System for detecting student attention pertaining and alerting

Abstract

Concentration is the ability to focus the mind on a specific context at a time. This is important to do any activities efficiently such as learning and driving. Especially, for students, it is tough to be stay focused because of the distractions. A single moment of drifting in mind may cause a significant impact on student’s performance. Therefore finding that moment and alert the student to regain attention, would help him to improve the ability to be concentrated while learning. Several types of researches have been conducted to find out the connection between concentration and human related parameters such as heart rate variability, brain waves, and facial expressions while learning. We propose a methodology to combine these three parameters, expected to overcome the limitations of one parameter by another. The extracted features from each collected data from the relevant sensors are fed into the classification models. As per the initial experiments, the primary relationships were derived with separate machine learning models for each parameter.