Multimodal machine learning for cognitive load based on eye tracking and biosensors

被引：0
|
作者：
Vulpe-Grigorasi, Adrian [1 ]
机构：
[1] Sankt Polten Univ Appl Sci, Sankt Polten, Austria
来源：
ACM SYMPOSIUM ON EYE TRACKING RESEARCH & APPLICATIONS, ETRA 2023 | 2023年
关键词：
eye tracking; VR; biosensors; cognitive load; therapy; SYSTEMS;
D O I：
10.1145/3588015.3589534
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
Eye tracking and virtual reality are set to drive the coming decade's most innovative developments in healthcare. Two key application areas stand at the forefront: cost-effective clinical and paraclinical training, and interactive virtual settings for patients in therapy and rehabilitation. As such, our main research focus will be to develop multimodal solutions based on eye tracking and bio-signals for cognitive load assessment within the broader spectrum of applied computer science and digital health. One of the objectives is to respond to the need for healthcare to become ever more individualized and multimodal, as exemplified by personalized medicine and digital therapeutics. The use of eye-tracking in conjunction with digital biomarkers intends to be a quantitative basis for care providers to adapt their therapies to user and patient needs.
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页数：3
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