An electrooculogram based real time system for measurement and analysis of visual stimuli for detecting strabismus and nystagmus.
01 Sep 2014-pp 1125-1130
TL;DR: To standardize the testing process, a novel real time electrooculography based system is proposed and bio sensors are used in this system to acquire EOG to identify/track the difference in alignment of both the eyes.
Abstract: Strabismus, the misalignment between the eyes, is a prevalent condition observed in the medical field. It is found in infants; patients affected by cerebral palsy and may also occur due to over usage of drugs. Nystagmus is a condition that causes involuntary, rapid movement of one or both eyes. The eye(s) may move from side to side, up and down, or in a circular motion. It is common for individuals with this condition to tilt their heads to compensate for their difficulty seeing. The individuals with these disorders are associated with difficulty in climbing stairs, reading or driving. The brain fails to take images from one of the eyes and the unused eye eventually turns blind. In the present eye examination system, to test for these disorders, manual analysis is done by a doctor or examiner. This includes the cover-uncover test where the person manually covers the affected eyes intermittently to observe the change in alignment. Also, caloric reflex test, in which warm or cold water or air is poured into one ear. Results of manual tests may vary for each patient depending on the eye examiner taking the test. To standardize the testing process, a novel real time electrooculography based system is proposed. Bio sensors are used in this system to acquire EOG to identify/track the difference in alignment of both the eyes. This can ensure the fast and accurate detection of strabismus or nystagmus affected eyes.
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01 Jul 2017
TL;DR: This research intend to develop a computer system to assist strabismus screening using the combination of computer games and eye tracking devices so that the screening results will be more accurate and exact.
Abstract: More than 5% of Thai people have strabismus. Strabismus is known as cross-eyed or wall-eyed because the visual field angle of two eyes is not parallel. The amblyopia disease is the cause of strabismus in kids. Strabismus can be completely cured if the strabismus screening can be made in early stage. Currently, strabismus screening includes methods such as Hirschberg test, cover test and Krimsky test, and etc. The strabismus screening in kids is difficult and takes a lot time in special room. This research intend to develop a computer system to assist strabismus screening using the combination of computer games and eye tracking devices so that the screening results will be more accurate and exact. This screening technique requires shorter time and it is easy to use, so it is better in terms of efficiency and reducing time for strabismus screening.
5 citations
Cites methods from "An electrooculogram based real time..."
...Some researchers used a technique called Electrooculography (EOG) which is used in recording eye movement to identify/track the strabismus, but the system setup is still complex and difficult to use [5]....
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01 Jan 2019
TL;DR: The developed technique allows automatic quantitative detection of a presence of possible strabismus and calculation of linear and vertical deviations of eyes in digital images and makes prediction using pre-trained regression model.
Abstract: Decreased vision, double vision, eye fatigue and strain associated with strabismus often require no-surgical or surgical options which may lead to overcorrection or under correction with a need for a follow up surgery. Therefore, quantitative assessment of the degree of strabismus can serve as very useful tool for deciding on therapeutic options and evaluation of their outcomes. Further, US focused statistics indicate that 4% of the population has strabismus while some global estimates attribute this anomaly only to 0.034% of world population. These contrasting statistics further lead to a necessity of having a uniform quantitative tool for a broader application to determine the scope and the degree of this anomaly in different populations. At this point variety of tests are used including Hirschberg test, Cover test, and Central Corneal Light Reflex Ratio. Therefore, the developed technique allows automatic quantitative detection of a presence of possible strabismus and calculation of linear and vertical deviations of eyes in digital images. In particular, the proposed algorithm was structured in seven stages: (1) face matching (2) face detection and alignment (3) extraction of region of interest (4) locating the iris of both eyes and their center positions (5) selection of reference points in the eyes (6) calculation of linear and vertical deviations (7) making prediction using pre-trained regression model. This methodology has 93% of accuracy, 84% of sensitivity and 30% of specificity as tested on 128 images. In particular, the outcome encompasses a methodology for two graphical user interfaces which have real time as well as local image processing capability; a bounding box approach to make the face of a person aligned; and determination of numerical linear and vertical deviations of the eyes in millimeters. While the deviation of normal eyes is close to zero, the higher numbers indicate pre-strabismus or strabismus conditions respectively.
1 citations
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01 Jan 2015
1,187 citations
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...[14] 2) Test Setup...
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TL;DR: 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.
Abstract: 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.
619 citations
"An electrooculogram based real time..." refers background in this paper
...[9] This is to check if there are distinct, involuntary eye movements when the water enters....
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TL;DR: It is possible that a crossed eye and hand preference may be partially the reason for visual-spatial and constructive disturbances observed in OCD.
Abstract: Dyslexia may be a development disturbance in which there are alterations in visual-spatial and visual-motor processing, while obsessive-compulsive disorder (OCD) is a psychiatric disease in which there are alterations in memory, executive function, and visual-spatial processing. Our hypothesis is that these disturbances may be, at least partially, the result of a crossed eye and hand preference. In the present study 16 controls, 20 OCD (DSM-IV criteria) and 13 dyslexic adults (Brazilian Dyslexia Association criteria) were included. All had a neurological examination, the Yale-Brown scale for obsessive-compulsive symptoms application and the Zazzo evaluation for laterality, abridged by Granjon. Results showed a right hand preference for 100% of controls, 84.6% of dyslexics, and 75% of OCD patients and a right eye preference for 73.3% of controls, 69.2% of dyslexics, and 35% of OCD patients. The left eye preference was significantly higher in OCD when compared with the two other groups (p = 0.01) and the left hand preference of OCD patients (25%) was also significant when compared to Brazilian population (4%) or British population (4.5%). It is possible that this crossed preference may be partially the reason for visual-spatial and constructive disturbances observed in OCD.
16 citations