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

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...

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Published inData in brief Vol. 25; p. 104217
Main Authors Biagetti, Giorgio, Carnielli, Virgilio Paolo, Crippa, Paolo, Falaschetti, Laura, Scacchia, Valentina, Scalise, Lorenzo, Turchetti, Claudio
Format Journal Article
LanguageEnglish
Published Netherlands Elsevier Inc 01.08.2019
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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.
AbstractList 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, Spirometer signal, sEMG wireless sensor, Respiratory activity monitoring
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.
ArticleNumber 104217
Author Falaschetti, Laura
Biagetti, Giorgio
Turchetti, Claudio
Scalise, Lorenzo
Scacchia, Valentina
Carnielli, Virgilio Paolo
Crippa, Paolo
AuthorAffiliation a Department of Information Engineering, Polytechnic University of Marche, Ancona, Italy
c Department of Industrial Engineering and Mathematical Sciences, Polytechnic University of Marche, Ancona, Italy
b Maternal and Child Health Institute, Polytechnic University of Marche and Salesi Hospital, Ancona, Italy
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Cites_doi 10.1016/j.resp.2006.06.002
10.1109/TCE.2016.7613192
10.3390/s8042174
10.1016/j.jelekin.2019.01.002
10.1152/japplphysiol.00914.2003
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Keywords Respiratory activity monitoring
Diaphragm surface electromyographic signal
Spirometer signal
sEMG wireless sensor
Language English
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Snippet We introduce a dataset to provide insights into the relationship between the diaphragm surface electromyographic (sEMG) signal and the respiratory air flow....
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SubjectTerms Diaphragm surface electromyographic signal
Engineering
Respiratory activity monitoring
sEMG wireless sensor
Spirometer signal
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Title Dataset from spirometer and sEMG wireless sensor for diaphragmatic respiratory activity monitoring
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