Extraction of notable points from ECG data: A description of a dataset related to 30-s seated and 30-s stand up
Journal
Data in brief
Date Issued
2023-02
Author(s)
Duarte, Rui Pedro
Marinho, Francisco Alexandre
Bastos, Eduarda Sofia
Pinto, Rui João
Silva, Pedro Miguel
Fermino, Alice
Denysyuk, Hanna Vitalyvna
Gouveia, António Jorge
Gonçalves, Norberto Jorge
Coelho, Paulo Jorge
Garcia, Nuno M
Pires, Ivan Miguel
DOI
10.1016/j.dib.2022.108874
Abstract
It is increasingly possible to acquire Electrocardiographic data with featured low-cost devices. The proposed dataset will help map different signals for various diseases related to Electrocardiography data. The dataset presented in this paper is related to the acquisition of electrocardiography data during the standing up and seated positions. The data was collected from 219 individuals (112 men, 106 women, and one other) in different environments, but they are in the Covilhã municipality. The dataset includes the 219 recordings and corresponds to the sensors' recordings of a 30 s sitting and a 30 s standing test, which checks to approximately 1 min for each one. This dataset includes 3.7 h (approximately) of recordings for further analysis with data processing techniques and machine learning methods. It will be helpful for the complementary creation of a robust method for identifying the characteristics of individuals related to Electrocardiography signals.
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