Extraction of notable points from ECG data: A description of a dataset related to 30-s seated and 30-s stand up
Rui Pedro Duarte,
Francisco Alexandre Marinho,
Eduarda Sofia Bastos,
Rui João Pinto,
Pedro Miguel Silva,
Alice Fermino,
Hanna Vitalyvna Denysyuk,
António Jorge Gouveia,
Norberto Jorge Gonçalves,
Paulo Jorge Coelho,
Eftim Zdravevski,
Petre Lameski,
Toni Tripunovski,
Nuno M. Garcia,
Ivan Miguel Pires
Affiliations
Rui Pedro Duarte
Escola de Ciências e Tecnologia, Universidade de Trás-Os-Montes e Alto Douro, Quinta de Prados, Vila Real 5001-801, Portugal
Francisco Alexandre Marinho
Escola de Ciências e Tecnologia, Universidade de Trás-Os-Montes e Alto Douro, Quinta de Prados, Vila Real 5001-801, Portugal
Eduarda Sofia Bastos
Escola de Ciências e Tecnologia, Universidade de Trás-Os-Montes e Alto Douro, Quinta de Prados, Vila Real 5001-801, Portugal
Rui João Pinto
Escola de Ciências e Tecnologia, Universidade de Trás-Os-Montes e Alto Douro, Quinta de Prados, Vila Real 5001-801, Portugal
Pedro Miguel Silva
Escola de Ciências e Tecnologia, Universidade de Trás-Os-Montes e Alto Douro, Quinta de Prados, Vila Real 5001-801, Portugal
Alice Fermino
Computer Science Department, Universidade da Beira Interior, Covilhã 6200-001, Portugal
Hanna Vitalyvna Denysyuk
Instituto de Telecomunicações, Universidade da Beira Interior, Covilhã 6200-001, Portugal
António Jorge Gouveia
Escola de Ciências e Tecnologia, Universidade de Trás-Os-Montes e Alto Douro, Quinta de Prados, Vila Real 5001-801, Portugal
Norberto Jorge Gonçalves
Escola de Ciências e Tecnologia, Universidade de Trás-Os-Montes e Alto Douro, Quinta de Prados, Vila Real 5001-801, Portugal
Paulo Jorge Coelho
School of Technology and Management, Polytechnic of Leiria, Leiria 2411-901, Portugal; Institute for Systems Engineering and Computers at Coimbra (INESC Coimbra), DEEC, Pólo II, Coimbra 3030-290, Portugal
Eftim Zdravevski
Faculty of Computer Science and Engineering, University Ss Cyril and Methodius, 1000 Skopje, North Macedonia
Petre Lameski
Faculty of Computer Science and Engineering, University Ss Cyril and Methodius, 1000 Skopje, North Macedonia
Toni Tripunovski
Institute of Pathophysiology and Nuclear Medicine, University Ss Cyril and Methodius, 1000 Skopje, North Macedonia
Nuno M. Garcia
Instituto de Telecomunicações, Universidade da Beira Interior, Covilhã 6200-001, Portugal
Ivan Miguel Pires
Instituto de Telecomunicações, Universidade da Beira Interior, Covilhã 6200-001, Portugal; Corresponding author.
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.
