The influence of graphical elements on user’s attention and control on a neurofeedback-based game

Vasiljevic, Gabriel Alves Mendes

doi:10.1016/j.entcom.2018.10.003

Cited by 26 publications

(10 citation statements)

References 18 publications

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“…Wearable EEG-based BCI devices, thanks to technological developments in dry electrodes and lowering prices, are now receiving considerable attention as potential research tools inside and outside the laboratory setting [16,17], especially in the gaming industry (e.g., [61]). Furthermore, their cost might enable a wide range of studies (e.g., involving low-income countries as well) that were not previously possible.…”

Section: Discussionmentioning

confidence: 99%

Validation of Electroencephalographic Recordings Obtained with a Consumer-Grade, Single Dry Electrode, Low-Cost Device: A Comparative Study

Rieiro

Díaz-Piedra

Morales

et al. 2019

Sensors

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The functional validity of the signal obtained with low-cost electroencephalography (EEG) devices is still under debate. Here, we have conducted an in-depth comparison of the EEG-recordings obtained with a medical-grade golden-cup electrodes ambulatory device, the SOMNOwatch + EEG-6, vs those obtained with a consumer-grade, single dry electrode low-cost device, the NeuroSky MindWave, one of the most affordable devices currently available. We recorded EEG signals at Fp1 using the two different devices simultaneously on 21 participants who underwent two experimental phases: a 12-minute resting state task (alternating two cycles of closed/open eyes periods), followed by 60-minute virtual-driving task. We evaluated the EEG recording quality by comparing the similarity between the temporal data series, their spectra, their signal-to-noise ratio, the reliability of EEG measurements (comparing the closed eyes periods), as well as their blink detection rate. We found substantial agreement between signals: whereas, qualitatively, the NeuroSky MindWave presented higher levels of noise and a biphasic shape of blinks, the similarity metric indicated that signals from both recording devices were significantly correlated. While the NeuroSky MindWave was less reliable, both devices had a similar blink detection rate. Overall, the NeuroSky MindWave is noise-limited, but provides stable recordings even through long periods of time. Furthermore, its data would be of adequate quality compared to that of conventional wet electrode EEG devices, except for a potential calibration error and spectral differences at low frequencies.

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Section: Discussionmentioning

confidence: 99%

Validation of Electroencephalographic Recordings Obtained with a Consumer-Grade, Single Dry Electrode, Low-Cost Device: A Comparative Study

Rieiro

Díaz-Piedra

Morales

et al. 2019

Sensors

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“…Researchers have shown that EEG Neurofeedback appears to increase cognitive skills and can be used to support the meditation learning process [10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27]. However, some recent studies found that the benefits from neurofeedback greatly differ between subjects, and in some particular cases neurofeedback does not appear to provide an advantage over meditating on one's own [28,29].…”

Section: Neurofeedback Is a Non-invasive Technique In Which Thementioning

confidence: 99%

Design of a Neurofeedback Training System for Meditation Based on EEG Technology

et al. 2021

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Meditation is a form of mental training that has therapeutic potential and cognitive benefits that may enhance attention, mental well-being, and neuroplasticity. However, the learning process is not easy because meditators do not receive immediate feedback that lets them know if they are correctly doing the activity. EEG Neurofeedback training is one of the techniques to train brain self-regulation and it has the potential to increase the effectiveness of meditation. However, the benefits greatly differ between subjects with a high percentage of inefficacy. In this work, an EEG Neurofeedback Training System is proposed based on user-centered design methodology to provide real-time performance feedback to meditators to increase levels of attention and relaxation through a visual, sound and smell stimuli interface. Levels of attention and relaxation of nine participants were measured with a mobile Neurosky EEG headset biosensor during meditation practice to analyze the incidence of each type of stimuli during activity. Visual stimuli feedback was able to increase attention levels of 78% of the participants by 11.8% compared to a meditation session without any stimuli. The sound stimuli feedback was able to increase the relaxation levels of 44.4% of the participants by 16% compared to a session without any stimuli. These results might bring new insights for the design of a neurofeedback system interface for meditation. Further research on neurofeedback training interfaces for meditators is suggested to validate these results with more participants.

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“…Special headsets are capable of detecting the changes in brainwaves and give the gamers the possibility to concentrate only on the game. The idea of attention-based mind-controlled games is gaining the attention of not only game producers but also research companies [134][135][136]. In 2018, Queiroz et al [136] launched a BCI-based game where the player has control via a wheeled robot through the Emotiv INSIGHT headset to reach a target.…”

Section: Gamingmentioning

confidence: 99%

“…The headset was tuned up to software, permitting the conversion of the commands as hot or cold through the computer interface controlling the movements of the robot-like spinning around or changing direction. In the same way, Vasiljevic in [134] and [135] launched an attention-based BCI game named Mental War, represented as a tug-of-war game. The value of attention captured by the NeuroSky MindWave headset and read during some period of time have been calculated for both players.…”

Section: Gamingmentioning

confidence: 99%

Wireless Sensors for Brain Activity—A Survey

et al. 2020

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Over the last decade, the area of electroencephalography (EEG) witnessed a progressive move from high-end large measurement devices, relying on accurate construction and providing high sensitivity, to miniature hardware, more specifically wireless wearable EEG devices. While accurate, traditional EEG systems need a complex structure and long periods of application time, unwittingly causing discomfort and distress on the users. Given their size and price, aside from their lower sensitivity and narrower spectrum band(s), wearable EEG devices may be used regularly by individuals for continuous collection of user data from non-medical environments. This allows their usage for diverse, nontraditional, non-medical applications, including cognition, BCI, education, and gaming. Given the reduced need for standardization or accuracy, the area remains a rather incipient one, mostly driven by the emergence of new devices that represent the critical link of the innovation chain. In this context, the aim of this study is to provide a holistic assessment of the consumer-grade EEG devices for cognition, BCI, education, and gaming, based on the existing products, the success of their underlying technologies, as benchmarked by the undertaken studies, and their integration with current applications across the four areas. Beyond establishing a reference point, this review also provides the critical and necessary systematic guidance for non-medical EEG research and development efforts at the start of their investigation.

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The influence of graphical elements on user’s attention and control on a neurofeedback-based game

Cited by 26 publications

References 18 publications

Validation of Electroencephalographic Recordings Obtained with a Consumer-Grade, Single Dry Electrode, Low-Cost Device: A Comparative Study

Validation of Electroencephalographic Recordings Obtained with a Consumer-Grade, Single Dry Electrode, Low-Cost Device: A Comparative Study

Design of a Neurofeedback Training System for Meditation Based on EEG Technology

Wireless Sensors for Brain Activity—A Survey

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