A novel deep learning approach for denoising and classification of SDRF sensing data for breathing patterns
This study presents a deep learning-enabled framework for non-contact respiratory pattern classification using software-defined radio frequency sensing. The proposed approach builds on an SDR-based wireless channel state information acquisition system to identify three breathing patterns: normal breathing, fast breathi...