| Autor: |
Giorgio Biagetti, Paolo Crippa, Laura Falaschetti, Leonardo Saraceni, Andrea Tiranti, Claudio Turchetti |
| Jazyk: |
angličtina |
| Rok vydání: |
2020 |
| Předmět: |
|
| Zdroj: |
Data in Brief, Vol 29, Iss , Pp - (2020) |
| Druh dokumentu: |
article |
| ISSN: |
2352-3409 |
| DOI: |
10.1016/j.dib.2019.105044 |
| Popis: |
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. Keywords: Photoplethysmography, Accelerometer, Machine learning, Activity recognition |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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