An Analysis of Entropy-Based Eye Movement Events Detection
| Autor: | Katarzyna Harezlak, Pawel Kasprowski, Dariusz R Augustyn |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Computer science
Multiresolution analysis approximate entropy 0206 medical engineering ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION General Physics and Astronomy time-scale decomposition lcsh:Astrophysics 02 engineering and technology Approximate entropy Time scale decomposition Article multiresolution analysis 03 medical and health sciences 0302 clinical medicine lcsh:QB460-466 lcsh:Science eye movement business.industry Eye movement Pattern recognition Cognition 020601 biomedical engineering Saccadic masking lcsh:QC1-999 Knn classifier Sample size determination lcsh:Q Artificial intelligence eye movement events detection business 030217 neurology & neurosurgery lcsh:Physics |
| Zdroj: | Entropy, Vol 21, Iss 2, p 107 (2019) Entropy Volume 21 Issue 2 |
| ISSN: | 1099-4300 |
| Popis: | Analysis of eye movement has attracted a lot of attention recently in terms of exploring areas of people&rsquo s interest, cognitive ability, and skills. The basis for eye movement usage in these applications is the detection of its main components&mdash namely, fixations and saccades, which facilitate understanding of the spatiotemporal processing of a visual scene. In the presented research, a novel approach for the detection of eye movement events is proposed, based on the concept of approximate entropy. By using the multiresolution time-domain scheme, a structure entitled the Multilevel Entropy Map was developed for this purpose. The dataset was collected during an experiment utilizing the &ldquo jumping point&rdquo paradigm. Eye positions were registered with a 1000 Hz sampling rate. For event detection, the knn classifier was applied. The best classification efficiency in recognizing the saccadic period ranged from 83% to 94%, depending on the sample size used. These promising outcomes suggest that the proposed solution may be used as a potential method for describing eye movement dynamics. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|