Emotion Observation-System (EOS)
Advisor(s)
Dr. Firas Hassan
Confirmation
1
Document Type
Poster
Location
ONU McIntosh Center; Activities Room
Start Date
24-4-2026 10:00 AM
End Date
24-4-2026 10:50 AM
Abstract
The Emotion Observation System (EO-S) is a portable, multi-sensor device designed to provide real-time emotional state estimation to assist therapists, educators, and caregivers in supporting individuals with communication difficulties. This research presents a revised validation protocol focused on optimizing an embedded 1-D Convolutional Neural Network (CNN) for the classification of physiological signals. The EO-S hardware, powered by an ESP32-S3 microcontroller, integrates a suite of non-invasive sensors including heart rate (HR), galvanic skin response (GSR), pulse oximetry (SpO2), and skin temperature (SKT).
The study employs a structured emotion induction battery to collect high-fidelity, labeled data from a target population of 100–200 adults. Participants undergo six validated psychophysiological protocols: the Maastricht Acute Stress Test (MAST) for acute stress, Proximal Anticipation for anxiety, the Sustained Attention to Response Task (SART) for boredom, and standardized media-based inductions for amusement, relaxation, and neutral baselines. Physiological data is sampled every 0.25 seconds, with the embedded CNN utilizing sliding 3–5 second windows to generate real-time estimates across the emotional spectrum.
By utilizing domain-specific induction procedures and human-subject variability, this research aims to enhance the generalizability of the EO-S machine learning module and validate its efficacy as a therapeutic intervention tool. The results will contribute to the development of more responsive, non-invasive affective computing systems in clinical and educational settings.
Recommended Citation
McCluskey, Chase D. and Randall, Alexander L., "Emotion Observation-System (EOS)" (2026). ONU Student Research Colloquium. 1.
https://digitalcommons.onu.edu/student_research_colloquium/2026/Posters/1
Open Access
Available to all.
Emotion Observation-System (EOS)
ONU McIntosh Center; Activities Room
The Emotion Observation System (EO-S) is a portable, multi-sensor device designed to provide real-time emotional state estimation to assist therapists, educators, and caregivers in supporting individuals with communication difficulties. This research presents a revised validation protocol focused on optimizing an embedded 1-D Convolutional Neural Network (CNN) for the classification of physiological signals. The EO-S hardware, powered by an ESP32-S3 microcontroller, integrates a suite of non-invasive sensors including heart rate (HR), galvanic skin response (GSR), pulse oximetry (SpO2), and skin temperature (SKT).
The study employs a structured emotion induction battery to collect high-fidelity, labeled data from a target population of 100–200 adults. Participants undergo six validated psychophysiological protocols: the Maastricht Acute Stress Test (MAST) for acute stress, Proximal Anticipation for anxiety, the Sustained Attention to Response Task (SART) for boredom, and standardized media-based inductions for amusement, relaxation, and neutral baselines. Physiological data is sampled every 0.25 seconds, with the embedded CNN utilizing sliding 3–5 second windows to generate real-time estimates across the emotional spectrum.
By utilizing domain-specific induction procedures and human-subject variability, this research aims to enhance the generalizability of the EO-S machine learning module and validate its efficacy as a therapeutic intervention tool. The results will contribute to the development of more responsive, non-invasive affective computing systems in clinical and educational settings.