EEG monitoring leads to an unusual development. The new headset will show the results.

Not everything what happens in Vegas stays in Vegas. The new development which was presented on an exhibition these days is able to demonstrate your emotions in a real-time and it’s going to provide extra abilities for VR-games and education. The novelty is similar to the #BasisNeuro and partially it copies the capabilities of our neurointerface which is also able to detect emotions and suggest music for your current mood. But the presented project is not a multipurpose platform of #BasisNeuro but a headset, though it’s really interesting to consider it’s abilities.

First of all you should remember: your brain generates the electricity approximately for powering the bulb on 40 vats and it possesses a unique «language» of neural codes which forms a multistable states (meaning periodically stable, but regularly changing). Nowadays researches are aimed at understanding this “language” and the functional states of the brain associated with the processes of perception, thinking and free behavior. The new headset which Imec demonstrated at an International exhibition of consumer electronics in Nevada, combines comfort of use with a low energy consumption and active dry electrodes from Datwyler and also soft for a real-time monitoring of EEG signals, detected in frontal regions of the brain, including signals connected with emotional states. But that’s not all! In order not to be bored with the headset, it contains headphone jack and compatible with Bluetooth for streaming music. According to the developers, the headset will be able to study the user’s personal music preferences and play music in a real-time that can change the user’s emotional state to the desired ones. Did you wish some fun by order and legally? It seems to be it. “Imec’s significant experience in this field is the result of almost ten years of work on creating circuits and wearable devices for EEG monitoring,” says Chris Van Hof from Imec. “Our experience in machine learning and emotion recognition helped us create a unique EEG system that links the music offered through headphones with emotional changes,” says Professor Masayuki Nu-mao from the Institute of Science. Previous studies have shown that for the recognition of emotions, the extraction of signs is as important as the classification algorithm. However, there is no standard method for extracting symptoms in the recognition of emotions, especially for a real-time monitoring, where the speed of computation is crucial and emotions change quite quickly.

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