학술논문

Pupil Dilation Reflecting the Characteristics of Attention Networks of Patients Using Image Processing
Document Type
Conference
Source
2022 IEEE International Conference on Electrical Engineering, Big Data and Algorithms (EEBDA) Electrical Engineering, Big Data and Algorithms (EEBDA), 2022 IEEE International Conference on. :1086-1092 Feb, 2022
Subject
Components, Circuits, Devices and Systems
Computing and Processing
Robotics and Control Systems
Temporal lobe
Technological innovation
Frontal lobe
Roads
Image processing
Epilepsy
Gaze tracking
Attention networks
Frontal lobe epilepsy
Temporal lobe epilepsy
Attention network test
Pupillometry
Language
Abstract
Attention is the basis of high-level cognitive functions of the human brain. The attention network consists of three networks: alerting, orienting, and executive network. Different type of epilepsy affects different brain regions, which could influence attention function differently. We created a computer-based automatic attention function evaluation platform with eye-tracking, which was adapted from the attention network test (ANT). Through this platform, we compared the pupil activation patterns of epilepsy patients (29 patients with frontal lobe epilepsy and 37 patients with temporal lobe epilepsy) and healthy controls (n = 29) in three networks. Participants had different patterns of pupil dilation under the three network conditions. Eye-tracking data showed that compared with the healthy control group, patients with frontal lobe epilepsy had a worse executive function, and temporal lobe epilepsy affected the patients' alerting and orienting network. Our study showed that the characteristic analysis of pupil activation curves of three networks could assist in the location of epileptogenic lesions in patients with epilepsy.