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The use of Brain-Computer Interface (BCI) has been increasing exponentially in the recent years due to the use of low-cost commercial Fast Fourier Transform (FFT) based EEG reading devices with non-clinical accuracy for consumer application development. Also, the design and implementation of 3D virtual environments for BCI training purposes has proven to be effective due to the high interaction with...
There is an urgent need for a quick screening process that could help neurologists diagnose and determine whether a patient is epileptic versus simply demonstrating symptoms linked to epilepsy but actually stemming from a different illness. An inaccurate diagnosis could have fatal consequences, particularly in operating rooms and intensive care units. Electroencephalogram (EEG) has been traditionally...
The MLSP competition (2010) purpose is to design a pattern recognition system for “mind reading”. This paper is a study of the EEG competition dataset and the crafting of the third place winning method. It shortly presents our signal processing methods for feature extraction, and channel selection. We accurately tuned all the parameters of these preprocessing stage before feeding a Gaussian SVM classifier...
This paper improves Biomimetic Pattern Recognition based on Hyper Sausage Neuron and applies it in the study of Motor Imagery EEG recognition. The paper uses the datasets from previous Brain-Computer Interface Competitions to test the accuracy and efficiency of the results, and compares them with those of SVM and BP. The results show that: with sufficient training set, the performance of Biomimetic...
The alcoholism is one of psychiatric phenotype, which results from interplay between genetic and environmental factors. Not only it leads to brain defects but also associated cognitive, emotional, and behavioral impairments. It can be detected by analyzing EEG signals. In this research, the power spectrum of the Haar mother wavelet is extracted as features. Then the principle component analysis is...
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