Driving can occupy a large portion of daily life and often can elicit negative emotional states
like anger or stress, which can significantly impact road safety and long-term human health …

With the advancement of wireless technologies and sensing methodologies, many studies
have shown the success of re-using wireless signals (eg, WiFi) to sense human activities …

This paper demonstrates accurate human pose estimation through walls and occlusions. We
leverage the fact that wireless signals in the WiFi frequencies traverse walls and reflect off …

We present and discuss several novel applications of deep learning for the physical layer.
By interpreting a communications system as an autoencoder, we develop a fundamental …

Vital signs are crucial indicators for human health, and researchers are studying contact-free
alternatives to existing wearable vital signs sensors. Unfortunately, most of these designs …

The past few years have witnessed the great potential of exploiting channel state information
retrieved from commodity WiFi devices for respiration monitoring. However, existing …

This paper introduces RF-Pose3D, the first system that infers 3D human skeletons from RF
signals. It requires no sensors on the body, and works with multiple people and across walls …

Since human bodies are good reflectors of wireless signals, human activities can be
recognized by monitoring changes in WiFi signals. However, existing WiFi-based human …

Recently, deep learning methodologies have become popular to analyse physiological
signals in multiple modalities via hierarchical architectures for human emotion recognition …

This paper presents WiPose, the first 3D human pose construction framework using
commercial WiFi devices. From the pervasive WiFi signals, WiPose can reconstruct 3D …