Real-time estimation of horizontal gaze angle by saccade integration using in-ear electrooculography

The manuscript proposes and evaluates a real-time algorithm for estimating eye gaze angle based solely on single-channel electrooculography (EOG), which can be obtained directly from the ear canal using conductive ear moulds. In contrast to conventional high-pass filtering, we used an algorithm that calculates absolute eye gaze angle via statistical analysis of detected saccades. The estimated eye positions of the new algorithm were still noisy. However, the performance in terms of Pearson product-moment correlation coefficients was significantly better than the conventional approach in some instances. The results suggest that in-ear EOG signals captured with conductive ear moulds could serve as a basis for lightweight and portable horizontal eye gaze angle estimation suitable for a broad range of applications. For instance, for hearing aids to steer the directivity of microphones in the direction of the user’s eye gaze

Nonlinear analysis of EEG signals at different mental states

BACKGROUND: The EEG (Electroencephalogram) is a representative signal containing information about the condition of the brain. The shape of the wave may contain useful information about the state of the brain. However, the human observer can not directly monitor these subtle details. Besides, since bio-signals are highly subjective, the symptoms may appear at random in the time scale. Therefore, the EEG signal parameters, extracted and analyzed using computers, are highly useful in diagnostics. This work discusses the effect on the EEG signal due to music and reflexological stimulation. METHODS: In this work, nonlinear parameters like Correlation Dimension (CD), Largest Lyapunov Exponent (LLE), Hurst Exponent (H) and Approximate Entropy (ApEn) are evaluated from the EEG signals under different mental states. RESULTS: The results obtained show that EEG to become less complex relative to the normal state with a confidence level of more than 85% due to stimulation. CONCLUSIONS: It is found that the measures are significantly lower when the subjects are under sound or reflexologic stimulation as compared to the normal state. The dimension increases with the degree of the cognitive activity. This suggests that when the subjects are under sound or reflexologic stimuli, the number of parallel functional processes active in the brain is less and the brain goes to a more relaxed stat

Multilayer Perceptrons for the classification of Brain Computer Interface data

Bioengineering, Proceedings of the Northeast Conference118-11

Estimation of the hemodynamic response of fMRI data using RBF neural network

10.1109/TBME.2007.900795IEEE Transactions on Biomedical Engineering5481371-1381IEBE

fMRI data analysis with nonstationary noise models: A Bayesian approach

10.1109/TBME.2007.902591IEEE Transactions on Biomedical Engineering5491621-1630IEBE

H∞ adaptive filters for eye blink artifact minimization from electroencephalogram

10.1109/LSP.2005.859526IEEE Signal Processing Letters1212816-819ISPL

Analysis of fMRI data with drift: Modified general linear model and Bayesian estimator

10.1109/TBME.2008.918563IEEE Transactions on Biomedical Engineering5551504-1511IEBE

Analysis of schizophrenic EEG synchrony using empirical mode decomposition

10.1109/ICDSP.2007.42885362007 15th International Conference on Digital Signal Processing, DSP 2007131-13

A constrained genetic algorithm for efficient dimensionality reduction for pattern classification

10.1109/CIS.2007.12Proceedings - 2007 International Conference on Computational Intelligence and Security, CIS 2007424-42