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Dataset from PPG wireless sensor for activity monitoring
We introduce a dataset to provide insights about the photoplethysmography (PPG) signal captured from the wrist in presence of motion artifacts and the accelerometer signal, simultaneously acquired from the same wrist. The data presented were collected by the electronics research team of the Departme...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6971339/ https://www.ncbi.nlm.nih.gov/pubmed/31989005 http://dx.doi.org/10.1016/j.dib.2019.105044 |
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author | Biagetti, Giorgio Crippa, Paolo Falaschetti, Laura Saraceni, Leonardo Tiranti, Andrea Turchetti, Claudio |
author_facet | Biagetti, Giorgio Crippa, Paolo Falaschetti, Laura Saraceni, Leonardo Tiranti, Andrea Turchetti, Claudio |
author_sort | Biagetti, Giorgio |
collection | PubMed |
description | We introduce a dataset to provide insights about the photoplethysmography (PPG) signal captured from the wrist in presence of motion artifacts and the accelerometer signal, simultaneously acquired from the same wrist. The data presented were collected by the electronics research team of the Department of Information Engineering, Polytechnic University of Marche, Ancona, Italy. This article describes data recorded from 7 subjects and includes 105 PPG signals (15 for each subject) and the corresponding 105 tri-axial accelerometer signals measured with a sampling frequency of 400 Hz. These data can be reused for testing machine learning algorithms for human activity recognition. |
format | Online Article Text |
id | pubmed-6971339 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-69713392020-01-27 Dataset from PPG wireless sensor for activity monitoring Biagetti, Giorgio Crippa, Paolo Falaschetti, Laura Saraceni, Leonardo Tiranti, Andrea Turchetti, Claudio Data Brief Engineering We introduce a dataset to provide insights about the photoplethysmography (PPG) signal captured from the wrist in presence of motion artifacts and the accelerometer signal, simultaneously acquired from the same wrist. The data presented were collected by the electronics research team of the Department of Information Engineering, Polytechnic University of Marche, Ancona, Italy. This article describes data recorded from 7 subjects and includes 105 PPG signals (15 for each subject) and the corresponding 105 tri-axial accelerometer signals measured with a sampling frequency of 400 Hz. These data can be reused for testing machine learning algorithms for human activity recognition. Elsevier 2019-12-23 /pmc/articles/PMC6971339/ /pubmed/31989005 http://dx.doi.org/10.1016/j.dib.2019.105044 Text en © 2019 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Engineering Biagetti, Giorgio Crippa, Paolo Falaschetti, Laura Saraceni, Leonardo Tiranti, Andrea Turchetti, Claudio Dataset from PPG wireless sensor for activity monitoring |
title | Dataset from PPG wireless sensor for activity monitoring |
title_full | Dataset from PPG wireless sensor for activity monitoring |
title_fullStr | Dataset from PPG wireless sensor for activity monitoring |
title_full_unstemmed | Dataset from PPG wireless sensor for activity monitoring |
title_short | Dataset from PPG wireless sensor for activity monitoring |
title_sort | dataset from ppg wireless sensor for activity monitoring |
topic | Engineering |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6971339/ https://www.ncbi.nlm.nih.gov/pubmed/31989005 http://dx.doi.org/10.1016/j.dib.2019.105044 |
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