Detection of Reading Movement from EOG Signals

Latifoğlu, Fatma; İleri, Ramis; Demirci, Esra; Altıntop, Çiğdem Gülüzar

doi:10.1109/memea49120.2020.9137290

Cited by 12 publications

(5 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Over the years researchers relied on eye movement information for reading detection. While some researchers obtained eye-movement information using camera-based eye trackers [17,27,28], some relied on the EOG signal [29][30][31]. Researchers explored reading detection in different controlled environments in the office, in transit and also during social interactions [32][33][34][35].…”

Section: A Eog-based Reading Detectionmentioning

confidence: 99%

EOG-Based Reading Detection in the Wild Using Spectrograms and Nested Classification Approach

Baray,

Ahmed,

Chowdhury

et al. 2023

IEEE Access

View full text Add to dashboard Cite

Electrooculography, also known as EOG, is a technique that is used to calculate the corneo-retinal standing potential, which is located between the cornea and the retina of the human eye. Applications of EOG include eye disease diagnosis and eye movement tracking. There has been various research on reading activity detection from EOG signals in controlled or laboratory settings. However, determining reading behaviours from data collected from real-world environments remains a challenging problem. Reading detection in practical scenarios can lead us to track our daily reading activity, in turn improving our learning experience and even workplace productivity. Tracking regular reading behaviour can also lead to further research in cognitive psychology, literacy development, reading motivation, and reading comprehension. In this study, we investigated an electrooculogram dataset that was collected on the field from 10 users who were engaged in their daily activities on two separate days. We propose a pipeline combining the statistical features with deep learning features from pretrained ImageNet models. To detect the fine-grained reading activities, we employed a nested classification approach where we detect reading and not reading at first and then do one more step of classification to discriminate among three different reading activities. With our pipeline, we could achieve 66.56% accuracy in detecting the reading activities whereas the original dataset publication showed a baseline performance of only 32%.

show abstract

Section: A Eog-based Reading Detectionmentioning

confidence: 99%

EOG-Based Reading Detection in the Wild Using Spectrograms and Nested Classification Approach

Baray,

Ahmed,

Chowdhury

et al. 2023

IEEE Access

View full text Add to dashboard Cite

show abstract

“…By acquiring the vertical and horizontal EOG, patients with severe motor disabilities have communicated with their surrounding people using EOG based speller [25]. Eight directional eye movement classification algorithm has been an effective way to analyse the aftermath effect of noise in EOG signals [26][27][28]. Several human-machine interface technologies utilize horizontal EOG signal, which has been used as a control strategy for a mobility aid [29].…”

Section: Literature Reviewmentioning

confidence: 99%

Study of electrooculography signal acquisition sites for assistive device applications

Raj¹

2021

IJATEE

View full text Add to dashboard Cite

Electrooculography (EOG) is a technique that involves the measurement of the corneo-retinal standing potential of the eye. The human eye acts as a dipole between the cornea (positive potential) and the retina (negative potential), creating an electric field around the eyeball. The resulting electric signal obtained from this field is called electrooculogram. These signals, generated by eye movements, could be measured by employing different electrode placement configurations for the acquisition. The properties of these signals change depending on the number and placement of the electrodes. The study conducted here describes EOG signal acquisition using new electrode placement configurations that employ fewer facial electrodes placed on the patient. Three pre-gelled disposable electrodes were utilized for this purpose. Only one electrode was placed on a facial location, enhancing patient comfort during the acquisition procedure. To support this study, a lowcost signal acquisition hardware was developed. Using active filtering and amplification, appropriate signal processing techniques were executed upon the horizontal EOG signal acquired to reduce noise and interference due to external conditions. Hence, this paper presents the findings of new electrode placement sites for the acquisition of EOG signals which could be used for assistive device applications while restricting the number of facial electrodes to one. Most of the studies regarding the EOG signal acquisition had been using all electrodes in the face region. In contrast, we reduced the number of electrodes in the face region, thereby providing patient comfort. The comparison was made mainly on the acquired data from these new locations to discover the configuration with the optimal signal response using data obtainedfrom seven healthy subjects. The amplitude values were being compared from the new locations with the standard acquisition sites. The findings of this study were found to have a productive result. The total gain of the system required for new electrode placement configurations was two times more than the total gain required for standard acquisition sites, and also, the amplitude was less but can be helpful for assistive device applications. The average peak to peak amplitude value of the EOG signal for the new site came around about 1.25 volt.

show abstract

“…The EOG signals were acquired via the standard 4-channel electrode placement. Latifoglu et al [18] employed random forests to detect the reading eye movements. Yan et al [19] used the backpropagation network to distinguish the eye movements with an accuracy of 96%.…”

Section: Introductionmentioning

confidence: 99%

A Robust Gaze Estimation Approach via Exploring Relevant Electrooculogram Features and Optimal Electrodes Placements

Zeng,

Tao,

Zhu

et al. 2024

IEEE J. Transl. Eng. Health Med.

View full text Add to dashboard Cite

Gaze estimation, as a technique that reflects individual attention, can be used for disability assistance and assisting physicians in diagnosing diseases such as autism spectrum disorder (ASD), Parkinson’s disease, and attention deficit hyperactivity disorder (ADHD). Various techniques have been proposed for gaze estimation and achieved high resolution. Among these approaches, electrooculography (EOG)-based gaze estimation, as an economical and effective method, offers a promising solution for practical applications. Objective: In this paper, we systematically investigated the possible EOG electrode locations which are spatially distributed around the orbital cavity. Afterward, quantities of informative features to characterize physiological information of eye movement from the temporal-spectral domain are extracted from the seven differential channels. Methods and procedures: To select the optimum channels and relevant features, and eliminate irrelevant information, a heuristical search algorithm (i.e., forward stepwise strategy) is applied. Subsequently, a comparative analysis of the impacts of electrode placement and feature contributions on gaze estimation is evaluated via 6 classic models with 18 subjects. Results: Experimental results showed that the promising performance was achieved both in the Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) within a wide gaze that ranges from −50° to +50°. The MAE and RMSE can be improved to 2.80° and 3.74° ultimately, while only using 10 features extracted from 2 channels. Compared with the prevailing EOG-based techniques, the performance improvement of MAE and RMSE range from 0.70° to 5.48° and 0.66° to 5.42°, respectively. Conclusion: We proposed a robust EOG-based gaze estimation approach by systematically investigating the optimal channel/feature combination. The experimental results indicated not only the superiority of the proposed approach but also its potential for clinical application. Clinical and translational impact statement: Accurate gaze estimation is a key step for assisting disabilities and accurate diagnosis of various diseases including ASD, Parkinson’s disease, and ADHD. The proposed approach can accurately estimate the points of gaze via EOG signals, and thus has the potential for various related medical applications.

show abstract

Detection of Reading Movement from EOG Signals

Cited by 12 publications

References 15 publications

EOG-Based Reading Detection in the Wild Using Spectrograms and Nested Classification Approach

EOG-Based Reading Detection in the Wild Using Spectrograms and Nested Classification Approach

Study of electrooculography signal acquisition sites for assistive device applications

A Robust Gaze Estimation Approach via Exploring Relevant Electrooculogram Features and Optimal Electrodes Placements

Contact Info

Product

Resources

About