M4X: Enhancing Cross-View Generalizability in RF-Based Human Activity Recognition by Exploiting Synthetic Data in Metric Learning

M Liu, Z Xie, F Ye - 2024 IEEE/ACM Conference on Connected …, 2024 - ieeexplore.ieee.org
Human activity recognition provides insights into physical and mental well-being by
monitoring patterns of movement and behavior, facilitating personalized interventions and …

A Paradigm Shift from an Experimental-Based to a Simulation-Based Framework Using Motion-Capture Driven MIMO Radar Data Synthesis

S Waqar, M Muaaz, S Sigg, M Pätzold - IEEE Sensors Journal, 2024 - ieeexplore.ieee.org
The development of radar-based classifiers driven by empirical data can be highly
demanding and expensive due to the unavailability of radar data. In this article, we introduce …

SMART: Scene-motion-aware human action recognition framework for mental disorder group

Z Lai, J Yang, S Xia, Q Wu, Z Sun, W Yu… - arXiv preprint arXiv …, 2024 - arxiv.org
Patients with mental disorders often exhibit risky abnormal actions, such as climbing walls or
hitting windows, necessitating intelligent video behavior monitoring for smart healthcare with …

Synthetic Radar Signal Generator for Human Motion Analysis

E Pocoma, HC Yildirim, JF Determe… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Synthetic generation of radar signals is an attractive solution to alleviate the lack of
standardized datasets containing paired radar and human-motion data. Unfortunately …

A Simulation-Based Framework for the Design of Direction-Independent Human Activity Recognition Systems Using Radar Sensors

S Waqar - Doctoral dissertations at University of Agder, 2024 - uia.brage.unit.no
Human activity recognition (HAR) systems play an important role in understanding and
interpreting human movements across various domains, with applications ranging from …