Multimodal physiological signals have been integrated to differentiate between discrete emotions. By integrating six physiological signals, the model accurately classifies emotions of gratitude, fear, amusement, tenderness, disgust, and sadness, thereby enhancing the precision of emotion recognition.
Abstract A physiological signal based emotion recognition system was designed. The system was developed to operate as a user independent system, based on three ...
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Emotion recognition system design using multi-physiological signals
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A physiological signal-based emotion recognition system was designed. The system was developed to operate as a use r-independent system, based on three ...
Sep 8, 2022 · We propose a substructure-based joint probability domain adaptation algorithm (SSJPDA) to overcome physiological signals' noise effect.
In this paper, we present a comprehensive review on physiological signal-based emotion recognition, including emotion models, emotion elicitation methods.
We propose a novel multimodal fusion method that considers both heterogeneity and correlation simultaneously, and realizes an end-to-end multimodal emotion ...
Nov 26, 2024 · This study aimed to develop an objective emotion recognition system that integrates multiple physiological signals. We use wearable devices to ...
In this paper, we propose a novel conformer-based system that uses multiple physiological signals collected from off-the-shelf, low-cost mobile and wearable ...
Mar 31, 2022 · I used. EMG and PPG sensors to measure psychologically relevant signals and provide data for emotion classification. I propose a two-dimensional ...
This review examines the current state of multimodal emotion recognition methods that integrate visual, vocal or physiological modalities for practical emotion ...