FOCUS: Detecting ADHD Patients by an EEG-Based Serious Game

Alchalabi, Alaa Eddin; Shirmohammadi, Shervin; Eddin, Amer Nour; Elsharnouby, Mohamed

doi:10.1109/tim.2018.2838158

Cited by 95 publications

(64 citation statements)

References 25 publications

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“…In such cases, each study's structure was evaluated to determine if the system, as reported, could be used as to estimate drowsiness. If not, it was excluded from the final review (Alchalabi et al, 2018 ).…”

Section: Search Methodologymentioning

confidence: 99%

A Systemic Review of Available Low-Cost EEG Headsets Used for Drowsiness Detection

LaRocco

Paeng

2020

Front. Neuroinform.

114

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Drowsiness is a leading cause of traffic and industrial accidents, costing lives and productivity. Electroencephalography (EEG) signals can reflect awareness and attentiveness, and low-cost consumer EEG headsets are available on the market. The use of these devices as drowsiness detectors could increase the accessibility of safety and productivity-enhancing devices for small businesses and developing countries. We conducted a systemic review of currently available, low-cost, consumer EEG-based drowsiness detection systems. We sought to determine whether consumer EEG headsets could be reliably utilized as rudimentary drowsiness detection systems. We included documented cases describing successful drowsiness detection using consumer EEG-based devices, including the Neurosky MindWave, InteraXon Muse, Emotiv Epoc, Emotiv Insight, and OpenBCI. Of 46 relevant studies, ∼27 reported an accuracy score. The lowest of these was the Neurosky Mindwave, with a minimum of 31%. The second lowest accuracy reported was 79.4% with an OpenBCI study. In many cases, algorithmic optimization remains necessary. Different methods for accuracy calculation, system calibration, and different definitions of drowsiness made direct comparisons problematic. However, even basic features, such as the power spectra of EEG bands, were able to consistently detect drowsiness. Each specific device has its own capabilities, tradeoffs, and limitations. Widely used spectral features can achieve successful drowsiness detection, even with low-cost consumer devices; however, reliability issues must still be addressed in an occupational context.

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Section: Search Methodologymentioning

confidence: 99%

A Systemic Review of Available Low-Cost EEG Headsets Used for Drowsiness Detection

LaRocco

Paeng

2020

Front. Neuroinform.

114

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“…A MVS foi usada em 25% dos trabalhos analisados. Por Alchalabi et al (2017Alchalabi et al ( ) (2018 A Rede Neural Artificialé uma técnica de AM amplamente utilizada naárea. Uma de suas muitas aplicaçõesé o planejamento de caminhos, pois ela tem uma grande capacidade de aprender caminhos não lineares (Ahmad et al, 2013).…”

Section: Figura 2 Técnicas De Aprendizado De Máquinaunclassified

“…O FOCUS, apresentado por Alchalabi et al (2017Alchalabi et al ( ) (2018, teve o objetivo de treinar e fortalecer a capacidade de atenção dos pacientes com TDAH e detectar seu nível de atenção. Este trabalho teve duas publicações inclusas nessa RSL com qualis A1 e B3, e 9 e 6 páginas.…”

Section: Quais Os Principais Jogos Sérios Que Utilizam Aprendizagem Dunclassified

“…Seu desempenho não foi muito encorajador para o exercício de agarrar em microcirurgias, provavelmente pelos poucos dados de treinamento, o que pode ser melhorado com a inclusão de mais dados de treinamento.No trabalho apresentado porAlchalabi et al (2017), o Aprendizado Supervisionado foi usado na representação dos modelos de níveis de atenção dos usuários. O aprendizado se mostrou eficiente na classificação dos dados de Eletroencefalografia (EEG) dos usuários, entretanto, foram usados poucos números de amostras e apenas de usuários saudáveis e não de pessoas diagnosticadas com TDAH, o que era objetivo do trabalho Alchalabi et al (2018). apresentaram o mesmo aprendizado do trabalho mencionado anteriormente, mas foram apresentados novos resultados e validações, o que demonstrou uma taxa de 96% de acerto na classificação dos dados do EEG para detectar o estado de atenção correto durante o jogo em indivíduos saudáveis, e de 98% na classificação dos dados do EEG para detectar o estado de atenção correto durante o jogo em indivíduos com TDAH.…”

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Aprendizado de Máquina nos Jogos para Medicina: Uma Revisão Sistemática

Silva

Oliveira

Neto

et al. 2019

Anais Do Simpósio Brasileiro De Computação Aplicada À Saúde (SBCAS 2019)

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This work presents a Systematic Literature Review of Machine Learning Literature in Games for Medicine held in 4 international research sources in the last 10 years, whose objective is to identify the state of the art of machine learning in medical games. As a result of the Systematic Review presented in this study, 1040 papers were analyzed, of which 40 were pre-selected and 12 were selected for data extraction. Among the selected works, it was possible to list several techniques of machine learning, types of learning, health areas and games used today.Resumo. Este trabalho apresenta a condução de uma Revisão Sistemática da Literatura sobre o Aprendizado de Máquina em Jogos para medicina realizada em 4 fontes de pesquisa internacionais nosúltimos 10 anos, cujo objetivoé identificar o estado da arte do aprendizado de máquina nos jogos para medicina. Como resultado da Revisão Sistemática apresentada neste trabalho, foram analisados 1040 trabalhos, e desse total, 40 foram pré-selecionados e 12 foram selecionados para extração de dados. Entre os trabalhos selecionados, foi possível elencar várias técnicas de aprendizado de máquina, tipos de aprendizado,áreas da saúde e jogos utilizados na atualidade.

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“…Some SGs include neurofeedback systems; It has been shown that these improve executive control in subjects with ADHD in combination with pharmacological treatment [39]. Other SGs use electroencephalogram (EEG) feedback to train attention ability [40]. In a pilot study, Lau et al [41] investigated the effectiveness of a brain-computer interface (Braingame Brian [42]) in ADHD and found an increase in the ability to control inattentive symptoms and hyperactive-impulsive symptoms.…”

Section: Introductionmentioning

confidence: 99%

Antonyms: A Computer Game to Improve Inhibitory Control of Impulsivity in Children with Attention Deficit/Hyperactivity Disorder (ADHD)

Crepaldi

Colombo²,

Mottura³

et al. 2020

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The design of a computer-supported serious game concerning inhibition skills in children with Attention Deficit/Hyperactivity Disorder (ADHD) is reported. The game consists of a series of activities, each eliciting the tendency to respond in an immediate, inadequate way. The game is based on the Dual Pathway Model of ADHD proposed by Sonuga-Barke. In the game, children must block impulsive tendencies, reflect upon the situation, inhibit irrelevant thoughts, and find the non-intuitive solution. In the game, the player personifies a superhero, who is asked to save a realm on the opposite side of the Earth (Antonyms) where things happen according to the opposite of the usual rules. The hero faces a series of challenges, in the form of mini-games, to free the planet from enemies crossing different scenarios. To succeed in the game, the player should change his/her attitude by thinking before performing any action rather than acting on impulse. The player is induced to be reflective and thoughtful as well. Results from the evaluation of a preliminary version of the serious game are reported. They support the notion that Antonyms is an adequate tool to lead children to inhibit their tendency to behave impulsively.

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FOCUS: Detecting ADHD Patients by an EEG-Based Serious Game

Cited by 95 publications

References 25 publications

A Systemic Review of Available Low-Cost EEG Headsets Used for Drowsiness Detection

A Systemic Review of Available Low-Cost EEG Headsets Used for Drowsiness Detection

Aprendizado de Máquina nos Jogos para Medicina: Uma Revisão Sistemática

Antonyms: A Computer Game to Improve Inhibitory Control of Impulsivity in Children with Attention Deficit/Hyperactivity Disorder (ADHD)

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