Contrastive Analysis for Human Activity Recognition Algorithms Using WiFi Signals
Jian Zhou, Han Su, Kai Yu
Available Online December 2016.
- https://doi.org/10.2991/icwcsn-16.2017.65How to use a DOI?
- channel state information (CSI); dynamic time warping (DTW); earth mover distance (EMD); activity recognition
- Human Activity monitoring has become increasingly important and has the potential to support a wide area of applications including elder care, well-being management, fitness tracking and building surveillance. Traditional approaches involve wearable sensors and specialized hardware installations. Compared with these solutions, channel state information (CSI) has its advantage. The algorithm for human detection based on CSI Info has become increasingly important. Some prior WiFi signal based human activity recognition systems have been proposed such as Wisee, WiFall, Witrack, CARM. Different from prior works, we propose a contrastive analysis for the recognition algorithms under different transmission frequencies and activities. Finally, the experimental performance of DTW (Dynamic Time Wrapping) and EMD (Earth Mover Distance) is adopted. Our works show that EMD has a better performance than DTW in most cases.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Jian Zhou AU - Han Su AU - Kai Yu PY - 2016/12 DA - 2016/12 TI - Contrastive Analysis for Human Activity Recognition Algorithms Using WiFi Signals PB - Atlantis Press SP - 299 EP - 303 SN - 2352-538X UR - https://doi.org/10.2991/icwcsn-16.2017.65 DO - https://doi.org/10.2991/icwcsn-16.2017.65 ID - Zhou2016/12 ER -