A new AI-based wireless signals could help to know inner emotions of individuals, according to a new study carried out at Queen Mary University, London.
The study demonstrates how radio waves can be used to measure heart rate and breathing signals. Furthermore, the study demonstrates how radio waves can predict the feelings of an individual in the absence of any other visual hint, such as facial expressions.
To examine this, during the initial phase, participants were asked to watch a video selected by researchers. This was to evoke one of the four basic emotions: joy, anger, sadness, and pleasure. Meanwhile, researchers emitted harmless radio signals while the individuals were watching the video, like the ones discharged from any wireless system such as WiFi or radar. The radio signals were aimed toward the individuals, and then the signals that bounced back measured. Thereafter, the changes in the signals caused by slight body movements analyzed, which helped the researchers to unveil hidden information about the heart and breathing rates of an individual.
In fact, previous research used similar wireless or non-invasive methods to detect emotions. However, for earlier such initiatives, data analysis depended on the use of classical machine learning approach, wherein an algorithm is used to find and classify emotional states for the data.
On the other hand, for the new approach, researchers employed deep learning techniques. For these techniques, an artificial neural network learns its own features from raw data that is time dependent. Using deep learning techniques, researchers revealed emotions could be detected more accurately than traditional machine learning methods.
Interestingly, deep learning allows to analyze data in a way similar how human brain would work in the event of different layers of information and to make connection between them.