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.
Dataset from PPG wireless sensor for activity monitoring / Biagetti, Giorgio; Crippa, Paolo; Falaschetti, Laura; Saraceni, Leonardo; Tiranti, Andrea; Turchetti, Claudio. - In: DATA IN BRIEF. - ISSN 2352-3409. - ELETTRONICO. - 29:(2020), p. 105044. [10.1016/j.dib.2019.105044]
Dataset from PPG wireless sensor for activity monitoring
Biagetti, Giorgio;Crippa, Paolo
;Falaschetti, Laura;Turchetti, Claudio
2020-01-01
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
