Dataset from spirometer and sEMG wireless sensor for diaphragmatic respiratory activity monitoring

Giorgio Biagetti; Virgilio Paolo Carnielli; Paolo Crippa; Laura Falaschetti; Valentina Scacchia; Lorenzo Scalise; Claudio Turchetti

doi:10.1016/j.dib.2019.104217

Dataset from spirometer and sEMG wireless sensor for diaphragmatic respiratory activity monitoring

Data Brief. 2019 Jul 5:25:104217. doi: 10.1016/j.dib.2019.104217. eCollection 2019 Aug.

Authors

Giorgio Biagetti¹, Virgilio Paolo Carnielli², Paolo Crippa¹, Laura Falaschetti¹, Valentina Scacchia³, Lorenzo Scalise³, Claudio Turchetti¹

Affiliations

¹ Department of Information Engineering, Polytechnic University of Marche, Ancona, Italy.
² Maternal and Child Health Institute, Polytechnic University of Marche and Salesi Hospital, Ancona, Italy.
³ Department of Industrial Engineering and Mathematical Sciences, Polytechnic University of Marche, Ancona, Italy.

Abstract

We introduce a dataset to provide insights into the relationship between the diaphragm surface electromyographic (sEMG) signal and the respiratory air flow. The data presented had been originally collected for a research project jointly developed by the Department of Information Engineering and the Department of Industrial Enginering and Mathematical Sciences, Polytechnic University of Marche, Ancona, Italy. This article describes data recorded from 8 subjects, and includes 8 air flow and 8 surface electromyographic (sEMG) signals for diaphragmatic respiratory activity monitoring, measured with a sampling frequency of 2 kHz.

Keywords: Diaphragm surface electromyographic signal; Respiratory activity monitoring; Spirometer signal; sEMG wireless sensor.