This repository presents a comparison of various deep learning models for Human Activity Recognition (HAR) using time series ... captures smartphone sensor signals (accelerometer and gyroscope) during ...

If the 3-axes of the human motion model are considered as the 3 channels of a RGB image, the value of the XYZ axial data can be mapped into the value of the RGB channel data in a RGB image ...

The results show that the method based on multiple features proposed in this paper dramatically outperforms the existing state-of-the-art methods for human complex activity recognition using sensor ...

2018) for use as a ground truth of when each activity ... sensor data would facilitate automatic data-driven assessment of movement quality, eliminating subjective scoring, and increasing the ability ...

Abstract: Human Activity Recognition (HAR ... algorithms have shown effective in predicting various human actions using time-series data collected from cell phones and wearable sensors. Deep ...