The eye-computer interaction technology based on electro-oculogram provides the users with a convenient way to control the device, which has great social significance. However, the eye-computer interaction is often disturbed by the involuntary eye movements, resulting in misjudgment, affecting the users' experience, and even causing danger in severe cases. Therefore, this paper starts from the basic concepts and principles of eye-computer interaction, sorts out the current mainstream classification methods of voluntary/involuntary eye movement, and analyzes the characteristics of each technology. The performance analysis is carried out in combination with specific application scenarios, and the problems to be solved are further summarized, which are expected to provide research references for researchers in related fields.
Computers ; Electrooculography/methods* ; Eye Movements ; Movement

The method of Joint approximate diagonalization (JADE) is used to remove the ocular artifact from Electroencephalogram (EEG). As the JADE algorithm can be used to separate sub-gaussian and super-gaussian sources, it is possible to extract the signals that are statistically independent, and to identify the spatial map that is associated with the artifactual component. Thus the method can remove artifactual component. Satisfactory results illustrate the robust and practicability of the algorithm.
Algorithms ; Artifacts ; Electroencephalography ; methods ; Electrooculography ; Humans ; Signal Processing, Computer-Assisted

As a classic eye movement method, electrooculogram (EOG) has been extensively used in many applications. There are many different types of eye movements and artifact in the EOG signal. Noise attenuation and signal separation have received special attention in the EOG research. In this paper, we introduce a novel Linear-nonlinear combinational filter based on weighted FIR-median-hybrid (WFMH) with the characteristic of the EOG signal. The result of the simulation shows that this filter has the property of removing random noise more efficiently when preserving sharp edges. Finally, it is shown that the new filter is effective in separating saccadic and eye blink in the EOG signal.
Electrooculography ; methods ; Eye Movements ; physiology ; Humans ; Signal Processing, Computer-Assisted

The non-invasive brain-computer interface (BCI) has gradually become a hot spot of current research, and it has been applied in many fields such as mental disorder detection and physiological monitoring. However, the electroencephalography (EEG) signals required by the non-invasive BCI can be easily contaminated by electrooculographic (EOG) artifacts, which seriously affects the analysis of EEG signals. Therefore, this paper proposed an improved independent component analysis method combined with a frequency filter, which automatically recognizes artifact components based on the correlation coefficient and kurtosis dual threshold. In this method, the frequency difference between EOG and EEG was used to remove the EOG information in the artifact component through frequency filter, so as to retain more EEG information. The experimental results on the public datasets and our laboratory data showed that the method in this paper could effectively improve the effect of EOG artifact removal and improve the loss of EEG information, which is helpful for the promotion of non-invasive BCI.
Humans ; Electrooculography/methods* ; Artifacts ; Brain-Computer Interfaces ; Algorithms ; Electroencephalography/methods* ; Signal Processing, Computer-Assisted

OBJECTIVE: To study the variation of latency and amplitude of the event related potential (ERP) and its distribution in human scalp when the normal subjects were stimulated with different visual fields. METHODS: The ERP recorded in scalp with the stimulation of 10 degrees visual field and 60 degrees visual field respectively in 20 healthy volunteers with normal visual function. RESULTS: Two different visual field stimulation may evoke the different exogenous components P1 (70-125 ms), N1 (90-170 ms), P2 (140-220 ms) and endogenous components N2 (190-280 ms) and P3 (290-430 ms). The latencies of all the components evoked by 10 degrees visual field were shorter than that of the 60 degrees visual field while the amplitudes of N1 and N2 were lower and appeared over the extensive encephalic region; and the amplitudes of the P1, P2 and P3 were higher and appeared in occipitotemporal, prefrontal and occipital region, respectively. CONCLUSION Two different visual field stimulation may evoke all the ERP components with significant differences in the latency, amplitude and distribution. The differences may reflect the different visual information integration and processing in human brain during the different visual field stimulation.
Adult ; Brain/physiology* ; Electroencephalography/methods* ; Electrooculography ; Evoked Potentials, Visual/physiology* ; Female ; Humans ; Male ; Photic Stimulation ; Reaction Time/physiology* ; Reference Values ; Scalp/physiology* ; Visual Field Tests/methods* ; Visual Fields/physiology* ; Visual Perception/physiology* ; Young Adult