Single-trial detection for intraoperative somatosensory evoked potentials monitoring

Abnormalities of somatosensory evoked potentials (SEPs) provide effective evidence for impairment of the somatosensory system, so that SEPs have been widely used in both clinical diagnosis and intraoperative neurophysiological monitoring. However, due to their low signal-to-noise ratio (SNR), SEPs are generally measured using ensemble averaging across hundreds of trials, thus unavoidably producing a tardiness of SEPs to the potential damages caused by surgical maneuvers and a loss of dynamical information of cortical processing related to somatosensory inputs. Here, we aimed to enhance the SNR of single-trial SEPs using Kalman filtering and time-frequency multiple linear regression (TF-MLR) and measure their single-trial parameters, both in the time domain and in the time-frequency domain. We first showed that, Kalman filtering and TF-MLR can effectively capture the single-trial SEP responses and provide accurate estimates of single- trial SEP parameters in the time domain and time-frequency domain, respectively. Furthermore, we identified significant correlations between the stimulus intensity and a set of indicative single- trial SEP parameters, including the correlation coefficient (between each single-trial SEPs and their average), P37 amplitude, N45 amplitude, P37-N45 amplitude, and phase value (at the zero-crossing points between P37 and N45). Finally, based on each indicative single-trial SEP parameter, we investigated the minimum number of trials required on a single-trial basis to suggest the existence of SEP responses, thus providing important information for fast SEP extraction in intraoperative monitoring.