Most of the application involving the study of EEG (Electroencephalogram) and ECG (Electrocardiogram) are focused on their usefulness from a medical point of view. In the last decade, these signals have been extensively studied also from other perspectives, like biometric recognition, sleep disorder analysis and brain computer interface applications. Although many datasets are publicly available, none of them gathers both EEG and ECG signal simultaneously. This lack carries the researchers to look for some workaround for analyzing aspects such as the removal of artifacts from the EEG or the data fusion of EEG and ECG. In the following work the dataset PhysioUnicaDB is presented; it consists of 22 acquisition from healthy subjects, in which the EEG and ECG signals are simultaneously acquired. The data are not filtered, so leaving the data as raw as possible.
PhysioUnicaDB: A dataset of EEG and ECG simultaneously acquired
Castiglione A.;
2018-01-01
Abstract
Most of the application involving the study of EEG (Electroencephalogram) and ECG (Electrocardiogram) are focused on their usefulness from a medical point of view. In the last decade, these signals have been extensively studied also from other perspectives, like biometric recognition, sleep disorder analysis and brain computer interface applications. Although many datasets are publicly available, none of them gathers both EEG and ECG signal simultaneously. This lack carries the researchers to look for some workaround for analyzing aspects such as the removal of artifacts from the EEG or the data fusion of EEG and ECG. In the following work the dataset PhysioUnicaDB is presented; it consists of 22 acquisition from healthy subjects, in which the EEG and ECG signals are simultaneously acquired. The data are not filtered, so leaving the data as raw as possible.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
