Mental Health Monitoring in Neurodivergent Children Using NeuroSky TGAM1: Real-Time EEG Signal Processing for Cognitive and Emotional Assessment

This study presents a real-time electroencephalography (EEG) monitoring system tailored for neurodivergent children, leveraging the affordable, single-channel NeuroSky TGAM1 sensor. We introduce a robust signal processing pipeline based on spectral power density analysis (from Delta to Gamma bands) to identify discrete cognitive-emotional states during therapy sessions. The system demonstrates 82.3% accuracy in classifying focused attention, emotional distress, and calm engagement. Crucially, our wearable implementation provides objective biomarkers for personalizing mental health interventions, effectively bridging biomedical engineering and child psychiatry. We illustrate the system’s adaptability across various therapeutic contexts; notably, our findings reveal compelling neural response patterns during dolphin-assisted therapy for children with Autism Spectrum Disorder (ASD). This low-cost, scalable solution shows significant potential for objectively evaluating therapeutic efficacy in populations with ADHD and ASD, moving beyond subjective assessments towards data-driven care.

@article{Villar2025,
  title     = {Mental Health Monitoring in Neurodivergent Children Using NeuroSky TGAM1: Real-Time EEG Signal Processing for Cognitive and Emotional Assessment},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {16},
  number    = {9},
  year      = {2025},
  publisher = {The Science and Information Organization},
  author    = {Erika Yolanda Aguilar Del Villar and Jes´us Jaime Moreno Escobar and Claudia Hern´andez Aguilar},
  doi       = {10.14569/IJACSA.2025.0160985},
  url       = {https://doi.org/10.14569/IJACSA.2025.0160985}
}