Technologies to support the diagnosis and/or treatment of neurodevelopmental disorders: A systematic review

Szkodo, Marzena Oliveira Ribas Previously Marzena; Micai, Martina; Caruso, Angela; Fulceri, Francesca; Fazio, Maria; Scattoni, María Luisa

doi:10.1016/j.neubiorev.2022.105021

Cited by 15 publications

(25 citation statements)

References 230 publications

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“…In our literature search we found two other reviews that dealt with the topic of NF in relation to ASD, but they were not included in our work for two reasons. First, in the review by Ribas et al (2022) , the NF interventions were different from the one examined in our review (i.e., the MRS-NFB) and, secondly, although in the work of Hurt et al (2014) there were four studies based on NF training, only two had used the protocol targeting the Mu rhythm ( Pineda et al, 2008 ) and they were both already mentioned in the 2020 review by Kumari and Sharma cited previously.…”

Section: The Integrated Bf + Nf Approachmentioning

confidence: 85%

Integrated use of biofeedback and neurofeedback techniques in treating pathological conditions and improving performance: a narrative review

Tosti,

Corrado,

Mancone

et al. 2024

Front. Neurosci.

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In recent years, the scientific community has begun tо explore the efficacy оf an integrated neurofeedback + biofeedback approach іn various conditions, both pathological and non-pathological. Although several studies have contributed valuable insights into its potential benefits, this review aims tо further investigate its effectiveness by synthesizing current findings and identifying areas for future research. Our goal іs tо provide a comprehensive overview that may highlight gaps іn the existing literature and propose directions for subsequent studies. The search for articles was conducted on the digital databases PubMed, Scopus, and Web of Science. Studies to have used the integrated neurofeedback + biofeedback approach published between 2014 and 2023 and reviews to have analyzed the efficacy of neurofeedback and biofeedback, separately, related to the same time interval and topics were selected. The search identified five studies compatible with the objectives of the review, related to several conditions: nicotine addiction, sports performance, Autism Spectrum Disorder (ASD), and Attention Deficit Hyperactivity Disorder (ADHD). The integrated neurofeedback + biofeedback approach has been shown to be effective in improving several aspects of these conditions, such as a reduction in the presence of psychiatric symptoms, anxiety, depression, and withdrawal symptoms and an increase in self-esteem in smokers; improvements in communication, imitation, social/cognitive awareness, and social behavior in ASD subjects; improvements in attention, alertness, and reaction time in sports champions; and improvements in attention and inhibitory control in ADHD subjects. Further research, characterized by greater methodological rigor, is therefore needed to determine the effectiveness of this method and the superiority, if any, of this type of training over the single administration of either. This review іs intended tо serve as a catalyst for future research, signaling promising directions for the advancement оf biofeedback and neurofeedback methodologies.

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Section: The Integrated Bf + Nf Approachmentioning

confidence: 85%

Integrated use of biofeedback and neurofeedback techniques in treating pathological conditions and improving performance: a narrative review

Tosti,

Corrado,

Mancone

et al. 2024

Front. Neurosci.

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“…The application of CNN to EEG data pre- and post-physical activity interventions has shed light on the neurophysiological shifts that might underlie observed behavioral changes in ADHD patients. CNN's adeptness at detecting spatial hierarchies in data makes it uniquely suited to identifying patterns within the complex signals characteristic of EEG recordings (Ribas et al, 2023 ), providing a conduit for exploring the neurobiological impact of exercise on individuals with ADHD.…”

Section: Related Workmentioning

confidence: 99%

Using artificial intelligence methods to study the effectiveness of exercise in patients with ADHD

Yu,

Fang

2024

Front. Neurosci.

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Attention Deficit Hyperactivity Disorder (ADHD) is a prevalent neurodevelopmental disorder that significantly affects children and adults worldwide, characterized by persistent inattention, hyperactivity, and impulsivity. Current research in this field faces challenges, particularly in accurate diagnosis and effective treatment strategies. The analysis of motor information, enriched by artificial intelligence methodologies, plays a vital role in deepening our understanding and improving the management of ADHD. The integration of AI techniques, such as machine learning and data analysis, into the study of ADHD-related motor behaviors, allows for a more nuanced understanding of the disorder. This approach facilitates the identification of patterns and anomalies in motor activity that are often characteristic of ADHD, thereby contributing to more precise diagnostics and tailored treatment strategies. Our approach focuses on utilizing AI techniques to deeply analyze patients' motor information and cognitive processes, aiming to improve ADHD diagnosis and treatment strategies. On the ADHD dataset, the model significantly improved accuracy to 98.21% and recall to 93.86%, especially excelling in EEG data processing with accuracy and recall rates of 96.62 and 95.21%, respectively, demonstrating precise capturing of ADHD characteristic behaviors and physiological responses. These results not only reveal the great potential of our model in improving ADHD diagnostic accuracy and developing personalized treatment plans, but also open up new research perspectives for understanding the complex neurological logic of ADHD. In addition, our study not only suggests innovative perspectives and approaches for ADHD treatment, but also provides a solid foundation for future research exploring similar complex neurological disorders, providing valuable data and insights. This is scientifically important for improving treatment outcomes and patients' quality of life, and points the way for future-oriented medical research and clinical practice.

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“…Continued exploration into Communication Disorders is imperative to enhance comprehension and treatment of these intricate conditions affecting a substantial segment of the global population (Ribas et al, 2023;Spicer-Cain et al, 2023;Westby & Watson, 2021, pp. 560-561).…”

Section: Future Directionsmentioning

confidence: 99%

Exploring The Effects of English as a Foreign Language on First Language Development of Young Children: The Case of Greece

Jansen

2024

IJELD

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This study meticulously investigates the interplay between Early Second Language Acquisition (ESLA) and the potential emergence of first language disorders in the unique context of Greece. Embedded in the Complex Dynamic Systems Theory (CDST) paradigm, it aims to untangle existing ambiguities and explore implications for Greek society and education. Employing a Concurrent Mixed Methods Approach, the study attempts to unveil the intricate impacts of ESLA on First Language Development (FLD).Grounded in CDST's framework emphasizing linguistic system complexity, and interconnectedness, the research design employs a Descriptive Exploratory orientation through a Case Study Methodology. This facilitates comprehensive research into two cohorts of children aged four, representing monolingual Greek kindergartens (Cohort A) and English as a Foreign Language (EFL)-focused kindergartens (Cohort B).The research inquiries delve into multifaceted language development aspects amidst intricate linguistic dynamics. This involves nuanced analysis of potential performance disparities in the primary language pre- and post-interventions in early foreign language pedagogy, meticulous comparative assessment of both cohorts, and insightful exploration of EFL's implications on young children's nascent language development.Methodologically, data collection employs a language development assessment tool (Logometro®). The collection of both quantitative and qualitative data in this study is contingent upon the application of the Logometro® language assessment instrument. Thematic Analysis shapes the qualitative corpus, complemented by statistical analyses for quantitative data.Anticipated outcomes aim to enhance understanding among Greek educational authorities and the scientific community about intricate, adaptive ESLA impacts on FLD. Findings could influence enduring, impactful EFL policies shaped by Greek authorities. Overall, the research deepens comprehension of latent consequences tied to ESLA's effects on FLD, set within Greece’s intricate context. Nested within CDST's theoretical framework, the amalgamation of research methodology and insights provides a robust foundation for future inquiries and invaluable guidance for policymakers navigating English language education decisions among young learners.

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Technologies to support the diagnosis and/or treatment of neurodevelopmental disorders: A systematic review

Cited by 15 publications

References 230 publications

Integrated use of biofeedback and neurofeedback techniques in treating pathological conditions and improving performance: a narrative review

Integrated use of biofeedback and neurofeedback techniques in treating pathological conditions and improving performance: a narrative review

Using artificial intelligence methods to study the effectiveness of exercise in patients with ADHD

Exploring The Effects of English as a Foreign Language on First Language Development of Young Children: The Case of Greece

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