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      Real-time estimation of horizontal gaze angle by saccade integration using in-ear electrooculography

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          Abstract

          The manuscript proposes and evaluates a real-time algorithm for estimating eye gaze angle based solely on single-channel electrooculography (EOG), which can be obtained directly from the ear canal using conductive ear moulds. In contrast to conventional high-pass filtering, we used an algorithm that calculates absolute eye gaze angle via statistical analysis of detected saccades. The estimated eye positions of the new algorithm were still noisy. However, the performance in terms of Pearson product-moment correlation coefficients was significantly better than the conventional approach in some instances. The results suggest that in-ear EOG signals captured with conductive ear moulds could serve as a basis for light-weight and portable horizontal eye gaze angle estimation suitable for a broad range of applications. For instance, for hearing aids to steer the directivity of microphones in the direction of the user’s eye gaze.

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          Most cited references29

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          State-of-the-art in visual attention modeling.

          Modeling visual attention--particularly stimulus-driven, saliency-based attention--has been a very active research area over the past 25 years. Many different models of attention are now available which, aside from lending theoretical contributions to other fields, have demonstrated successful applications in computer vision, mobile robotics, and cognitive systems. Here we review, from a computational perspective, the basic concepts of attention implemented in these models. We present a taxonomy of nearly 65 models, which provides a critical comparison of approaches, their capabilities, and shortcomings. In particular, 13 criteria derived from behavioral and computational studies are formulated for qualitative comparison of attention models. Furthermore, we address several challenging issues with models, including biological plausibility of the computations, correlation with eye movement datasets, bottom-up and top-down dissociation, and constructing meaningful performance measures. Finally, we highlight current research trends in attention modeling and provide insights for future.
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            Eye movement analysis for activity recognition using electrooculography.

            In this work, we investigate eye movement analysis as a new sensing modality for activity recognition. Eye movement data were recorded using an electrooculography (EOG) system. We first describe and evaluate algorithms for detecting three eye movement characteristics from EOG signals-saccades, fixations, and blinks-and propose a method for assessing repetitive patterns of eye movements. We then devise 90 different features based on these characteristics and select a subset of them using minimum redundancy maximum relevance (mRMR) feature selection. We validate the method using an eight participant study in an office environment using an example set of five activity classes: copying a text, reading a printed paper, taking handwritten notes, watching a video, and browsing the Web. We also include periods with no specific activity (the NULL class). Using a support vector machine (SVM) classifier and person-independent (leave-one-person-out) training, we obtain an average precision of 76.1 percent and recall of 70.5 percent over all classes and participants. The work demonstrates the promise of eye-based activity recognition (EAR) and opens up discussion on the wider applicability of EAR to other activities that are difficult, or even impossible, to detect using common sensing modalities.
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              Blinks and saccades as indicators of fatigue in sleepiness warnings: looking tired?

              The present study examines changes in a variety of oculomotoric variables as a function of increasing sleepiness in 129 participants, who have been passed through a broad range of subjective alertness. Up to now, spontaneous eye blinks are the most promising biosignal for in-car sleepiness warnings. Reviewing the current literature on eye movements and fatigue, experimental data are provided including additional indicative oculomotoric parameters; inter-individual differences in the experiments were also assessed. Here, self-rated alertness decreased over six steps on average and proved itself a reliable measurement. Regarding oculomotoric parameters, blink duration, delay of lid reopening, blink interval and standardised lid closure speed were identified as the best indicators of subjective as well as objective sleepiness. Saccadic parameters and fixation durations also showed specific changes with increasing sleepiness. Substantial inter-individual differences in all of these variables were illustrated. Oculomotoric parameters were linked to three different components of sleepiness while driving: a) deactivation; b) decreasing attention, resulting in disinhibition of spontaneous blinks and reflexive saccades; c) increasing attempts of self-activation. Finally, implications for the development of drowsiness detection devices were discussed.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Writing – original draft
                Role: ConceptualizationRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: ResourcesRole: SoftwareRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                5 January 2018
                2018
                : 13
                : 1
                : e0190420
                Affiliations
                [1 ] Medical Research Council/Chief Scientist Office Institute of Hearing Research - Scottish Section, Glasgow, United Kingdom
                [2 ] School of Engineering, University of Glasgow, Glasgow, United Kingdom
                Tokai University, JAPAN
                Author notes

                Competing Interests: We have read the journal's policy and the authors of this manuscript have the following competing interests: pending UK patent [application no. 1709993.8]. Bernd Porr runs the company GLASGOW NEURO LTD. from which a product was used in the study. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

                Author information
                http://orcid.org/0000-0002-0870-7612
                Article
                PONE-D-17-29994
                10.1371/journal.pone.0190420
                5755791
                29304120
                d5cf2592-cba3-474a-a30a-c445efd7c38b
                © 2018 Hládek et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 14 August 2017
                : 14 December 2017
                Page count
                Figures: 12, Tables: 0, Pages: 24
                Funding
                Funded by: Oticon Fonden (DK)
                Funded by: funder-id http://dx.doi.org/10.13039/501100000265, Medical Research Council;
                Award ID: U135097131
                Funded by: funder-id http://dx.doi.org/10.13039/501100000589, Chief Scientist Office;
                Funded by: funder-id http://dx.doi.org/10.13039/501100000265, Medical Research Council;
                Award ID: MC_UU_00010/4
                This work was supported by grants from the Oticon Foundation, the UK Medical Research Council [grant nos. U135097131 and MC_UU_00010/4], and the Chief Scientist Office (Government of Scotland). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Physiology
                Sensory Physiology
                Visual System
                Eye Movements
                Medicine and Health Sciences
                Physiology
                Sensory Physiology
                Visual System
                Eye Movements
                Biology and Life Sciences
                Neuroscience
                Sensory Systems
                Visual System
                Eye Movements
                Biology and Life Sciences
                Anatomy
                Head
                Eyes
                Medicine and Health Sciences
                Anatomy
                Head
                Eyes
                Biology and Life Sciences
                Anatomy
                Ocular System
                Eyes
                Medicine and Health Sciences
                Anatomy
                Ocular System
                Eyes
                Physical Sciences
                Mathematics
                Applied Mathematics
                Algorithms
                Research and Analysis Methods
                Simulation and Modeling
                Algorithms
                Physical Sciences
                Chemistry
                Electrochemistry
                Electrode Potentials
                Engineering and Technology
                Signal Processing
                Signal Filtering
                Biology and Life Sciences
                Anatomy
                Head
                Ears
                Medicine and Health Sciences
                Anatomy
                Head
                Ears
                Biology and Life Sciences
                Neuroscience
                Cognitive Science
                Cognitive Psychology
                Attention
                Biology and Life Sciences
                Psychology
                Cognitive Psychology
                Attention
                Social Sciences
                Psychology
                Cognitive Psychology
                Attention
                Medicine and Health Sciences
                Otorhinolaryngology
                Otology
                Hearing Disorders
                Custom metadata
                Raw data and the implementation of the algorithm are available from the Nottingham Research Data Management Repository (DOI: 10.17639/nott.334).

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                Uncategorized

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