Construction and Operation of a High-Speed, High-Precision Eye Tracker for Tight Stimulus Synchronization and Real-Time Gaze Monitoring in Human and Animal Subjects

Farivar, Reza; Michaud-Landry, Danny

doi:10.3389/fnsys.2016.00073

Cited by 6 publications

(5 citation statements)

References 3 publications

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“…In research settings, models for eye and gaze have not replaced the standard individual-based calibration, because of the desire to keep the measurement error and cost at a minimum. It would be interesting to see if the simple replacement calibration method suggested here could be used with the high-precision cost-effective design from McGill (Farivar & Michaud-Landry, 2016), making eye-tracking studies dramatically more accessible in a variety of settings.…”

Section: Discussionmentioning

confidence: 99%

A nonvisual eye tracker calibration method for video-based tracking

et al. 2018

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Video-based eye trackers have enabled major advancements in our understanding of eye movements through their ease of use and their non-invasiveness. One necessity to obtain accurate eye recordings using video-based trackers is calibration. The aim of the current study was to determine the feasibility and reliability of alternative calibration methods for scenarios in which the standard visual-calibration is not possible. Fourteen participants were tested using the EyeLink 1000 Plus video-based eye tracker, and each completed the following 5-point calibration methods: 1) standard visual-target calibration, 2) described calibration where participants were provided with verbal instructions about where to direct their eyes (without vision of the screen), 3) proprioceptive calibration where participants were asked to look at their hidden finger, 4) replacement calibration, where the visual calibration was performed by 3 different people; the calibrators were temporary substitutes for the participants. Following calibration, participants performed a simple visually-guided saccade task to 16 randomly presented targets on a grid. We found that precision errors were comparable across the alternative calibration methods. In terms of accuracy, compared to the standard calibration, non-visual calibration methods (described and proprioception) led to significantly larger errors, whilst the replacement calibration method had much smaller errors. In conditions where calibration is not possible, for example when testing blind or visually impaired people who are unable to foveate the calibration targets, we suggest that using a single stand-in to perform the calibration is a simple and easy alternative calibration method, which should only cause a minimal decrease in accuracy.

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Section: Discussionmentioning

confidence: 99%

A nonvisual eye tracker calibration method for video-based tracking

et al. 2018

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“…Components of a typical eye gaze system, adapted from [22,38]. The optical and the visual axes are used for the calibration process commonly required to set up the eye gaze system [22,39].…”

Section: Figurementioning

confidence: 99%

Augmentative and Alternative Communication (AAC) Advances: A Review of Configurations for Individuals with a Speech Disability

Elsahar

Bouazza-Marouf

et al. 2019

Sensors

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High-tech augmentative and alternative communication (AAC) methods are on a constant rise; however, the interaction between the user and the assistive technology is still challenged for an optimal user experience centered around the desired activity. This review presents a range of signal sensing and acquisition methods utilized in conjunction with the existing high-tech AAC platforms for individuals with a speech disability, including imaging methods, touch-enabled systems, mechanical and electro-mechanical access, breath-activated methods, and brain–computer interfaces (BCI). The listed AAC sensing modalities are compared in terms of ease of access, affordability, complexity, portability, and typical conversational speeds. A revelation of the associated AAC signal processing, encoding, and retrieval highlights the roles of machine learning (ML) and deep learning (DL) in the development of intelligent AAC solutions. The demands and the affordability of most systems hinder the scale of usage of high-tech AAC. Further research is indeed needed for the development of intelligent AAC applications reducing the associated costs and enhancing the portability of the solutions for a real user’s environment. The consolidation of natural language processing with current solutions also needs to be further explored for the amelioration of the conversational speeds. The recommendations for prospective advances in coming high-tech AAC are addressed in terms of developments to support mobile health communicative applications.

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“…and dist and meandist are the distances from the eye to the screen and from the eye to the tracker respectively [22,37]. Components of a typical eye gaze system, adapted from [22,38]. The optical and the visual axes are used for the calibration process commonly required to set up the eye gaze system [22,39].…”

Section: Aac Signal Sources and Associated Processingmentioning

confidence: 99%

Augmentative and Alternative Communication (AAC) Advances: A Review of Configurations for Speech Disabled Individuals

Elsahar¹,

Hu²,

Bouazza-Marouf³

et al. 2019

Preprint

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High-tech augmentative and alternative communication (AAC) methods are on a constant rise; however, the interaction between the user and the assistive technology is still challenged for an optimal user experience centered around the desired activity. This review presents a range of signal sensing and acquisition methods utilized in conjunction with the existing high-tech AAC platforms for speech disabled individuals, including imaging methods, touch-enabled systems, mechanical and electro-mechanical access, breath-activated methods, and brain computer interfaces (BCI). The listed AAC sensing modalities are compared in terms of ease of access, affordability, complexity, portability, and typical conversational speeds. A revelation of the associated AAC signal processing, encoding, and retrieval highlights the roles of machine learning (ML) and deep learning (DL) in the development of intelligent AAC solutions. The demands and the affordability of most systems were found to hinder the scale of usage of high-tech AAC. Further research is indeed needed for the development of intelligent AAC applications reducing the associated costs and enhancing the portability of the solutions for a real user’s environment. The consolidation of natural language processing with current solutions also needs to be further explored for the amelioration of the conversational speeds. The recommendations for prospective advances in coming high-tech AAC are addressed in terms of developments to support mobile health communicative applications.

show abstract

Construction and Operation of a High-Speed, High-Precision Eye Tracker for Tight Stimulus Synchronization and Real-Time Gaze Monitoring in Human and Animal Subjects

Cited by 6 publications

References 3 publications

A nonvisual eye tracker calibration method for video-based tracking

A nonvisual eye tracker calibration method for video-based tracking

Augmentative and Alternative Communication (AAC) Advances: A Review of Configurations for Individuals with a Speech Disability

Augmentative and Alternative Communication (AAC) Advances: A Review of Configurations for Speech Disabled Individuals

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