Brain computer interface for diagnosis of ASD
Year: 2024
Type: article
Abstract: ASD, or Autism Spectrum Disorder, is a complex neurodevelopmental disorder that significantly impacts an individual's social communication abilities and overall communication skills. Traditional diagnostic methods for ASD face several challenges, including a high degree of subjectivity and difficulties in early identification, which can delay crucial interventions. In this context, Brain-Computer Interface (BCI) technology emerges as a promising solution. BCI technology offers the capability to provide real-time and objective data on neural activity by directly interpreting brain signals. The paper begins by detailing the clinical characteristics of ASD, highlighting the diverse range of symptoms and behaviors that can manifest in affected individuals. It also discusses the limitations of current diagnostic methods, emphasizing the need for more objective tools. Following this, the fundamental principles and classifications of BCI technology are explained in depth, outlining how it works and the various types of BCIs available. Specific application cases of BCI technology in the diagnosis of ASD are presented, illustrating its practical utility in clinical settings. In conclusion, the paper summarizes the key points discussed and anticipates future developments in the field.
Source: Theoretical and Natural Science
Author: Yuqi Wang
Institution: Northeastern University
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: hybrid
OpenAlex ID: W4405120013