Selvaraj Thomas George, Ramasamy Balakrishnan, Jeyaraj Stanly Johnson, Suviseshamuthu Easter Selvan
Department of Electrical and Electronics Engineering, Karunya University, Coimbatore, India
Department of Neurology, PSG Institute of Medical Sciences and Research, Coimbatore, India.
Clin EEG Neurosci. 2014 Oct;45(4):304-309. doi: 10.1177/1550059413500960. Epub 2013 Dec 19.
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.
本文介绍了一个可在线访问的脑电图（EEG）数据库，其中的脑电图记录包含尖峰、多尖峰、慢波和锐波等异常模式，以帮助诊断相关疾病。目前，这些数据是来自印度泰米尔纳德邦哥印拜陀一家诊断中心的脑电图集合，数据样本涉及年龄从1岁到107岁的人群。最终，还将纳入有关其他疾病的脑电图数据以及来自其他机构的数据。本数据库提供以下类别的信息：疾病的主要分类、患者记录、数字化脑电图和具体诊断；此外，数据库还设有搜索功能。本文解释了领域专家、应用程序开发人员和研究人员的访问方式以及一些经典应用。随着临床神经科学的发展，该数据库将有助于开发诊断和治疗等应用的软件。
