EEG-based multimodal emotion recognition: a machine learning perspective
H Liu, T Lou, Y Zhang, Y Wu, Y Xiao… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
Emotion, a fundamental trait of human beings, plays a pivotal role in shaping aspects of our
lives, including our cognitive and perceptual abilities. Hence, emotion recognition also is …
lives, including our cognitive and perceptual abilities. Hence, emotion recognition also is …
Advancements in Affective Disorder Detection: Using Multimodal Physiological Signals and Neuromorphic Computing Based on SNNs
Currently, the integration of artificial intelligence (AI) techniques with multimodal
physiological signals represents a pivotal approach to detect affective disorders (ADs). With …
physiological signals represents a pivotal approach to detect affective disorders (ADs). With …
[HTML][HTML] A comparison of personalized and generalized approaches to emotion recognition using consumer wearable devices: machine learning study
J Li, P Washington - JMIR AI, 2024 - ai.jmir.org
Background: There are a wide range of potential adverse health effects, ranging from
headaches to cardiovascular disease, associated with long-term negative emotions and …
headaches to cardiovascular disease, associated with long-term negative emotions and …
Hybrid densenet with long short-term memory model for multi-modal emotion recognition from physiological signals
A Pradhan, S Srivastava - Multimedia Tools and Applications, 2024 - Springer
Recognition of emotions from multi-modal physiological signals is one among the toughest
tasks prevailing amid the research communities. Most existing works have focused on …
tasks prevailing amid the research communities. Most existing works have focused on …
Multi-input speech emotion recognition model using mel spectrogram and GeMAPS
I Toyoshima, Y Okada, M Ishimaru, R Uchiyama… - Sensors, 2023 - mdpi.com
The existing research on emotion recognition commonly uses mel spectrogram (MelSpec)
and Geneva minimalistic acoustic parameter set (GeMAPS) as acoustic parameters to learn …
and Geneva minimalistic acoustic parameter set (GeMAPS) as acoustic parameters to learn …
Exploring contactless techniques in multimodal emotion recognition: insights into diverse applications, challenges, solutions, and prospects
In recent years, emotion recognition has received significant attention, presenting a plethora
of opportunities for application in diverse fields such as human–computer interaction …
of opportunities for application in diverse fields such as human–computer interaction …
Multi-scale transformer-based network for emotion recognition from multi physiological signals
T Vu, VT Huynh, SH Kim - arXiv preprint arXiv:2305.00769, 2023 - arxiv.org
This paper presents an efficient Multi-scale Transformer-based approach for the task of
Emotion recognition from Physiological data, which has gained widespread attention in the …
Emotion recognition from Physiological data, which has gained widespread attention in the …
Perception for Humanoid Robots
Abstract Purpose of Review The field of humanoid robotics, perception plays a fundamental
role in enabling robots to interact seamlessly with humans and their surroundings, leading to …
role in enabling robots to interact seamlessly with humans and their surroundings, leading to …
Towards Reducing Continuous Emotion Annotation Effort During Video Consumption: A Physiological Response Profiling Approach
Emotion-aware video applications (eg, gaming, online meetings, online tutoring) strive to
moderate the content presentations for a more engaging and improved user experience …
moderate the content presentations for a more engaging and improved user experience …
I DARE: IULM Dataset of Affective Responses
Consumer Neuroscience and Neuromarketing apply neuroscience tools and methodologies
to investigate consumer behavior (Karmarkar and Plassmann, 2017; Lim, 2018), addressing …
to investigate consumer behavior (Karmarkar and Plassmann, 2017; Lim, 2018), addressing …