Recognition of a human's continuous emotional states in real time plays an important role machine intelligence and human-machine interaction. Existing real-time emotion recognition systems use stimuli with low ecological validity (e.g., picture, sound) to elicit emotions recognise only valence arousal. To overcome these limitations, this paper, we construct standardised database 16 film clips that were selected from over one thousand excerpts. Based on categories are induced by clips,...

Most previous EEG-based emotion recognition methods studied hand-crafted EEG features extracted from different electrodes. In this article, we study the relation among electrodes and propose a deep learning method to automatically extract spatial that characterize functional between signals at Our proposed model is called <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">AT</b> tention-based xmlns:xlink="http://www.w3.org/1999/xlink">LSTM</b>...

A traditional model of emotion cannot explain the differences in brain activities between two discrete emotions that are similar valence-arousal coordinate space. The current study elicited positive (amusement and tenderness) negative (anger fear) both valence arousal dimensions to examine these emotional states. Frontal electroencephalographic (EEG) asymmetry midline power three bands (theta, alpha beta) were measured when participants watched affective film excerpts. Significant detected...

The stable relationship between personality and EEG ensures the feasibility of inference from brain activities. In this paper, we recognize an individual's traits by analyzing waves when he or she watches emotional materials. Thirty-seven participants took part in study watched 7 standardized film clips that characterize real-life experiences target seven discrete emotions. Features extracted signals subjective ratings enter SVM classifier as inputs to predict five dimensions traits. Our...

Emotion recognition from EEG signals has attracted much attention in affective computing. Recently, a novel dynamic graph convolutional neural network (DGCNN) model was proposed, which simultaneously optimized the parameters and weighted <inline-formula><tex-math notation="LaTeX">$G$</tex-math></inline-formula> characterizing strength of functional relation between each pair two electrodes recording equipment. In this article, we propose sparse DGCNN modifies by imposing sparseness...

Quantitative estimation of a driver's vigilance level has great value for improving driving safety and preventing accidents. Previous studies have identified correlations between electroencephalogram (EEG) spectrum power mental states such as alertness. Studies also built classification models that can estimate state changes based on data collected from drivers. In the present study, we propose system to detect using not only EEG signals but contexts inputs. We combined support vector...

Mental fatigue is one of the main reasons for decline response inhibition. This study aimed to explore impairing influence mental on a driver's The effects inhibition were assessed by comparing brain activity and behavioral indices when performing Go/NoGo task before after 90-min manipulation task. Participants in driving group performed simulated task, while individuals control spent same time watching movies. We found that participants reported higher levels had percentage eye closure...

Human activity recognition (HAR) technology based on wearables has received increasing attention in recent years. The traditional methods have used hand-crafted features to recognize human activities, resulting shallow feature extraction. With the development of deep learning, an number researchers focused studying learning methods. To achieve higher accuracy, majority current HAR research involves multisource and multimodal sensors (MMSs) data. However, due limitations receptive fields...

Abstract Emotions are processed asymmetrically by the human brain. Frontal alpha asymmetry (FAA) as measured electroencephalographic (EEG) power in band (8–13 Hz), is a sensitive indicator of asymmetric brain activity frontal cortex. The current study aimed to analyze EEG asymmetries terms valence and motivational direction. We presented 37 participants with three film excerpts that were selected from standard emotional database elicit target emotions: tenderness, anger, neutrality....

The ability to detect anomalies in perceived stimuli is critical a broad range of practical and applied activities involving human operators. In this paper, we propose real-time physiological-based system assess the cross-task mental workload during anomaly detection. Forty participants were recruited anomalous images from set different distracting (Task I) abnormal surveillance videos II). Task I, task difficulty levels manipulated by changing number anomalies/distracting (15, 21, 28, or...

Film clips are widely used in emotion research due to their relatively high ecological validity. Although researchers have established various film clip sets for different cultures, the few that exist related Chinese culture do not adequately address positive emotions. The main purposes of present study were establish a standardised database emotional could elicit more categories reported emotions compared existing databases and expand available can be as neutral materials. Two experiments...

The quantitative prediction and understanding of a driver's speed control is an essential component in preventing speeding designing vehicle systems. Driver complex behavior longitudinal consisting perception, decision making, motor control, dynamics modeling, individual driver differences. However, there are few existing models that can integrate all these aspects cohesive manner. To address this problem, paper introduces mathematical model for with analytical solutions based on human...

The robust generalization of deep learning models in the presence inherent noise remains a significant challenge, especially when labels are ambiguous due to their subjective nature and is indiscernible natural settings. In this article, we address specific important scenario monitoring suicidal ideation (SI), where time-series data, such as galvanic skin response (GSR) photoplethysmography (PPG), susceptible noise. Current methods predominantly focus on image text data or artificially...

Abstract This study presents a CFRP repair technology by laying up the uncured T800 prepreg as patch followed curing in microwave field. The effect of single‐ and double‐sided patches on comprehensive properties repaired panel were studied detail. Dielectric property tests reveal that exhibits higher dielectric constant than matrix material. sample with 10 layers total achieves highest heating rate 4.03 °C/min field when power was set at 800 W. FTIR analysis confirms degree cured...

Objective: Drinking and driving is a primary cause of traffic fatalities it has been suggested that binge drinkers comprise major portion those drivers involved in drinking accidents. Although several experimental studies have investigated the behavior (particularly college students and/or young adults) under influence alcohol, few focused on comparison sober general population between non-binge with consideration drivers' income levels. In addition, these not taken other potentially...