Preprocessing Acceleration Data and Applying Deep Learning for Human Activity Recognition

& Joaquín Ordieres-Meré
This algorithm is designed to preprocess acceleration data with different methods and classify human activities using deep convolutional neural networks based on the preprocessed data. The algorithm contains two general sections: the data preprocessing section (written in R language) and deep convolutional neural networks training and testing section (written in Python language). Four public datasets are used in this algorithm: RealWorld-2016 (Timo et.al), Skoda (P. Zappi et.al), WISDM v1.1 (Jennifer et.al) and WISDM v2.0 (Gary...
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