AIMC Topic: Facial Expression

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Learning Multiscale Active Facial Patches for Expression Analysis.

IEEE transactions on cybernetics
In this paper, we present a new idea to analyze facial expression by exploring some common and specific information among different expressions. Inspired by the observation that only a few facial parts are active in expression disclosure (e.g., aroun...

Machine Learning Methods to Track Dynamic Facial Function in Facial Palsy.

IEEE transactions on bio-medical engineering
OBJECTIVE: For patients with facial palsy, the wait for return of facial function and resulting vision risk from poor eye closure, difficulty speaking and eating from flaccid oral sphincter muscles, and psychological morbidity from the inability to s...

Multimodal depression recognition and analysis: Facial expression and body posture changes via emotional stimuli.

Journal of affective disorders
BACKGROUND: Clinical studies have shown that facial expressions and body posture in depressed patients differ significantly from those of healthy individuals. Combining relevant behavioral features with artificial intelligence technology can effectiv...

[Application of multi-scale spatiotemporal networks in physiological signal and facial action unit measurement].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Multi-task learning (MTL) has demonstrated significant advantages in the field of physiological signal measurement. This approach enhances the model's generalization ability by sharing parameters and features between similar tasks, even in data-scarc...

Learning Sequential Variation Information for Dynamic Facial Expression Recognition.

IEEE transactions on neural networks and learning systems
A multiscale sequence information fusion (MSSIF) method is presented for dynamic facial expression recognition (DFER) in video sequences. It exploits multiscale information by integrating features from individual frames, subsequences, and entire sequ...

Facial emotion based smartphone addiction detection and prevention using deep learning and video based learning.

Scientific reports
Smartphone addiction among students has emerged as a critical issue, negatively impacting their academic performance, emotional well-being, and social behavior. This paper introduces the Theory of Mind integrated with Video Modelling (TMVM) framework...

Facial expression deep learning algorithms in the detection of neurological disorders: a systematic review and meta-analysis.

Biomedical engineering online
BACKGROUND: Neurological disorders, ranging from common conditions like Alzheimer's disease that is a progressive neurodegenerative disorder and remains the most common cause of dementia worldwide to rare disorders such as Angelman syndrome, impose a...

Naturalistic acute pain states decoded from neural and facial dynamics.

Nature communications
Pain remains poorly understood in task-free contexts, limiting our understanding of its neurobehavioral basis in naturalistic settings. Here, we use a multimodal, data-driven approach with intracranial electroencephalography, pain self-reports, and f...

Neural dynamics of mental state attribution to social robot faces.

Social cognitive and affective neuroscience
The interplay of mind attribution and emotional responses is considered crucial in shaping human trust and acceptance of social robots. Understanding this interplay can help us create the right conditions for successful human-robot social interaction...

A psychologically interpretable artificial intelligence framework for the screening of loneliness, depression, and anxiety.

Applied psychology. Health and well-being
Negative emotions such as loneliness, depression, and anxiety (LDA) are prevalent and pose significant challenges to emotional well-being. Traditional methods of assessing LDA, reliant on questionnaires, often face limitations because of participants...