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[HTML][HTML] A survey on databases for multimodal emotion recognition and an introduction to the VIRI (visible and InfraRed image) database
Multimodal human–computer interaction (HCI) systems pledge a more human–human-like
interaction between machines and humans. Their prowess in emanating an unambiguous …
interaction between machines and humans. Their prowess in emanating an unambiguous …
A clinical and technical methodological review on stress detection and sleep quality prediction in an academic environment
Background Mental health in recent times is a much talked about topic and its effects on the
sleep health of the students are said to result in long-term health issues if not identified and …
sleep health of the students are said to result in long-term health issues if not identified and …
Stress detection through wrist-based electrodermal activity monitoring and machine learning
Stress is an inevitable part of modern life. While stress can negatively impact a person's life
and health, positive and under-controlled stress can also enable people to generate creative …
and health, positive and under-controlled stress can also enable people to generate creative …
Multimodal hierarchical CNN feature fusion for stress detection
Stress is one of the most severe concerns in modern life. High-level stress can create
various diseases or loss of focus and productivity at work. Being under stress prevents …
various diseases or loss of focus and productivity at work. Being under stress prevents …
[HTML][HTML] Applying self-supervised representation learning for emotion recognition using physiological signals
The use of machine learning (ML) techniques in affective computing applications focuses on
improving the user experience in emotion recognition. The collection of input data (eg …
improving the user experience in emotion recognition. The collection of input data (eg …
A systematic review of intermediate fusion in multimodal deep learning for biomedical applications
Deep learning has revolutionized biomedical research by providing sophisticated methods
to handle complex, high-dimensional data. Multimodal deep learning (MDL) further …
to handle complex, high-dimensional data. Multimodal deep learning (MDL) further …
A multimodal intermediate fusion network with manifold learning for stress detection
Multimodal deep learning methods capture synergistic features from multiple modalities and
have the potential to improve accuracy for stress detection compared to unimodal methods …
have the potential to improve accuracy for stress detection compared to unimodal methods …
Mental stress classification based on a support vector machine and naive Bayes using electrocardiogram signals
M Kang, S Shin, G Zhang, J Jung, YT Kim - Sensors, 2021 - mdpi.com
Examining mental health is crucial for preventing mental illnesses such as depression. This
study presents a method for classifying electrocardiogram (ECG) data into four emotional …
study presents a method for classifying electrocardiogram (ECG) data into four emotional …
Joint modality features in frequency domain for stress detection
Rich feature extraction is essential to train a good machine learning (ML) framework. These
features are generally extracted separately from each modality. We hypothesize that richer …
features are generally extracted separately from each modality. We hypothesize that richer …
Disaster assessment from social media using multimodal deep learning
Real-time global event detection particularly catastrophic events has benefited significantly
due to the ubiquitous adoption of social media platforms and advancements in image …
due to the ubiquitous adoption of social media platforms and advancements in image …