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Eye Movement Prediction Based on Adaptive BP Neural Network
- Source :
- Scientific Programming, Vol 2021 (2021)
- Publication Year :
- 2021
- Publisher :
- Hindawi Limited, 2021.
-
Abstract
- This paper uses adaptive BP neural networks to conduct an in-depth examination of eye movements during reading and to predict reading effects. An important component for the implementation of visual tracking systems is the correct detection of eye movement using the actual data or real-world datasets. We propose the identification of three typical types of eye movements, namely, gaze, leap, and smooth navigation, using an adaptive BP neural network-based recognition algorithm for eye movement. This study assesses the BP neural network algorithm using the eye movement tracking sensors. For the experimental environment, four types of eye movement signals were acquired from 10 subjects to perform preliminary processing of the acquired signals. The experimental results demonstrate that the recognition rate of the algorithm provided in this paper can reach up to 97%, which is superior to the commonly used CNN algorithm.
- Subjects :
- Artificial neural network
Article Subject
business.industry
Computer science
media_common.quotation_subject
Eye movement
Gaze
Computer Science Applications
Identification (information)
QA76.75-76.765
Reading (process)
Component (UML)
Eye tracking
Computer vision
Artificial intelligence
Computer software
Recognition algorithm
business
Software
media_common
Subjects
Details
- Language :
- English
- ISSN :
- 10589244
- Volume :
- 2021
- Database :
- OpenAIRE
- Journal :
- Scientific Programming
- Accession number :
- edsair.doi.dedup.....19b213080fcdd3febe2a6cac5badf740