• Supriyo Ghosh
• Biswarup Sasmal
• Arnab Kumar Patra
• Deeprekha Bhoumick

Hearing-impaired children often face challenges in expressing and interpreting emotions due to reduced access to auditory cues. To support their emotional understanding, this study investigates a multimodal emotion-recognition approach using combined physiological (Heart Rate, HRV, EDA peaks, EMG amplitude) and behavioral signals (facial Action Unit intensity, eye movement, and gesture dynamics). Data collected from twenty participants were analyzed through statistical feature extraction, correlation evaluation, and K-means clustering. Results identified four distinct emotion-like clusters: a mixed response group, an aroused state (fear/anger-like), a low-arousal state (sad/neutral-like), and a high-arousal state (joy/surprise-like). Physiological indicators such as HR and EDA showed strong relationships with arousal levels, while behavioral cues—particularly AU intensity and eye movement—provided expressive context. Statistical distributions further validated the reliability of these signals, and correlation patterns highlighted meaningful interdependencies between physiological responses. The findings demonstrate that integrating physiological and behavioral signals effectively differentiates emotional patterns in hearing-impaired children, offering a promising foundation for emotion-aware assistive technologies and educational tools

Multimodal Emotion Recognition, Hearing-Impaired Children, Physiological Signals, Behavioral Signals, Affective Computing, Emotion Clustering.

"MULTIMODAL EMOTION RECOGNITION FOR HEARING-IMPAIRED CHILDREN USING PHYSIOLOGICAL AND BEHAVIORAL SIGNALS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 11, page no.e594-e602, November-2025, Available :http://www.jetir.org/papers/JETIR2511474.pdf

"MULTIMODAL EMOTION RECOGNITION FOR HEARING-IMPAIRED CHILDREN USING PHYSIOLOGICAL AND BEHAVIORAL SIGNALS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 11, page no. ppe594-e602, November-2025, Available at : http://www.jetir.org/papers/JETIR2511474.pdf