Year: 2024
Type: conference-paper
Abstract: This paper presents a collaborative fall detection and response system integrating Wi-Fi sensing with robotic assistance. The proposed system leverages channel state information (CSI) disruptions caused by movements to detect falls in non-line-of-sight (NLOS) scenarios, offering non-intrusive monitoring. Besides, a companion robot is utilized to provide assistance capabilities to navigate and respond to incidents autonomously, improving efficiency in providing assistance in various environments. The experimental results demonstrate the effectiveness of the proposed system in detecting falls and responding effectively.
Authors: Yunwang Chen, Yaozhong Kang, Ziqi Zhao, Yue Hong, Lingxiao Meng, Max Q.-H. Meng
Institution: Southern University of Science and Technology
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Awards: G4527326195, G981542294
OpenAlex ID: W4408223411