Measurement System for Electromagnetic Environment in Medicine using SDR with Machine Learning

Managing the electromagnetic environment in medicine is important for establishing a good reception of wireless communications. However, introducing measurement devices of electromagnetic environment such as spectrum analyzers into clinical settings is challenging owing to their cost and the requirement for specialized skills. In this study, we propose a measurement system for monitoring the electromagnetic environment in medicine using software-defined radio (SDR) technology and machine learning (ML). We evaluated the receiver sensitivity of SDR devices and developed ML models to estimate the carrier-to-noise ratio of wireless medical telemetry services.