Comparison of Blind Source Separation Methods in Fast Somatosensory-Evoked Potential Detection

Single-Trial Extraction of Pure Somatosensory Evoked Potential Based on Expectation Maximization Approach

It is of great importance for intraoperative monitoring to accurately extract somatosensory evoked potentials (SEPs) and track its changes fast. Currently, multi-trial averaging is widely adopted for SEP signal extraction. However, because of the loss of variations related to SEP features across different trials, the estimated SEPs in such a way are not suitable for the purpose of real-time monitoring of every single trial of SEP. In order to handle this issue, a number of single-trial SEP extraction approaches have been developed in the literature, such as ARX and SOBI, but most of them have their performance limited due to not sufficient utilization of multi-trial and multi-condition structures of the signals. In this paper, a novel Bayesian model of SEP signals is proposed to make systemic use of multi-trial and multi-condition priors and other structural information in the signal by integrating both a cortical source propagation model and a SEP basis components model, and an Expectation Maximization (EM) algorithm is developed for single-trial SEP estimation under this model. Numerical simulations demonstrate that the developed method can provide reasonably good single-trial estimations of SEP as long as signal-to-noise ratio (SNR) of the measurements is no worse than -25 dB. The effectiveness of the proposed method is further verified by its application to real SEP measurements of a number of different subjects during spinal surgeries. It is observed that using the proposed approach the main SEP features (i.e., latencies) can be reliably estimated at single-trial basis, and thus the variation of latencies in different trials can be traced, which provides a solid support for surgical intraoperative monitoring.

Usefulness of Time-Frequency Patterns of Somatosensory Evoked Potentials in Identification of the Location of Spinal Cord Injury

Somatosensory evoked potentials (SEPs) have been widely used to monitor the neurological integrity of the spinal cord during spinal surgery. However, the location of neurologic impairment cannot be determined from SEPs. Previous studies imply that the time-frequency characteristics of SEPs may reflect the location of the spinal cord injury. To validate the hypothesis that time-frequency patterns of SEPs are associated with the location of neurologic deficits in the spinal cord, we studied the time-frequency distributions of SEPs at different injury levels. Twenty-four rats were equally divided into one normal group and three injury groups, in which weight-drop contusions were delivered to the spinal cord of the rats at C4, C5, or C6 level, respectively. By comparing the time-frequency patterns of SEPs across groups, we found significant differences in several time-frequency regions of interest in the time-frequency distributions of the normal group and the injury groups. Importantly, the regions of interest were different across injury groups, suggesting that these regions of interest could be specific to injury locations. The results imply that changes of the time-frequency patterns of SEPs may be related to the location of the spinal cord injury.

Trial-to-trial latency variability of somatosensory evoked potentials as a prognostic indicator for surgical management of cervical spondylotic myelopathy

Background

Early detection of neural conductivity changes at the compressed spinal cord is important for predicting the surgical outcomes of patients with cervical spondylotic myelopathy (CSM). The prognostic value of median nerve somatosensory evoked potential (SEP) has been proposed previously. The present prospective study evaluates the use of trial-to-trial variability in SEP as a valuable predictor of neurological recovery after surgery of CSM.

Methods

A total of 35 CSM patients who underwent surgery with up to 6-month follow-up were recruited in this study. SEP signals were recorded preoperatively. The single trial SEP was extracted by a newly developed second-order blind identification method. The postoperative recovery was assessed using the modified Japanese Orthopaedic Association. The correlation between the latency variability of trial-to-trial SEP and post-operative recovery ratio was analyzed. The prognostic value of trial-to-trial SEP for CSM was evaluated using a receiver operator characteristic curve which can accurately reflect the relationship between sensitivity and specificity of a diagnostic method and represent the accuracy of prognosis.

Results

The correlation coefficient of trial-to-trial latency variability and the 6-month recovery ratio was statistically significant (r = −0.82, P < 0.01). The trial-to-trial SEP had a higher prognostic accuracy (AUC = 0.928, P < 0.001) with an optimal prognostic value of 9.25 % compared with averaged SEP when the threshold of recovery ratio was 40 %, and was more sensitive (93.80 %) than the averaged SEP (43.80 %).

Conclusions

These findings indicate that the latency variability of trial-to-trial SEP reflect the recovery ratio of CSM patients after surgery. It is suggested that the latency variability of trial-to-trial SEP is useful for predicting the surgical outcomes for patients with CSM, which would be a potential indication of surgical treatment for CSM to help decision making of surgical planning for CSM patients.

Electronic supplementary material

The online version of this article (doi:10.1186/s12984-015-0042-4) contains supplementary material, which is available to authorized users.