A Comprehensive Study on Techniques Utilized for Attention Detection

The persistent focus of cognitive resources on information while disregarding distractions is what attention is best defined as. Recent advancements in eye sensors and computer vision algorithms have enabled automated monitoring of subjects' behavioral and emotional states at many levels. This paper aims to provide a detailed review of efficient techniques, utilized for detecting a subject's attention state by encapsulating statistics from a ternary data collection infrastructure. Methods that use eyelid closure, heart rate variability, motion, mindfulness, and several stimuli have been examined thoroughly. From the aforementioned, ECG, with a populous data set and convenient signal window, proved to be an effective implementation of an approach towards efficient measurement and analysis of the aforementioned data has been discussed in this paper.