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A Randomized Trial Utilizing EEG Brain Computer Interface to Improve Facial Emotion Recognition in Autistic Adults.
Brewe, Alexis M; Antezana, Ligia; Carlton, Corinne N; Gracanin, Denis; Richey, John A; Kim, Inyoung; White, Susan W.
Afiliação
  • Brewe AM; Center for Youth Development and Intervention, University of Alabama, 101 McMillan Building, 200 Hackberry Lane, Tuscaloosa, AL, 35487, USA. abrewe@crimson.ua.edu.
  • Antezana L; Department of Psychology, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA.
  • Carlton CN; Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.
  • Gracanin D; Department of Psychology, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA.
  • Richey JA; Department of Computer Science, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA.
  • Kim I; Department of Psychology, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA.
  • White SW; Department of Statistics, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA.
J Autism Dev Disord ; 2024 Jun 28.
Article em En | MEDLINE | ID: mdl-38941048
ABSTRACT

PURPOSE:

Many individuals with autism spectrum disorder (ASD) experience challenges with facial emotion recognition (FER), which may exacerbate social difficulties in ASD. Few studies have examined whether FER can be experimentally manipulated and improved for autistic people. This study utilized a randomized controlled trial design to examine acceptability and preliminary clinical impact of a novel mixed reality-based neurofeedback program, FER Assistant, using EEG brain computer interface (BCI)-assisted technology to improve FER for autistic adolescents and adults.

METHODS:

Twenty-seven autistic male participants (M age 21.12 years; M IQ 105.78; 85% white) were randomized to the active condition to receive FER Assistant (n = 17) or waitlist control (n = 10). FER Assistant participants received ten sessions utilizing BCI-assisted neurofeedback training in FER. All participants, regardless of randomization, completed a computerized FER task at baseline and endpoint.

RESULTS:

Results partially indicated that FER Assistant was acceptable to participants. Regression analyses demonstrated that participation in FER Assistant led to group differences in FER at endpoint, compared to a waitlist control. However, analyses examining reliable change in FER indicated no reliable improvement or decline for FER Assistant participants, whereas two waitlist participants demonstrated reliable decline.

CONCLUSION:

Given the preliminary nature of this work, results collectively suggest that FER Assistant may be an acceptable intervention. Results also suggest that FER may be a potential mechanism that is amenable to intervention for autistic individuals, although additional trials using larger sample sizes are warranted.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article