Joint analysis of simultaneous EEG and eye tracking data for video images

Szajerman, Dominik; Napieralski, Piotr; Lecointe, Jean‐Philippe

doi:10.1108/compel-07-2018-0281

Cited by 10 publications

(3 citation statements)

References 31 publications

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“…Szajerman et al [15] synchronized EEG and eye-tracking data by detecting key events from eye movements such as blinking. Baekgaard et al [1] proposed to do so from the EEG signal instead.…”

Section: Related Workmentioning

confidence: 99%

Gustav: Cross-device Cross-computer Synchronization of Sensory Signals

Latifzadeh

Leiva

2022

Adjunct Proceedings of the 35th Annual ACM Symposium on User Interface Software and Technology

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Temporal synchronization of behavioral and physiological signals collected through different devices (and sometimes through different computers) is a longstanding challenge in HCI, neuroscience, psychology, and related areas. Previous research has proposed to synchronize sensory signals using (1) dedicated hardware; (2) dedicated software; or (3) alignment algorithms. All these approaches are either vendor-locked, non-generalizable, or difficult to adopt in practice. We propose a simple but highly efficient alternative: instrument the stimulus presentation software by injecting supervisory event-related timestamps, followed by a post-processing step over the recorded log files. Armed with this information, we introduce Gustav, our approach to orchestrate the recording of sensory signals across devices and computers. Gustav ensures that all signals coincide exactly with the duration of each experiment condition, with millisecond precision. Gustav is publicly available as open source software. CCS CONCEPTS• Human-centered computing → Laboratory experiments; Interaction devices; HCI design and evaluation methods.

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“…Szajerman et al [15] synchronized EEG and eye-tracking data by detecting key events from eye movements such as blinking. Baekgaard et al [1] proposed to do so from the EEG signal instead.…”

Section: Related Workmentioning

confidence: 99%

Gustav: Cross-device Cross-computer Synchronization of Sensory Signals

Latifzadeh

Leiva

2022

Adjunct Proceedings of the 35th Annual ACM Symposium on User Interface Software and Technology

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“…Therefore, to supplement such analyses and obtain objective data, researchers have attempted to develop a fundamental approach for determining user emotions through electroencephalogram (EEG) sensor data, which is the stage preceding perceptual interpretation [7].…”

Section: Introduction 1backgroundmentioning

confidence: 99%

Interactive Smart Space for Single-Person Households Using Electroencephalogram through Fusion of Digital Twin and Artificial Intelligence

2021

Energies

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The core technology for building a smart space includes the capability to analyse the space for users using various sensors. The purpose of this study was to propose a personalised interactive smart space implementation model driven by the fusion of digital twin (DT) and artificial intelligence (AI) based on electroencephalogram (EEG) data. This study utilised a handheld EEG sensor to identify a user’s emotion information and focused on the connection with the space. A smart space for single-person households that responds to EEG-based biometric information was designed for an interactive space that can improve the current emotional state of the space user. The technical characteristics of DT and AI were analysed to control spatial changes according to the user’s emotional state and to address safety-related issues. Furthermore, a fusion mechanism for DT and AI was developed for intelligent motor control to change the dimensions of the space in order to improve the EEG state of the user. In addition, using an AI model that converts EEG data into emotional state information, the user’s emotional state was analysed, and key issues related to the spatial dimensions and change of space that induce psychological stability were investigated.

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“…The reliable imaging of the brain for diagnostic purposes is a very significant procedure, as the early detection of possible anomalies is deemed decisive for a successful therapy. Several defects and malfunctions in the brain’s inner structure can be spotted through various non-invasive imaging techniques (Oldendorf, 1978; Wintermark et al , 2005; Shenton et al , 2012; Kraiger and Schnizer, 2013; Zhang et al , 2014; Szajerman et al , 2018; Eichardt et al , 2019) either considering the different properties of the brain tissues or through the brain activity. The former includes the popular magnetic resonance imaging (MRI) and the computed tomography (CT) scanning, while the latter is implemented in terms of functional MRI (fMRI), positron emission tomography (PET), electroencephalography (EEG) and magnetoencephalography (MEG).…”

Section: Introductionmentioning

confidence: 99%

Transcranial ultrasonic propagation and enhanced brain imaging exploiting the focusing effect of the skull

Amanatiadis

Apostolidis

Bekiari

et al. 2020

COMPEL

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Purpose The reliable transcranial imaging of brain inner structures for diagnostic purposes is deemed crucial owing to the decisive importance and contribution of the brain in human life. The purpose of this paper is to investigate the potential application of medical ultrasounds to transcranial imaging using advanced techniques, such as the total focussing method. Design/methodology/approach Initially, the fundamental details of the total focussing method are presented, while the skull properties, such as the increased acoustic velocity and scattering, are thoroughly examined. Although, these skull characteristics constitute the main drawback of typical transcranial ultrasonic propagation algorithms, they are exploited to focus the acoustic waves towards the brain. To this goal, a virtual source is designed, considering the wave refraction, to efficiently correct the reconstructed brain image. Finally, the verification of the novel method is conducted through numerical simulations of various realistic setups. Findings The theoretically designed virtual source resembles a focussed sensor; therefore, the directivity increment, owing to the propagation through the skull, is confirmed. Moreover, numerical simulations of real-world scenarios indicate that the typical artifacts of the conventional total focussing method are fully overcome because of the increased directivity of the proposed technique, while the reconstructed image is efficiently corrected when the proposed virtual source is used. Originality/value A new systematic methodology along with the design of a flexible virtual source is developed in this paper for the reliable and precise transcranial ultrasonic image reconstruction of the brain. Despite the slight degradation owing to the skull scattering, the combined application of the total focussing method and the featured virtual source can successfully detect arbitrary anomalies in the brain that cannot be spotted by conventional techniques.

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Joint analysis of simultaneous EEG and eye tracking data for video images

Cited by 10 publications

References 31 publications

Gustav: Cross-device Cross-computer Synchronization of Sensory Signals

Gustav: Cross-device Cross-computer Synchronization of Sensory Signals

Interactive Smart Space for Single-Person Households Using Electroencephalogram through Fusion of Digital Twin and Artificial Intelligence

Transcranial ultrasonic propagation and enhanced brain imaging exploiting the focusing effect of the skull

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