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.
Dataset from spirometer and sEMG wireless sensor for diaphragmatic respiratory activity monitoring / Biagetti, Giorgio; Carnielli, Virgilio Paolo; Crippa, Paolo; Falaschetti, Laura; Scacchia, Valentina; Scalise, Lorenzo; Turchetti, Claudio. - In: DATA IN BRIEF. - ISSN 2352-3409. - ELETTRONICO. - 25:(2019), p. 104217. [10.1016/j.dib.2019.104217]
Dataset from spirometer and sEMG wireless sensor for diaphragmatic respiratory activity monitoring
Biagetti, Giorgio;Carnielli, Virgilio Paolo;Crippa, Paolo;Falaschetti, Laura
;SCACCHIA, VALENTINA;Scalise, Lorenzo;Turchetti, Claudio
2019-01-01
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
