Decoding Thoughts with Deep Learning: EEG-Based Digit Detection using CNNs
<p>The muse dataset from the <a href="http://mindbigdata.com/opendb/index.html" rel="noopener ugc nofollow" target="_blank">MindBigData</a> EEG database is being used here for the training. The dataset being used contains 163,932<strong> </strong>brain signals of <strong>2 seconds each</strong>, captured with the stimulus of <strong>seeing a digit (from 0 to 9)</strong> and thinking about it, from a single Test Subject <a href="https://vivancos.com/" rel="noopener ugc nofollow" target="_blank">David Vivancos</a>. A small portion of the signals were captured without the stimulus of seeing the digits for contrast, all are random actions not related to thinking or seeing digits, they use the code -1.</p>
<p>It needs to be mentioned here that though the dataset contains 163,932 data points only <strong>3000</strong> data points were used for training the model with 1500 of them being digits and 1500 being non-digits.</p>
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