We present a wearable, oscillating magnetic field-based proximity sensing system to monitor
social distancing as suggested to prevent COVID 19 spread (being between 1.5 and 2.0m) …

Energy efficiency and low latency are crucial requirements for designing wearable AI-empowered
human activity recognition systems, due to the hard constraints of battery operations …

Social distancing and contact/exposure tracing are accepted to be critical strategies in the
fight against the COVID-19 epidemic. They are both closely connected to the ability to reliably …

Although hand gesture recognition has been widely explored with sensing modalities like
IMU, electromyography and camera, it is still a challenge of those modalities to provide a …

This work proposes an incremental learning (IL) framework for wearable sensor human activity
recognition (HAR) that tackles two challenges simultaneously: catastrophic forgetting and …

Due to the fact that roughly sixty percent of the human body is essentially composed of water,
the human body is inherently a conductive object, being able to, firstly, form an inherent …

Human activity recognition (HAR) has become an intensive research topic in the past decade
because of the pervasive user scenarios and the overwhelming development of advanced …

We present MoCaPose, a novel wearable motion capturing (MoCap) approach to continuously
track the wearer's upper body's dynamic poses through multi-channel capacitive sensing …

Smart glasses are rapidly gaining advanced functions thanks to cutting-edge computing
technologies, especially accelerated hardware architectures, and tiny Artificial IntelligenceAI …

This work presents a novel and versatile approach to employ textile capacitive sensing as
an effective solution for capturing human body movement through fashionable and everyday-…