A Cost-Effective Eye-Tracker for Early Detection of Mild Cognitive Impairment

被引：2

作者：

Greco, Danilo ^{[1
]}

Masulli, Francesco ^{[1
,2
]}

Rovetta, Stefano ^{[1
,2
]}

Cabri, Alberto ^{[1
,2
]}

Daffonchio, Davide ^{[1
]}

机构：

[1] Univ Genoa, DIBRIS, Via Dodecaneso 35, I-16146 Genoa, Italy

[2] Vega Res Labs Srl, Via Ippolito dAste 7-5, I-16121 Genoa, Italy

来源：

2022 IEEE 21ST MEDITERRANEAN ELECTROTECHNICAL CONFERENCE (IEEE MELECON 2022) | 2022年

关键词：

Eye-tracker; Alzheimer's disease; Mild Cognitive Impairment; Early Detection; Raspberry; Webcam; Heart Rate Variability; Photoplethysmography; !text type='Python']Python[!/text; Neural Networks; PAIRED-COMPARISON TASK; MOVEMENTS;

D O I：

10.1109/MELECON53508.2022.9843008

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper presents a low-cost eye-tracker aimed at carrying out tests based on a Visual Paired Comparison protocol for the early detection of Mild Cognitive Impairment. The proposed eye-tracking system is based on machine learning algorithms, a standard webcam, and two personal computers that constitute, respectively, the "Measurement Sub-System" performing the test on the patients and the "Test Management Sub-System" used by medical staff for configuring the test protocol, recording the patient data, monitoring the test and storing the test results. The system also integrates an stress estimator based on the measurement of heart rate variability obtained with photoplethysmography.

引用

页码：1141 / 1146

页数：6

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