LSTM-modeling of emotion recognition using peripheral physiological signals in naturalistic conversations

MS Zitouni, CY Park, U Lee… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
The automated recognition of human emotions plays an important role in develo**
machines with emotional intelligence. Major research efforts are dedicated to the …

Evaluating multimodal wearable sensors for quantifying affective states and depression with neural networks

A Ahmed, J Ramesh, S Ganguly… - IEEE Sensors …, 2023 - ieeexplore.ieee.org
With the increasing proliferation of embedded sensors in wearable devices, there is
potential for modeling individual emotional and mental state variations. The popular …

Identification of mental stress granularity from long-term ECG recordings using novel complexity analysis

S Nasrat, K Mahmoodi, A Khandoker… - 2024 46th Annual …, 2024 - ieeexplore.ieee.org
Mental health conditions often manifest as changes in physiological signals and are
characterized by specific features within these signals. However, there is limited knowledge …

Crucial Events Identify Emotion Granularity from Long-Term ECG Recordings

S Nasrat, A Khandoker, H Jelinek - 2023 Computing in …, 2023 - ieeexplore.ieee.org
The increasing interest in improving the accessibility and implementation of psychiatric
solutions in diagnosing and treating mental and neurological disorders is driven by the need …