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In this paper a system for detecting the possibility of eye dystonia, a neural disorder that causes a person to blink excessively, by eye movement analysis is proposed. The designed system counts the number of blinks for a particular time interval and thus detecting the risk of eye dystonia. Electrooculogram (EOG) signal is recorded to collect eye movement data using a laboratory developed acquisition...
The present work proposes a system for assistance of Autistic children by analysis of eye movements. Autism is a disease characterized by abnormal eye movements and an inability to follow a pattern of object movement in different directions. Eye movement data is recorded from normal individuals over a period of five days using an Electrooculogram signal acquisition system developed in the laboratory...
The present work proposes a system for detecting the possibility of eye dystonia from the analysis of eye movements. Eye movement data is recorded using an Electrooculogram signal acquisition system developed in the laboratory. Combinations of Hjorth parameters and Autoregressive (AR) parameters with Power Spectral Density (PSD) are used as signal features. Blinks are classified from other types of...
In this work we establish the fact that using Electroencephalogram (EEG) with tactile signal during dynamic exploration accomplishes object shape recognition better than using the either alone. Adaptive auto-regressive coefficients and Hjorth parameters are used as features which are classified using linear Support Vector Machine, Naïve Bayes, k-nearest neighbor and tree classifiers. Following this,...
Recognition of cognitive context is an important aspect of context aware pervasive computing systems. The present work is aimed at identification of cognitive contexts of human beings from the analysis of their eye movements by acquiring Electrooculogram signals. These signals are represented through Adaptive Autoregressive Parameters, Hjorth Parameters and Wavelet Coefficients as signal features...
This paper aims at laying a foundation towards the development of a robust platform for efficient control of the motion of autonomous mobile robots. Electroencephalographic (EEG) signals liberated during motor imagery of a human controller have been used to design the control mechanism. The proposed scheme can find widespread applications in the defense sector as secrecy of generated commands can...
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