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Temple EEG Database Over 30,000 clinical EEGs and accompanying neurologist reports Human Macroscopic EEG Healthy and various diseases Yes [44] Ultrahigh resolution T1-weighted whole brain MR dataset T1-weighted MR data acquired using prospective motion correction at an ultrahigh isotropic resolution of 250 μm. Human Mesoscopic
P300 Interface Dataset Data from nine subjects collected using P300-based brain-computer interface for disabled subjects. Split into four sessions for each subject. MATLAB code given. 1,224 Text Classification 2008 [263] [264] U. Hoffman et al. Heart Disease Data Set Attributed of patients with and without heart disease.
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]
Kaggle is a data science competition platform and online community for data scientists and machine learning practitioners under Google LLC.Kaggle enables users to find and publish datasets, explore and build models in a web-based data science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.
There are two important methods for time domain EEG analysis: Linear Prediction and Component Analysis. Generally, Linear Prediction gives the estimated value equal to a linear combination of the past output value with the present and past input value. And Component Analysis is an unsupervised method in which the data set is mapped to a feature ...
The analog signal comprises a microvoltage time series of the EEG, sampled digitally and sampling rates adequate to over-sample the signal (using the Nyquist principle of exceeding twice the highest frequency being detected). Modern EEG amplifiers use adequate sampling to resolve the EEG across the traditional medical band from DC to 70 or 100 ...
Some research groups have performed fMRI combined to EEG in order to achieve inner-speech dictation and the approach of inner-speech recognition. [ 18 ] [ 19 ] [ 20 ] The P300 wave obtained by visual stimulation is used to assess cognitive processes in humans, and the value of the latency and amplitude of the P300 wave can be a measure of the ...
EEGLAB is a MATLAB toolbox distributed under the free BSD license for processing data from electroencephalography (EEG), magnetoencephalography (MEG), and other electrophysiological signals. [ 1 ] [ 2 ] Along with all the basic processing tools, EEGLAB implements independent component analysis (ICA), time/frequency analysis, artifact rejection ...