Analysis and Prediction of Employee Promotions Using Deep Learning

PRODUCT DESCRIPTION

Analyzing brain activity through electroencephalograms (EEG) is a common practice in neuroscience and clinical settings. EEGs involve placing electrodes on a patient’s scalp to capture electrical activity via voltage differences. These multichannel voltage signals are typically stored in the European Data Format (EDF). Notably, the size of EDF files can be substantial; a 1MB EDF file represents just one minute of EEG data recorded at a rate of 250Hz.

This challenge is compounded when dealing with extensive datasets, such as those from the TUH EEG Corpus. our goal is to empower EEG researchers and clinicians with efficient, accessible, and user-friendly tools for EEG data analysis. These enhancements contribute to the advancement of our understanding of brain activity and its clinical applications, potentially leading to breakthroughs in neuroscience and neurology.