Multi-channel evoked response detection using only phase information.
The phase consistency of contiguous segments of the electroencephalogram (EEG) has been used in the detection of evoked responses to rhythmic stimulation. One of such techniques is the component synchrony measure (CSM), which is often used since the threshold for the detection task is easily obtained based on the estimates of asymptotic sample distribution. In this work we investigated the appropriateness of such thresholds for practical number of segments (M). The performance of CSM was next evaluated by Monte Carlo simulations with different signal-to-noise ratios (SNR) and values of M, and the results, compared with those for the magnitude-squared coherence. A way of improving the detection with CSM was also proposed, by suggesting the estimation taking into account the mean phase angle of a set of N signals. This multivariate detector was evaluated in simulations and an illustration of the technique was also given with the EEG of 14 subjects during photic stimulation. In simulated signals with equal SNR, the detection rate with this multivariate measure increased with N. The application to EEG data lead to similar results in 70% of the subjects, which suggests that improvements might be expected when more signals are available to detect evoked responses in EEG.
Miranda de Sá
Antonio Mauricio F L
AM
Department of Electrical Engineering (DEPEL), Federal University of São João del Rei (UFSJ), Praça Frei Orlando, 170, Centro, São João del Rei, CEP 36307-352 Minas Gerais, Brazil. amiranda@ufsj.edu.br
Felix
Leonardo B
LB
D000161:Acoustic Stimulation; D003198:Computer Simulation; D003344:Cortical Synchronization; D004569:Electroencephalography / Q000379:methods*; D005072:Evoked Potentials, Auditory / Q000502:physiology*; D005074:Evoked Potentials, Visual / Q000502:physiology*; D006801:Humans; D008959:Models, Neurological; D009010:Monte Carlo Method; D010775:Photic Stimulation; D011336:Probability; D012680:Sensitivity and Specificity; D012684:Sensory Thresholds; D017603:Signal Detection, Psychological / Q000502:physiology*; D012815:Signal Processing, Computer-Assisted