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 …

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

Recognizing facial activity is a well-understood (but non-trivial) computer vision problem.
However, reliable solutions require a camera with a good view of the face, which is often …

In this work, we propose a novel single-end morphing capacitive sensing method for shape
tracking, FxC, by combining Folding origami structures and Capacitive sensing to detect the …

We present CaptAinGlove, a textile-based, low-power (≤ 1.15 Watts), privacy-conscious,
real-time on-the-edge (RTE) glove-based solution with a tiny memory footprint (≤ 2MB) …

Smaller machine learning models, with less complex architectures and sensor inputs, can
benefit wearable sensor-based human activity recognition (HAR) systems in many ways …

Surface electromyography (sEMG)-based gesture recognition in virtual/augmented reality
(VR/AR) environments faces challenges such as effective multimodal fusion and individual …

Folding is an unique structural technique to enable planer materials with motion or 3D
mechanical properties. Textile-based capacitive sensing has shown to be sensitive to the …

Combining different sensing modalities with multiple positions helps form a unified
perception and understanding of complex situations such as human behavior. Hence …

Human-robot interaction (HRI) has become increasingly ubiquitous and pervasive, with
hand gestures serving as a common means of communication between humans and robots …