This work demonstrates a new technology, EQ-Radio, that can infer a person’s emotions from RF signals reflected off his body. EQ-Radio transmits an RF signal and analyzes its reflections off a person’s body to recognize his emotional state (happy, sad, etc.). The key enabler underlying EQ-Radio is a new algorithm for extracting the individual heartbeats from the wireless signal at an accuracy comparable to on-body ECG monitors. The resulting beats are then used to compute emotion-dependent features which feed a machine-learning emotion classifier. This work describes the design and implementation of EQ-Radio, and demonstrates through a user study that its emotion recognition accuracy is on par with stateof-the-art emotion recognition systems that require a person to be hooked to an ECG monitor.