Recurrent Neural Network for Human Activity Recognition in Embedded Systems Using PPG and Accelerometer Data

Recurrent Neural Network for Human Activity Recognition in Embedded Systems Using PPG and Accelerometer Data

Photoplethysmography (PPG) is a common and practical technique to detect human activity and other physiological parameters and is commonly implemented in wearable devices. However, the PPG signal is often severely corrupted by motion artifacts. The aim of this paper is to address the human activity...

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Bibliographic Details
Main Authors: Michele Alessandrini, Giorgio Biagetti, Paolo Crippa, Laura Falaschetti, Claudio Turchetti
Format: Article
Language:English
Published: MDPI AG 2021-07-01
Series:Electronics
Subjects:
recurrent neural network (RNN)
deep neural network (DNN)
photoplethysmography (PPG)
accelerometer
human activity recognition (HAR)
embedded system
Online Access:https://www.mdpi.com/2079-9292/10/14/1715

Internet

https://www.mdpi.com/2079-9292/10/14/1715

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