epidural electrical stimulation studies, single electrode sites and continuous tetanic stimulation have often been used. With this stimulation, the body is prone to declines in tolerance and locomotion coordination. In the present study, rat models of complete spinal cord injury were established by vertically cutting the spinal cord at the T8 level to eliminate disturbance from residual nerve fibers, and were then subjected to epidural electrical stimulation. The flexible extradural electrode had good anatomical topology and matched the shape of the spinal canal of the implanted segment. Simultaneously, the electrode stimulation site was able to be accurately applied to the L2-3 and S1 segments of the spinal cord. To evaluate the biocompatibility of the implanted epidural electrical stimulation electrodes, GFAP/Iba-1 double-labeled immunofluorescence staining was performed on the spinal cord below the electrodes at 7 days after the electrode implantation. Immunofluorescence results revealed no significant differences in the numbers or morphologies of microglia and astrocytes in the spinal cord after electrode implantation, and there was no activated Iba-1+ cell aggregation, indicating that the implant did not cause an inflammatory response in the spinal cord. Rat gait analysis showed that, at 3 days after surgery, gait became coordinated in rats with spinal cord injury under burst stimulation. The regained locomotion could clearly distinguish the support phase and the swing phase and dynamically adjust with the frequency of stimulus distribution. To evaluate the matching degree between the flexible epidural electrode (including three stimulation contacts), vertebral morphology, and the level of the epidural site of the stimulation electrode, micro-CT was used to scan the thoracolumbar vertebrae of rats before and after electrode implantation. Based on the experimental results of gait recovery using three-site stimulation electrodes at L2-3 and S1 combined with burst stimulation in a rat model of spinal cord injury, epidural electrical stimulation is a promising protocol that needs to be further explored. This study was approved by the Animal Ethics Committee of Chinese PLA General Hospital (approval No. 2019-X15-39) on April 19, 2019.

Dataset Information

A novel approach for automatic visualization and activation detection of evoked potentials induced by epidural spinal cord stimulation in individuals with spinal cord injury.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets