Software defined radio frequency sensing framework for intelligent monitoring of sleep apnea syndrome

•A non-invasive intelligent SDRF sensing framework is developed for diagnosing sleep apnea syndrome using the multi-carrier orthogonal frequency division multiplexing (OFDM) technique to extract the fine-grained WCSI.•Collected a real-time dataset of 25 subjects for 100 experiments with 14,600 records for four breathing patterns using the SDRF sensing in the lab environment.•A feature selection approach is used for feature scoring to reduce the dimensions of the dataset and extract meaningful information.•The machine learning classification models are trained on the dataset of SDRF sensing, and classification performance is evaluated.