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.

Authors

Publication Details

Journal
International Journal of Advanced Computer Science and Applications
Published
2025-01-01
DOI
https://doi.org/10.14569/ijacsa.2025.0160985
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
0.00

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article

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

Jes ́us Jaime Moreno Escobar, Carlos Aguilar, Erika Yolanda Aguilar del Villar
International Journal of Advanced Computer Science and Applications
EEG and Brain-Computer Interfaces
article

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

Jes ́us Jaime Moreno Escobar, Carlos Aguilar, Erika Yolanda Aguilar del Villar
article en

Abstract

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.

International Journal of Advanced Computer Science and ApplicationsVol. 16(9)
Instituto Politécnico Nacional, Universidad Autónoma del Estado de México, Comisión de Operación y Fomento de Actividades Académicas, Instituto Politécnico Nacional, Centro de Investigación en Computación
Openalex Percentile: Top 73%
EEG and Brain-Computer Interfaces
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Mental Health Monitoring in Neurodivergent Children Using NeuroSky TGAM1: Real-Time EEG Signal Processing for Cognitive and Emotional Assessment — Jes ́us Jaime Moreno Escobar, Carlos Aguilar, et al. · International Journal of Advanced Computer Science and Applications (2025) | TGRS Research Map | TGRS