Emotion is a crucial physiological attribute in humans, and emotion recognition technology can significantly assist individuals in self-awareness. Addressing the challenge of significant differences in electroencephalogram (EEG) signals among different subjects, we introduce a novel mechanism in the traditional whale optimization algorithm (WOA) to expedite the optimization and convergence of the algorithm. Furthermore, the improved whale optimization algorithm (IWOA) was applied to search for the optimal training solution in the extreme learning machine (ELM) model, encompassing the best feature set, training parameters, and EEG channels. By testing 24 common EEG emotion features, we concluded that optimal EEG emotion features exhibited a certain level of specificity while also demonstrating some commonality among subjects. The proposed method achieved an average recognition accuracy of 92.19% in EEG emotion recognition, significantly reducing the manual tuning workload and offering higher accuracy with shorter training times compared to the control method. It outperformed existing methods, providing a superior performance and introducing a novel perspective for decoding EEG signals, thereby contributing to the field of emotion research from EEG signal.
There are two modes to display panoramic movies in virtual reality (VR) environment: non-stereoscopic mode (2D) and stereoscopic mode (3D). It has not been fully studied whether there are differences in the activation effect between these two continuous display modes on emotional arousal and what characteristics of the related neural activity are. In this paper, we designed a cognitive psychology experiment in order to compare the effects of VR-2D and VR-3D on emotional arousal by analyzing synchronously collected scalp electroencephalogram signals. We used support vector machine (SVM) to verify the neurophysiological differences between the two modes in VR environment. The results showed that compared with VR-2D films, VR-3D films evoked significantly higher electroencephalogram (EEG) power (mainly reflected in α and β activities). The significantly improved β wave power in VR-3D mode showed that 3D vision brought more intense cortical activity, which might lead to higher arousal. At the same time, the more intense α activity in the occipital region of the brain also suggested that VR-3D films might cause higher visual fatigue. By the means of neurocinematics, this paper demonstrates that EEG activity can well reflect the effects of different vision modes on the characteristics of the viewers’ neural activities. The current study provides theoretical support not only for the future exploration of the image language under the VR perspective, but for future VR film shooting methods and human emotion research.
ObjectiveTo systematically review the relationship between polycyclic aromatic hydrocarbons (PAHs) and emotion and behaviors in children and adolescents. MethodsThe PubMed, EBSCO, Web of Science, CBM, VIP, WanFang Data, OVFT, Proquest Psychological database and CNKI databases were electronically searched to collect studies on the relationship between PAHs and emotion and behaviors in children and adolescents from inception to October 20, 2022. Two reviewers independently screened the literature, extracted data and assessed the risk of bias of the included studies. A qualitative systematic review was then performed. ResultsA total of six cohort studies were included, five studies involving maternal exposure during pregnancy, found that maternal exposure to PAHs during pregnancy was associated with an increase in childhood anxiety/depression syndrome, attention problems, social withdrawal, social competence, social problems, orientation/regulation, withdrawal behaviors, and autism-related behaviors. Another study of exposure in school-age children found that PAHs exposure was associated with poorer attention performance in school. Results of other emotional behaviors were inconsistent, or no association was found. ConclusionCurrent evidence shows that PAHs have certain effects on emotional behaviors of children and adolescents. Due to the limited quality and quantity of the included studies, more high-quality cohort studies are required to verify above conclusion.
Emotion recognition refers to the process of determining and identifying an individual's current emotional state by analyzing various signals such as voice, facial expressions, and physiological indicators etc. Using electroencephalogram (EEG) signals and virtual reality (VR) technology for emotion recognition research helps to better understand human emotional changes, enabling applications in areas such as psychological therapy, education, and training to enhance people’s quality of life. However, there is a lack of comprehensive review literature summarizing the combined researches of EEG signals and VR environments for emotion recognition. Therefore, this paper summarizes and synthesizes relevant research from the past five years. Firstly, it introduces the relevant theories of VR and EEG signal emotion recognition. Secondly, it focuses on the analysis of emotion induction, feature extraction, and classification methods in emotion recognition using EEG signals within VR environments. The article concludes by summarizing the research’s application directions and providing an outlook on future development trends, aiming to serve as a reference for researchers in related fields.
ObjectiveTo explore the psychological process and needs of the second victims of medical adverse events after the occurrence of adverse events, so as to provide reference for the psychological intervention strategies of medical institutions for the second victims of medical adverse events.MethodsThe second victims of medical adverse events in the First People’s Hospital of Ziyang were selected from April to July 2019. Qualitative research method was used to conduct semi-structured in-depth interviews with the second victims. Colaizzi method was used to analyze the transcripts through reading and rereading, coding, and thematizing. ResultsA total of 22 second victims of medical adverse events were interviewed. The second victims of medical adverse events experienced negative emotional experience, and the desire to seek emotional support was urgent. The psychological process of the second victims of medical adverse events mainly involved five stages: fear, anxiety, depression, guilt and recovery. Emotional support hada positive effect on regression. Conversely, negative or lack of emotional support had a negative effect on regression. ConclusionsThe emotional experience of the second victims of medical adverse events is relatively staged, and the recovery and regression are greatly affected by internal and external factors. Hospital administrators should take active measures and establish an emotional support mechanism for adverse events in order to reduce psychosomatic injuries and improve medical quality and efficiency.
Objective To explore the association between behavioral, emotional problems and life events among adolescents, and to determine which factors of life events correlate most highly with the behavioral, emotional problems. Method A total of 1 325 adolescents were investigated with Youth Self-Report (YSR) of Achenbach’s behavior checklist and Adolescent Self-Rating Life Events Checklist (ASLEC), and the data were analyzed with canonical correlation analysis. Results Canonical correlation was statistically significant. The correlation coefficients of the first pair of canonical variables in the male and female group were 0.631 3 and 0.621 1, respectively, and the cumulative proportion of the first two pairs of canonical variables was above 0.95. In the first pair of canonical variables, the loadings of anxious/depressed, interpersonal sensitivity and study pressure were higher, while in the second pair, withdrawal and punishment were the most important factors. Conclusions The effects of life events on emotional problems mainly contributed to interpersonal sensitivity and study pressure.
ObjectivesTo systematically review the association between pubertal development progression and emotional and behavioral problems.MethodsVIP, CNKI, CBM, WanFang Data, PubMed, Web of Science and EBSCO databases were electronically searched to collect studies on the relationship between pubertal tempo or trajectory and emotional and behavioral problems from inception to December 31st, 2019. Two reviewers independently screened literature, extracted data and assessed risk of bias of included studies. Qualitative methods were then used to analyze the data.ResultsA total of 14 cohort studies were included. The results showed that depression was the most studied emotional problem, and 2 of the 3 studies found a significant association between faster pubertal tempo and more depressive symptoms in juvenile males. However, no association was found in 3 of the 4 studies on juvenile females. The content of behavioral problems of included studies was broad, including internalizing and externalizing problems, substance abuse, attention problem, self-control, first-sexual experience, delinquency, conduct disorder, peer relationship, etc. However, few studies on the same behaviors, and the relationship between behavioral problems was unclear.ConclusionsThe faster pubertal tempo may be associated with depression in juvenile males. The association between pubertal tempo and behavioral problems in males and females remain to be determined by more studies.
Objective To identify the prevalence and related factors of emotional disorder of inpatients in Department of Spinal Surgery . Methods A cross-sectional study was conducted from October 2015 to April 2016 to screen 300 patients undergoing spinal surgery. Huaxi Emotional-distress Index was used to assess the emotional status of the patients, and a self-designed general condition questionnaire was used to evaluate the demographic data. Results The prevalence of emotional disorder of patients in Department of Spinal Surgery was 14.3%. Anxiety was the main type of emotional disorder. Logistic regression analysis showed that the education level and pathogeny were the main factors of emotional disorder. Conclusions In Department of Spinal Surgery, the inpatients’ psychological status is poor, and anxiety is the main emotional disorder. Emotional disorder is related to education level and pathogeny. Timely psychological treatment should be used in order to comprehensively improve the level of recovery of the inpatients.
ObjectiveTo investigate the effect of positive family behavior support on emotional and behavioral problems in preschool children with epilepsy. Methods A total of 80 preschool epileptic children and their parents who were admitted to the Department of Neurology of our hospital from October 2022 to February 2023 were selected as the research objects, and were divided into experimental group and control group with 40 cases each by random number table method. The control group received neurology routine nursing, and the experimental group received positive family behavior support intervention based on the control group. The scores of family intimacy and adaptability scale, strengths and difficulties questionnaire, medication compliance and quality of life of epilepsy children were compared before and after intervention between the two groups. ResultsAfter intervention, the scores of strength and difficulty questionnaire in experimental group were lower than those in control group (P<0.05), and the scores of family intimacy and adaptability scale, quality of life and medication compliance in experimental group were higher than those in control group (all P<0.05). ConclusionThe application of positive family behavior support program can reduce the occurrence of emotional behavior problems, improve family closeness and adaptability, improve medication compliance, and improve the quality of life of preschool children with epilepsy.
Emotion classification and recognition is a crucial area in emotional computing. Physiological signals, such as electroencephalogram (EEG), provide an accurate reflection of emotions and are difficult to disguise. However, emotion recognition still faces challenges in single-modal signal feature extraction and multi-modal signal integration. This study collected EEG, electromyogram (EMG), and electrodermal activity (EDA) signals from participants under three emotional states: happiness, sadness, and fear. A feature-weighted fusion method was applied for integrating the signals, and both support vector machine (SVM) and extreme learning machine (ELM) were used for classification. The results showed that the classification accuracy was highest when the fusion weights were set to EEG 0.7, EMG 0.15, and EDA 0.15, achieving accuracy rates of 80.19% and 82.48% for SVM and ELM, respectively. These rates represented an improvement of 5.81% and 2.95% compared to using EEG alone. This study offers methodological support for emotion classification and recognition using multi-modal physiological signals.