26 citations · 103 across the 33 of their papers we have counts for
9 papers · 1 filter
Bridging Generalization and Personalization in Human Activity Recognition via On-Device Few-Shot Learning
Pixi Kang, Julian Moosmann, Mengxi Liu +4
Human Activity Recognition (HAR) with different sensing modalities requires both strong generalization across diverse users and efficient personalization for individuals. However,…
Passive Body-Area Electrostatic Field (Human Body Capacitance) for Ubiquitous Computing
Sizhen Bian, Mengxi Liu, Paul Lukowicz
Passive body-area electrostatic field sensing, also referred to as human body capacitance (HBC), is an energy-efficient and non-intrusive sensing modality that exploits the human b…
TinierHAR: Towards Ultra-Lightweight Deep Learning Models for Efficient Human Activity Recognition on Edge Devices
Sizhen Bian, Mengxi Liu, Vitor Fortes Rey +2
Human Activity Recognition (HAR) on resource-constrained wearable devices demands inference models that harmonize accuracy with computational efficiency. This paper introduces Tini…
iBreath: Usage Of Breathing Gestures as Means of Interactions
Mengxi Liu, Daniel Geißler, Deepika Gurung +5
Breathing is a spontaneous but controllable body function that can be used for hands-free interaction. Our work introduces "iBreath", a novel system to detect breathing gestures si…
From Neck to Head: Bio-Impedance Sensing for Head Pose Estimation
Mengxi Liu, Lala Shakti Swarup Ray, Sizhen Bian +6
We present NeckSense, a novel wearable system for head pose tracking that leverages multi-channel bio-impedance sensing with soft, dry electrodes embedded in a lightweight, necklac…
Hybrid CNN-Dilated Self-attention Model Using Inertial and Body-Area Electrostatic Sensing for Gym Workout Recognition, Counting, and User Authentification
Sizhen Bian, Vitor Fortes Rey, Siyu Yuan +1
While human body capacitance () has been explored as a novel wearable motion sensing modality, its competence has never been quantitatively demonstrated compared to that of th…
Optimization of An Induced Magnetic Field-Based Positioning System
Sizhen Bian, Gerald Pirkl, Jingyuan Cheng +1
Using oscillating magnetic fields for indoor positioning is a robust way to resist dynamic environments. This work presents the hard- and software-related optimizations of an induc…
Assessing the Impact of Sampling Irregularity in Time Series Data: Human Activity Recognition As A Case Study
Mengxi Liu, Daniel Geißler, Sizhen Bian +2
Human activity recognition (HAR) ideally relies on data from wearable or environment-instrumented sensors sampled at regular intervals, enabling standard neural network models opti…
Collaborative Human Activity Recognition with Passive Inter-Body Electrostatic Field
Sizhen Bian, Vitor Fortes Rey, Siyu Yuan +1
The passive body-area electrostatic field has recently been aspiringly explored for wearable motion sensing, harnessing its two thrilling characteristics: full-body motion sensitiv…