Emotion recognition using wireless signals

This paper demonstrates a new technology 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. We describe the design and implementation of EQ-Radio, and demonstrate through a user study that its emotion recognition accuracy is on par with state-of-the-art emotion recognition systems that require a person to be hooked to an ECG monitor. Emotion recognition is an emerging field that has attracted much interest from both the industry and the research community.13, If we can, such machines would enable smart homes that react to our moods and adjust the lighting or music accordingly. Movie makers would have better tools to evaluate user experience. Advertisers would learn customer reaction immediately. Computers would automatically detect symptoms of depression, anxiety, and bipolar disorder, allowing early response to such conditions. More broadly, machines would no longer be limited to explicit commands, and could interact with people in a manner more similar to how we interact with each other. Existing approaches for inferring a person's emotions either rely on audiovisual cues, such as images and audio clips,22, 42, 48 or require the person to wear physiological sensors like an Electrocardiogram (ECG) monitor.7,