During the last decade, overweight and obesity have become an increasing global issue. According to WHO, in 2008, around 1.4 billion people over the age of 20 were overweight, at least 500 million were obese and at least 40 million children under the age of five were overweight.

The Food Industry's response to the obesity epidemic has been to produce a number of low fat and sugar food products that enable the consumer to eat the same food while consuming fewer calories. However, an investigation conducted by the Food Administration shows that people tend to consume extra-large servings of the light products, negating any benefits the light products might offer. 

A solution to the above-mentioned obesity epidemic requires a more thorough understanding of the brain's response to varying salt, sugar and fat levels and subjective satiation. Traditionally, food ingredient selection is based on physical and sensory analysis methods. However, in connection with salt, sugar and fat substitution products, objective measurement methods lack the ability to describe what we can register with our senses. In this regard, brain recordings are particularly interesting.

The idea behind the project is to utilise EEG methods to screen salt, sugar and fat substituents when selecting new food ingredients. The goal is to compare EEG results with physical or sensory data for new food ingredients with the hope of supplementing selection criteria for new food ingredients with objective physiological EEG responses.

Ear-EEG is a novel EEG (electroencephalography) recording approach in which the EEG signal is recorded from electrodes embedded on an ear-piece placed in the ear canal. The ear-EEG has great potentials within continuous brain monitoring in everyday life and will have application within both medical and consumer electronics devices.

The integration of brain monitoring based on EEG into everyday life has been hindered by the limited portability and long set-up time of current wearable systems as well as by the invasiveness of implanted systems.

To address these issues, the ear-EEG has been introduced which is a discreet, unobtrusive and user-centred approach to brain monitoring. The ear-EEG recording concept has been tested by using several standard EEG paradigms and benchmarked against standard on-scalp EEG.

All ear-EEG recordings made so far have been based on wet-electrode technology. In order to improve the usability and user-friendliness, this project will exploit so-called dry-contact electrode technology. This has impact on the design of the electrode itself, the supporting mechanics and the electronic instrumentation for acquiring the EEG signal.