Monitoring Human Attention with a Portable EEG Sensor and Supervised Machine Learning

For several healthcare applications, it is important to monitor the attention level of people, especially in the fields of rehabilitation and psychology. The recent availability of cheap and portable EEG readers has enabled continuous and unobtrusive acquisition of EEG signals. Those signals may be preprocessed and analysed with machine learning algorithms to estimate the attention level of people without interfering with their current activities. In this paper, we report our experience with attention level estimation using two kinds of devices: an off-the-shelf portable EEG headset, and a more sophisticated EEG device.