Scientists have proposed an algorithm that can detect human emotions. The outcome is based on facial expressions and eye movements displayed from optical or video cameras. The ingenuity involves using wireless signals for emotion states recognition.
The research was conducted on 15 participants, whose heartbeat and breathing signals were recorded using radio waves. Then Deep Learning analysis and Machine Learning analysis was deployed for detection of emotional states.
Analysis was based on the deployment of machine learning techniques where they used an algorithm to identify and classify emotional states within the data. Deep learning proved to be most effective method in detecting emotions than traditional machine learning techniques.
Four basic emotion types like sadness, anger, pleasure and joy were detected. Researchers were able to draw their conclusions based on the signals caused by body movements. Analysis of body movements showed hidden information about a person’s heart and the rate of breathing.
Ahsan Noor Khan, a PHD student and one of the researchers was quoted by Venture Beat saying that: “We are now looking to probe how we could use low-cost existing systems, such as Wi-Fi routers, to detect emotions of a large number of people gathered, for instance in an office.”
However, this research is likely to raise eyebrows as it’s an infringement to privacy and questions might pop up on the limits of brain/computer interaction.
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