A Channel State Information based Respiration Rate Monitoring Method
Changchen Wang, H. B. Liu · 2023
With the development of integrated sensing and communication (ISAC) technologies, wireless sensing based on Wi-Fi channel state information (CSI) has become a hot research topic. Most of the current CSI-based research uses deep learning methods for sensing technologies such as human respiration rate monitoring, motion recognition and indoor localization. This approach is not easy to deploy because it needs higher requirements for computational and storage resources. In this paper, we propose a CSI-based respiration rate monitoring method that reduces storage and computational resources while ensuring high recognition accuracy.