Recently,as recognizing emotion has been one of the hallmarks of affective computing,more attention has been paid to physiological signals for emotion recognition.This paper presented an approach to emotion recognitio...Recently,as recognizing emotion has been one of the hallmarks of affective computing,more attention has been paid to physiological signals for emotion recognition.This paper presented an approach to emotion recognition using ElectroCardioGraphy(ECG) signals from multiple subjects.To collect reliable affective ECG data,we applied an arousal method by movie clips to make subjects experience specific emotions without external interference.Through precise location of P-QRS-T wave by continuous wavelet transform,an amount of ECG features was extracted sufficiently.Since feature selection is a combination optimization problem,Improved Binary Particle Swarm Optimization(IBPSO) based on neighborhood search was applied to search out effective features to improve classification results of emotion states with the help of fisher or K-Nearest Neighbor(KNN) classifier.In the experiment,it is shown that the approach is successful and the effective features got from ECG signals can express emotion states excellently.展开更多
Objectives:The purpose of this study was to describe relationships between negative emotions and perceived emotional support in parents of children admitted to the pediatric intensive care unit(PICU).Methods:This cros...Objectives:The purpose of this study was to describe relationships between negative emotions and perceived emotional support in parents of children admitted to the pediatric intensive care unit(PICU).Methods:This cross-sectional descriptive study conducted face-to-face interviews between January 2019 and January 2020.Study variables included depression(PHQ-9 Scale),anxiety(Emotional Distress-Anxiety-Short Form 8a),anger(Emotional Distress-Anger-Short Form 5a),fear(Fear-Affect Computerized Adaptive Test),somatic fear(Fear-Somatic Arousal-Fixed Form),loneliness(Revised 20-item UCLA Loneliness Scale),and perceived emotional support(Emotional Support-Fixed Form).Results:Eighty parents reported symptoms of depression 8.00(4.00,13.75),anxiety(23.43±7.80),anger(13.40±5.46),fear(72.81±27.26),somatic fear 9.00(6.00,12.75),loneliness(39.35±12.00),and low perceived emotional support(32.14±8.06).Parents who were young,single,low-income,and with limited-post secondary education reported greater loneliness and lower perceived emotional support.Fear correlated with depression(r=0.737,P<0.01)and anxiety(r=0.900,P<0.01).Inverse relationships were discovered between perceived emotional support and loneliness(r=-0.767,P<0.01),anger(r=-0.401,P<0.01),and depression(r=-0.334,P<0.01).Conclusions:The cluster of negative emotions identified will serve as potential targets for future interventions designed to enhance support for parents of critically ill children.展开更多
So far,a lot of scientific studies have been carried out on nonverbal signals,which are considered as extrinsic expression of human’s intrapsychic state.Among them,emotion detection aims to automatically determine a ...So far,a lot of scientific studies have been carried out on nonverbal signals,which are considered as extrinsic expression of human’s intrapsychic state.Among them,emotion detection aims to automatically determine a person’s affective state,with immense potentials in many areas from health care,psychological detection to human-computer interaction.Traditional emotion detection is based on expressions,or linguistic and acoustic features in speech.However,展开更多
基金Supported by the National Natural Science Foundation of China (No.60873143)the National Key Subject Foundation for Basic Psychology (No.NKSF07003)
文摘Recently,as recognizing emotion has been one of the hallmarks of affective computing,more attention has been paid to physiological signals for emotion recognition.This paper presented an approach to emotion recognition using ElectroCardioGraphy(ECG) signals from multiple subjects.To collect reliable affective ECG data,we applied an arousal method by movie clips to make subjects experience specific emotions without external interference.Through precise location of P-QRS-T wave by continuous wavelet transform,an amount of ECG features was extracted sufficiently.Since feature selection is a combination optimization problem,Improved Binary Particle Swarm Optimization(IBPSO) based on neighborhood search was applied to search out effective features to improve classification results of emotion states with the help of fisher or K-Nearest Neighbor(KNN) classifier.In the experiment,it is shown that the approach is successful and the effective features got from ECG signals can express emotion states excellently.
基金This work was supported by the West Virginia University School of Nursing Research Investment Fund.
文摘Objectives:The purpose of this study was to describe relationships between negative emotions and perceived emotional support in parents of children admitted to the pediatric intensive care unit(PICU).Methods:This cross-sectional descriptive study conducted face-to-face interviews between January 2019 and January 2020.Study variables included depression(PHQ-9 Scale),anxiety(Emotional Distress-Anxiety-Short Form 8a),anger(Emotional Distress-Anger-Short Form 5a),fear(Fear-Affect Computerized Adaptive Test),somatic fear(Fear-Somatic Arousal-Fixed Form),loneliness(Revised 20-item UCLA Loneliness Scale),and perceived emotional support(Emotional Support-Fixed Form).Results:Eighty parents reported symptoms of depression 8.00(4.00,13.75),anxiety(23.43±7.80),anger(13.40±5.46),fear(72.81±27.26),somatic fear 9.00(6.00,12.75),loneliness(39.35±12.00),and low perceived emotional support(32.14±8.06).Parents who were young,single,low-income,and with limited-post secondary education reported greater loneliness and lower perceived emotional support.Fear correlated with depression(r=0.737,P<0.01)and anxiety(r=0.900,P<0.01).Inverse relationships were discovered between perceived emotional support and loneliness(r=-0.767,P<0.01),anger(r=-0.401,P<0.01),and depression(r=-0.334,P<0.01).Conclusions:The cluster of negative emotions identified will serve as potential targets for future interventions designed to enhance support for parents of critically ill children.
文摘So far,a lot of scientific studies have been carried out on nonverbal signals,which are considered as extrinsic expression of human’s intrapsychic state.Among them,emotion detection aims to automatically determine a person’s affective state,with immense potentials in many areas from health care,psychological detection to human-computer interaction.Traditional emotion detection is based on expressions,or linguistic and acoustic features in speech.However,
