Biomedical subjects

Leonardo B Felix

Publications and source records attributed to Leonardo B Felix.

3 recordsLinked to original sources

PubMed2004

A matrix-based algorithm for estimating multiple coherence of a periodic signal and its application to the multichannel EEG during sensory stimulation.

The coherence between the stimulation signal and the electroencephalogram (EEG) has been used in the detection of evoked responses. The detector's performance, however, depends on both the signal-to-noise ratio (SNR) of the responses and the number of data segments (M) used in coherence estimation. In practical situations, when a given SNR occurs, detection can only be improved by increasing M and hence the total data length. This is particularly relevant when monitoring is the objective. In the present study, we propose a matrix-based algorithm for estimating the multiple coherence of the stimulation signal taking into account a set of N EEG channels as a way of increasing the detection rate for a fixed value of M. Monte Carlo simulations suggest that thresholds for such multivariate detector are the same as those for multiple coherence of Gaussian signals and that using more than six signals is not advisable for improving the detection rate with M = 10. The results with EEG from 12 normal subjects during photic stimulation at 10 Hz showed a maximum detection for N greater than 2 in 58% of the subjects with M = 10, and hence suggest that the proposed multivariate detector is valuable in evoked responses applications.

Adolescent↗

PubMed2003

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.

Acoustic Stimulation↗

PubMed2002

Improving the detection of evoked responses to periodic stimulation by using multiple coherence--application to EEG during photic stimulation.

The coherence between the stimulation signal and the electroencephalogram (EEG) has been used in the detection of evoked responses. However the detector's performance depends on both the signal-to-noise ratio (SNR) of the responses and the number of data segments (M) used in coherence estimation. In this work, a technique for detecting evoked responses was developed based on the extension to the multivariate case of this coherence. Thus, instead of using the EEG collected at a unique region, the estimation is proposed using two EEG derivations. As for the univariate case, this multiple coherence is independent of the stimulation signal. In addition, considering equal SNR in both signals, the detection rate with this multiple coherence is always greater than that one using only one signal. This was verified in Monte Carlo simulations, which also showed that a superior performance is still expected in practical situations, when a smaller SNR is found in the second signal. The results with EEG from 12 normal subjects during photic stimulation confirm this better performance. Since the proposed technique allows a higher detection rate without the need of increasing M, it permits evoked responses to be detected faster, which is very useful during monitored surgeries.

Adolescent↗