Fusion-based spatio-temporal feature detection for robust classification of instantaneous changes in pupil response as a correlate of cognitive response

摘要

A computationally efficient and robust approach for monitoring the instantaneous pupil response as a correlate to significant cognitive response to relevant stimuli derives data samples d(n) of the pupil diameter (area), v(n) of pupil velocity and a(n) of pupil acceleration from the pupillary response and segments the data samples into a sequence of time-shifted windows. A feature extractor extracts a plurality of spatio-temporal pupil features from the data samples from the response and baseline periods in each window. A classifier trained to detect patterns of the extracted spatio-temporal pupil features for relevant stimuli generates an output indicative of the occurrence of absence of a significant cognitive response in the subject to a relevant stimulus.