ObjectiveTo explore and clarify the relationship between epileptic seizure and inducing factors. Avoid inducing factors and reduce epileptic seizure, so as to improve the quality of life in patients with epilepsy.MethodsClinical data of 604 patients diagnosed with epilepsy in Xijing Hospital of Air Force Military Medical University from January 2018 to January 2019 were collected. The clinical data of patients with epilepsy were followed up 6 months.ResultsAmong the 604 patients, 318 (52.6%) were seizure-free in the last 6 months, 286 (47.4%) had seizures. 169 (59.1%) had seizures with at least one inducing factor. Common inducing factors: 123 cases of sleep disorder (72.8%), 114 cases of emotion changes (67.5%), 87 cases of irregular medication (51.5%), 97 cases of diet related (57.4%), 33 cases of menstruation and pregnancy (19.5%), etc. Using the χ2 test, seizures with age, gender differences had no statistical significance (P > 0.05), but seizure type was statistically different between inducing factors. In generalized seizures, tonic-clonic seizures associated with sleep deprivation (χ2= 0.189), absence seizures and anger (χ2= 0.237), pressure (χ2= 0.203), irregular life (χ2= 0.214). In the focal seizures, focal motor seizures was correlated with coffee consumption (χ2=0.145), focal sensory seizures with cold (χ2=0.235), electronic equipment use (χ2 =0.153), satiety (χ2 =0.257). Complex partial seizures was correlated with anger (χ2 =0.229), stress (χ2 =0.187), and cold (χ2 =0.198). The secondarily generalized seizures was correlated with drug missing (χ2 =0.231), sleep deprivation (χ2 =0.158), stress (χ2 =0.161), cold (χ2 =0.263), satiety (χ2 =0.182). Among the inducing factors, sleep deprivation was correlated with anger (χ2 =0.167), fatigue (χ2 =0.283), and stress (χ2 =0.230).ConclusionsEpileptic seizure were usually induced by a variety of factors. Generalized seizures were associated with sleep disorders, emotional changes, stress, irregular life, etc. While focal seizures were associated with stress, emotional changes, sleep disorders, cold, satiety, etc. An analysis of the triggers found that sleep deprivation was associated with anger, fatigue, and stress. Therefore, to clarify the inducing factors of epileptic seizure, avoid the inducing factors as much as possible, reduce the harm caused by seizures, and improve the quality of life of patients.
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.
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.
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.
ObjectiveTo identify the effects of transition to siblinghood (TTS) on the firstborn children’s emotions and behaviors, and to define the time of TTS.MethodsCBM, VIP, CNKI, WanFang Data, PubMed, Web of Science and EBSCO were electronically searched to collect studies on the emotional and behavioral characteristics of firstborn children in TTS from inception to December 31st, 2019. Two reviewers independently screened literature, extracted data and assessed the risk bias of included studies. Then, qualitative methods were used to analyze the studies.ResultsA total of 13 studies involving 980 children were included. 12 behavioral related studies explored self-behavior of the firstborn children during TTS, 3 studies focused on the interaction behavior between the firstborn children and their parents, the firstborn children and the second children. The systematic reviews found that TTS showed both positive and negative effects on the behavioral characteristics of firstborn children, primarily the negative effects. Firstborn children’s anxiety, confrontation and attachment showed 3 different patterns over time, respectively. Two studies showed the increase of negative emotions of firstborn children during TTS. The time range of TTS was mainly concentrated in the third trimester to 12 months after the birth of the second child.ConclusionsThe current evidence shows that TTS primarily increases the negative emotions and behaviors of firstborn children, and the behaviors of firstborn children changes over time. Due to limited quality and quantity of the included studies, more high quality studies are required to verify above conclusions.
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.
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.
Existing emotion recognition research is typically limited to static laboratory settings and has not fully handle the changes in emotional states in dynamic scenarios. To address this problem, this paper proposes a method for dynamic continuous emotion recognition based on electroencephalography (EEG) and eye movement signals. Firstly, an experimental paradigm was designed to cover six dynamic emotion transition scenarios including happy to calm, calm to happy, sad to calm, calm to sad, nervous to calm, and calm to nervous. EEG and eye movement data were collected simultaneously from 20 subjects to fill the gap in current multimodal dynamic continuous emotion datasets. In the valence-arousal two-dimensional space, emotion ratings for stimulus videos were performed every five seconds on a scale of 1 to 9, and dynamic continuous emotion labels were normalized. Subsequently, frequency band features were extracted from the preprocessed EEG and eye movement data. A cascade feature fusion approach was used to effectively combine EEG and eye movement features, generating an information-rich multimodal feature vector. This feature vector was input into four regression models including support vector regression with radial basis function kernel, decision tree, random forest, and K-nearest neighbors, to develop the dynamic continuous emotion recognition model. The results showed that the proposed method achieved the lowest mean square error for valence and arousal across the six dynamic continuous emotions. This approach can accurately recognize various emotion transitions in dynamic situations, offering higher accuracy and robustness compared to using either EEG or eye movement signals alone, making it well-suited for practical applications.
ObjectiveTo explore the influence factors of therapeutic compliance and emotional expression of first-degree relatives in acute schizophrenic patients with psychotic symptoms. MethodsThe Brief Psychiatric Rating Scale (BPRS) was used to measure the severity of psychotic symptoms in sixty schizophrenic patients from June to September 2014 in West China Hospital and the Toronto Alexithymia Scale (TAS) was used to survey the emotional expression in their family members. The homemade treatment adherence scale was used to survey the treatment adherence in patients for one week. ResultsThere was a poor therapeutic compliance in nineteen patients with acute schizophrenia (32%) and the other 41(68%) had good therapeutic compliance; the relatives of schizophrenic patients had high TAS scores (male: 67.61±10.03; female: 69.68±11.46) than the normal models did (P ＜ 0.05) . The differences between the patients with different therapeutic compliance in BPRS total score, reactivator, hostile and suspicion factor (P ＜ 0.05) . The therapeutic compliance was related to the severity of the psychotic symptoms (P ＜ 0.05) . Conclusions There is a bad emotional expression in the relatives of acute schizophrenic patients. The psychotic symptoms can influence the therapeutic compliance. The milder the psychotic symptoms, the better the therapeutic dependence.