Research Area:  Machine Learning

Abstract:

This article presents an online accessible electroencephalogram (EEG) database, where the EEG recordings comprise abnormal patterns such as spikes, poly spikes, slow waves, and sharp waves to help diagnose related disorders. The data, as of now, are a collection of EEGs from a diagnostic center in Coimbatore, Tamil Nadu, India, and the data samples pertain to an age-group ranging from 1 to 107 years. Eventually, the EEG data concerning other disorders as well as those from other institutions will be included. The present database provides information under the following categories: major classification of the disorder, patient-s record, digitized EEG, and specific diagnosis; in addition, a search facility is incorporated into the database. The mode of access by the domain experts, application developers, and researchers, along with a few classical applications are explained in this article. With the advance of clinical neuroscience, this database will be helpful in developing software for applications such as diagnosis and treatment.

Keywords:  

Author(s) Name:  Thomas George Selvaraj, Balakrishnan Ramasamy, Stanly Johnson Jeyaraj , and Easter Selvan Suviseshamuthu

Publisher name:  SAGE

DOI:  10.1177/1550059413500960

Volume Information:  Vol 45, Issue 4

Paper Link:   https://journals.sagepub.com/doi/abs/10.1177/1550059413500960