AIMC Topic: Facial Expression

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Performance Evaluation of a Supervised Machine Learning Pain Classification Model Developed by Neonatal Nurses.

Advances in neonatal care : official journal of the National Association of Neonatal Nurses
BACKGROUND: Early-life pain is associated with adverse neurodevelopmental consequences; and current pain assessment practices are discontinuous, inconsistent, and highly dependent on nurses' availability. Furthermore, facial expressions in commonly u...

Detecting emotions through EEG signals based on modified convolutional fuzzy neural network.

Scientific reports
Emotion is a human sense that can influence an individual's life quality in both positive and negative ways. The ability to distinguish different types of emotion can lead researchers to estimate the current situation of patients or the probability o...

Auto Diagnosis of Parkinson's Disease Via a Deep Learning Model Based on Mixed Emotional Facial Expressions.

IEEE journal of biomedical and health informatics
Parkinson's disease (PD) is a common degenerative disease of the nervous system in the elderly. The early diagnosis of PD is very important for potential patients to receive prompt treatment and avoid the aggravation of the disease. Recent studies ha...

Sensing technologies and machine learning methods for emotion recognition in autism: Systematic review.

International journal of medical informatics
BACKGROUND: Human Emotion Recognition (HER) has been a popular field of study in the past years. Despite the great progresses made so far, relatively little attention has been paid to the use of HER in autism. People with autism are known to face pro...

Emotion Classification Based on Pulsatile Images Extracted from Short Facial Videos via Deep Learning.

Sensors (Basel, Switzerland)
Most human emotion recognition methods largely depend on classifying stereotypical facial expressions that represent emotions. However, such facial expressions do not necessarily correspond to actual emotional states and may correspond to communicati...

A multi-featured expression recognition model incorporating attention mechanism and object detection structure for psychological problem diagnosis.

Physiology & behavior
Expression is the main method for judging the emotional state and psychological condition of the human body, and the prediction of changes in facial expressions can effectively determine the mental health of a person, thus avoiding serious psychologi...

An accurately supervised motion-aware deep network for non-contact pain assessment of trigeminal neuralgia mouse model.

Journal of oral & facial pain and headache
Pain assessment in trigeminal neuralgia (TN) mouse models is essential for exploring its pathophysiology and developing effective analgesics. However, pain assessment methods for TN mouse models have not been widely studied, resulting in a critical g...

Deep Learning for Face Detection and Pain Assessment in Japanese macaques ().

Journal of the American Association for Laboratory Animal Science : JAALAS
Facial expressions have increasingly been used to assess emotional states in mammals. The recognition of pain in research animals is essential for their well-being and leads to more reliable research outcomes. Automating this process could contribute...

Hierarchical Context-Based Emotion Recognition With Scene Graphs.

IEEE transactions on neural networks and learning systems
For a better intention inference, we often try to figure out the emotional states of other people in social communications. Many studies on affective computing have been carried out to infer emotions through perceiving human states, i.e., facial expr...

PASTFNet: a paralleled attention spatio-temporal fusion network for micro-expression recognition.

Medical & biological engineering & computing
Micro-expressions (MEs) play such an important role in predicting a person's genuine emotions, as to make micro-expression recognition such an important resea rch focus in recent years. Most recent researchers have made efforts to recognize MEs with ...