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This paper presents a data driven approach to explore the variations in the electroencephalogram(EEG) signals when a person tries to imagine movements like moving his or her left hand, right hand, foot and tongue. The paper tries to find out the type of variations that occur in the EEG signals when such type of imagined movements are undertaken by a person and also the regions in the brain where the...
The purpose of the study was to develop a machine learning based technique to detect the up-calls of North Atlantic Right Whales from all other noises, like calls of other creatures in the sea, so that ships plying in the seas could be warned of their presence in order to avoid a direct collision with the whales. What made the study quite difficult was the non-stationary component of the signals along...
A Brain Computer Interfaces (BCI) system enables users to control devices by acquiring and processing brain activity. An important component of a BCI system is feature extraction, which is responsible for representing brain signals in terms of essential components called features. This paper presents a comparison of the following feature extraction techniques for BCI; Common Spatial Patterns (CSP),...
Eye blinks and lateral eye movements are prominent in EEG signals which are obtained by placing electrodes in the frontal region of the brain. This paper presents a machine learning approach to detect eye movements and blinks from EEG data and map them as intents to control external devices like a computer desktop or a wheel chair.
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