Wearable EEG Neurofeedback Based-on Machine Learning Algorithms for Children with Autism: A Randomized, Placebo-controlled Study

Curr Med Sci. 2024 Dec;44(6):1141-1147. doi: 10.1007/s11596-024-2938-3. Epub 2024 Nov 20.

Abstract

Objective: Behavioral interventions have been shown to ameliorate the electroencephalogram (EEG) dynamics underlying the behavioral symptoms of autism spectrum disorder (ASD), while studies have also demonstrated that mirror neuron mu rhythm-based EEG neurofeedback training improves the behavioral functioning of individuals with ASD. This study aimed to test the effects of a wearable mu rhythm neurofeedback training system based on machine learning algorithms for children with autism.

Methods: A randomized, placebo-controlled study was carried out on 60 participants aged 3 to 6 years who were diagnosed with autism, at two center-based intervention sites. The neurofeedback group received active mu rhythm neurofeedback training, while the control group received a sham neurofeedback training. Other behavioral intervention programs were similar between the two groups.

Results: After 60 sessions of treatment, both groups showed significant improvements in several domains including language, social and problem behavior. The neurofeedback group showed significantly greater improvements in expressive language (P=0.013) and cognitive awareness (including joint attention, P=0.003) than did the placebo-controlled group.

Conclusion: Artificial intelligence-powered wearable EEG neurofeedback, as a type of brain-computer interface application, is a promising assistive technology that can provide targeted intervention for the core brain mechanisms underlying ASD symptoms.

Keywords: artificial intelligence; autism spectrum disorder; brain-computer interface; mu rhythm; neurofeedback training; wearable technology.

Publication types

  • Randomized Controlled Trial

MeSH terms

  • Algorithms
  • Autism Spectrum Disorder / physiopathology
  • Autism Spectrum Disorder / therapy
  • Autistic Disorder / physiopathology
  • Autistic Disorder / therapy
  • Child
  • Child, Preschool
  • Electroencephalography* / methods
  • Female
  • Humans
  • Machine Learning*
  • Male
  • Neurofeedback* / instrumentation
  • Neurofeedback* / methods
  • Wearable Electronic Devices*