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Data Brief. 2019 Dec 23;29:105044. doi: 10.1016/j.dib.2019.105044. eCollection 2020 Apr.

Dataset from PPG wireless sensor for activity monitoring.

Data in brief

Giorgio Biagetti, Paolo Crippa, Laura Falaschetti, Leonardo Saraceni, Andrea Tiranti, Claudio Turchetti

Affiliations

  1. Department of Information Engineering, Polytechnic University of Marche, Ancona, Italy.

PMID: 31989005 PMCID: PMC6971339 DOI: 10.1016/j.dib.2019.105044

Abstract

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.

© 2019 The Authors.

Keywords: Accelerometer; Activity recognition; Machine learning; Photoplethysmography

References

  1. IEEE Trans Biomed Eng. 2015 Feb;62(2):522-31 - PubMed
  2. IEEE Trans Biomed Eng. 2015 Aug;62(8):1902-10 - PubMed

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