Emotion Recognition In Children Research Articles

Interparental conflict dimensions and children's psychological problems: Emotion recognition as a mediator.

This study tested children's emotion recognition as a mediator of associations between their exposure to hostile and cooperative interparental conflict and their internalizing and externalizing symptoms. From 2018 to 2022, 238 mothers, their partners, and preschool children (Mage = 4.38, 52% female; 68% White; 18% Black; 14% Multiracial or another race; and 16% Latinx) participated in three annual measurement occasions. Path analyses indicated that Wave 1 observations of hostile interparental conflict predicted residualized increases in children's emotion recognition accuracy (i.e., angry, sad, and happy) at Wave 2 (β = .27). Wave 2 emotion recognition, in turn, predicted residualized decreases in children's internalizing symptoms at Wave 3 (β = -.22). Mediational findings were partly attributable to children's accuracy in identifying angry and high-intensity expressions.

Assessing Complex Emotion Recognition in Children. A Preliminary Study of the CAM-C: Argentine Version

Assessing Complex Emotion Recognition in Children. A Preliminary Study of the CAM-C: Argentine Version

Emotion Recognition in Children and Adolescents with ASD and ADHD: a Systematic Review

AbstractChildren and adolescents with autism spectrum disorder (ASD) and attention deficit and hyperactivity disorder (ADHD) show difficulties in recognizing emotions. Similarities and differences between these two clinical groups’ emotion recognition (ER) have been little explored. This systematic review aims to summarize the results of comparative studies that included samples of cases with ASD and ADHD. A systematic search was conducted following PRISMA guidelines, and 24 papers were included. Behavioral, brain-based, and eye-tracking studies were considered, paying particular attention to the different methods used and to the characteristics of the study groups, such as cognitive factors, age-related differences, and comorbidities. This review provides some insight on the complex process of ER in ASD and ADHD, highlighting important directions for future research.

3.42 Impairment of Facial Emotion Recognition in Children With High Levels of Irritability

3.42 Impairment of Facial Emotion Recognition in Children With High Levels of Irritability

Characteristics of Facial Emotion Recognition in Children Aged 7-8 with High-Functioning ASD Using an Eye-Tracker

Objectives: The purpose of the present study was to investigate characteristics of peer’s facial emotion recognition (FER) in children with high-functioning autism spectrum disorder (HF-ASD) through gaze patterns; and to suggest implications through comparison with typically developing (TD children). Methods: The participants were 10 children with HF-ASD aged 7-8 years and 10 children with TD matched on chronological age. Children performed FER tasks consisting of two types of stimuli (static, dynamic) for four basic emotions (happy, sad, anger, surprise) and their eye movement were measured while they performed the task using an eye-tracker. The emotion recognition accuracy, proportion of fixation, and heatmap were analyzed, and correlation analysis was conducted. Results: The HF-ASD group performed significantly poorer than the TD group in overall emotion recognition and made significantly more errors only in anger. There was no statistically significant difference in emotion recognition between static and dynamic stimuli in both groups. There was no interaction effect between group and emotion type and areas of interest (AOI). Only the interaction effect between emotion type and AOI was significant in the TD group. The HF-ASD group tended to look more at the mouth than the eyes and look relatively more at non-feature area of the faces compared to the TD group. These gaze patterns seem to affect the accuracy depending on emotion types. Conclusion: Children with HF-ASD have deficits in FER and show gaze patterns different with TD peers. The results of this study suggest that a deficit in FER of children with HF-ASD is related to gaze pattern.

Effects of wearing an opaque or transparent face mask on the perception of facial expressions: A comparative study between Japanese school-aged children and adults.

The negative side effects of mask-wearing on reading facial emotional cues have been investigated in several studies with adults post-2020. However, little is known about children. This study aimed to determine the negative influence of mask-wearing on reading emotions of adult faces by Japanese school-aged children, compared to Japanese adults. We also examined whether this negative influence could be alleviated by using a transparent face mask instead of an opaque one (surgical mask). The performance on reading emotions was measured using emotion categorization and emotion intensity rating tasks for adult faces. As per the findings, the accuracy of emotion recognition in children was impaired for various facial expressions (disgust, fear, happy, neutral, sad, and surprise faces), except for angry faces. Conversely, in adults, it was impaired for a few facial expressions. The perceived intensity for happy faces with a surgical mask was weaker in both children and adults than in those without the mask. A negative influence of wearing surgical masks was generally not observed for faces wearing a transparent mask in both children and adults. Thus, negative side effects of mask-wearing on reading emotions are observed for more facial expressions in children than in adults; transparent masks can help remedy these.

Enhancing Social Interaction: FER assistance for ASD Children's Emotion Recognition

Autism spectrum disorder (ASD) is a neurological condition that has an impact on the development of the brain, resulting in difficulties with social interaction, restrictive or repetitive behaviors and has been a concern due to its increasing prevalence. Facial expressions are a crucial aspect of human communication, as they are more impactful than words particularly in face-to-face interactions. Absence of facial expressions is a common symptom in people generally suffering from ASD. Teaching emotional detection at an early stage, specifically during childhood, is essential for improving one's ability to detect emotions.Assistive technology stands out as a crucial innovation in enhancing the quality of life for individuals with autism. This research demonstrates the application and utilization of a fundamental structure of Convolutional Neural Network to educate children diagnosed with ASD to recognize human emotions. The method utilizes a convolutional neural network (CNN) to classify fundamental facial emotions: anger, fear, happy, neutral, sadness, and surprise and assist children diagnosed with ASD in learning to identify human emotions.

The Impact of Working Memory on the Development of Social Play in Japanese Preschool Children: Emotion Knowledge as a Mediator

Through enriched play, children learn social-emotional skills necessary for academic achievement and interpersonal relationships with others. Further research is needed on how specific factors associated with social play, such as working memory and emotion knowledge, interact to promote it. Previous studies have examined the association of working memory and emotion knowledge with social play. However, there are no consistent results as to which abilities influence which skills first. Thus, the present study examines the impact of working memory on the development of social play and the role of emotion knowledge in the relationship between working memory and social play. Forty-seven Japanese preschoolers were tested on working memory, social play, and emotion knowledge. Regression analysis indicated that working memory was significantly related to social play. Furthermore, mediation analysis indicated that emotion recognition mediates the effects of working memory on social play. Working memory was found to contribute to social play by improving emotion recognition in children. These results indicate that the pathway from working memory to social play is mediated by emotion recognition and expands previous perspectives on the developmental mechanisms of emotion knowledge in children.

Educational Facial Emotion Recognition in Children With Autism Spectrum Disorder: A Clinical Trial Study

Objectives: The disability to recognize facial emotions is one of the behavioral problems in autistic children. This study was designed to evaluate the effect of education on the promotion of face recognition. Methods: This single-blind clinical trial study was conducted on children with autism. The participants were allocated with random sampling to the two groups. Autistic children in the intervention group were educated in 10 sessions with 40 facial emotions images, each session lasted 20 min. Autistic children in the control group underwent routine teaching. The assistant researcher completed the Benton questionnaire for each child before and after the study. The obtained data were analyzed with SPSS software, version 22. Results: This study showed that education on facial emotions has good effects on the recognition of facial expressions by children with autism. In addition, a significant difference is identified between the two study groups in identifying facial emotions (P<0.001). Discussion: Education to children with autism improved facial emotion identification. Therefore, according to the increase in children with autism all over the world such as in Iran, it seems that caregivers and health managers should review and use our study results for providing a supportive environment to promote recognition emotional states of the face and ultimately to improve the child’s treatment.

Do different robot appearances change emotion recognition in children with ASD?

Socially Assistive Robotics has emerged as a potential tool for rehabilitating cognitive and developmental disorders in children with autism. Social robots found in the literature are often able to teach critical social skills, such as emotion recognition and physical interaction. Even though there are promising results in clinical studies, there is a lack of guidelines on selecting the appropriate robot and how to design and implement the child-robot interaction. This work aims to evaluate the impacts of a social robot designed with three different appearances according to the results of a participatory design (PD) process with the community. A validation study in the emotion recognition task was carried out with 21 children with autism. Spectrum disorder results showed that robot-like appearances reached a higher percentage of children's attention and that participants performed better when recognizing simple emotions, such as happiness and sadness. This study offers empirical support for continuing research on using SAR to promote social interaction with children with ASD. Further long-term research will help to identify the differences between high and low-functioning children.

Basic emotion recognition of children on the autism spectrum is enhanced in music and typical for faces and voices.

In contrast with findings of reduced facial and vocal emotional recognition (ER) accuracy, children on the autism spectrum (AS) demonstrate comparable ER skills to those of typically-developing (TD) children using music. To understand the specificity of purported ER differences, the goal of this study was to examine ER from music compared with faces and voices among children on the AS and TD children. Twenty-five children on the AS and 23 TD children (6-13 years) completed an ER task, using categorical (happy, sad, fear) and dimensional (valence, arousal) ratings, of emotions presented via music, faces, or voices. Compared to the TD group, the AS group showed a relative ER strength from music, and comparable performance from faces and voices. Although both groups demonstrated greater vocal ER accuracy, the children on the AS performed equally well with music and faces, whereas the TD children performed better with faces than with music. Both groups performed comparably with dimensional ratings, except for greater variability by the children on the AS in valence ratings for happy emotions. These findings highlight a need to re-examine ER of children on the AS, and to consider how facilitating strengths-based approaches can re-shape our thinking about and support for persons on the AS.

Emotion Recognition Skill in Specific Learning Disorder and Attention-Deficit Hyperactivity Disorder.

Social difficulties can affect both academic and relational-social functioning in common neurodevelopmental disorders such as attention-deficit hyperactivity disorder and specific learning disorder. It is known that social cognitive skills directly affect social functioning. The aim in this study is to examine the social cognitive skill of facial emotion recognition in children with attention-deficit hyperactivity disorder and specific learning disorder and to investigate whether literacy learning is related to emotion recognition. In the study, we compared the emotion recognition skill of 41 children with attention-deficit hyperactivity disorder, 50 with specific learning disorder, and 43 typically developed children using the Reading Mind in the Eyes Test. In addition, we evaluated the relationship between children's emotion recognition ability and literacy learning time. Attention-deficit hyperactivity disorder and specific learning disorder groups did not show a statistically significant difference in terms of Reading Mind in the Eyes Test scores, but both groups had lower scores than their typically eveloped peers (P < .001). In addition, we found that low Reading Mind in the Eyes Test scores were associated with late learning in reading and writing (P < .001, r = -.033). This study found that the specific learning disorder and attention-deficit hyperactivity disorder groups showed similar but poorer impact recognition skills than their typically developed peers. In addition, we showed that literacy learning speed is related to emotion recognition.

1.14 Gender and Conduct Problem Severity Are Associated With Physiological Arousal and Emotion Recognition in Children Exposed to Peer Distress Cues

1.14 Gender and Conduct Problem Severity Are Associated With Physiological Arousal and Emotion Recognition in Children Exposed to Peer Distress Cues

Facial emotion recognition in children and youth with attention-deficit/hyperactivity disorder and irritability.

The ability to recognize emotions evident in people's faces contributes to social functioning and might be affected by ADHD and irritability. Given their high co-occurrence, we examined the relative contribution of ADHD and irritability to facial emotion recognition (FER). We hypothesized that irritability but not ADHD traits would predict increased likelihood of misrecognizing emotions as negative, and that FER performance would explain the association of ADHD and irritability traits with social skills. FER was measured using the Reading the Mind in the Eyes Test (RMET) in children (6-14years old) referred for ADHD assessment (n = 304) and healthy controls (n = 128). ADHD, irritability and social skills were measured using parent ratings. We used repeated measure logistics regression, comparing the effects across emotion valence of images (i.e., neutral/positive/negative). High irritability but not ADHD diagnosis predicted lower RMET accuracy. ADHD traits predicted lower RMET accuracy in younger but not older participants, whereas irritability predicted poorer accuracy at all ages. ADHD traits predicted lower RMET accuracy across all emotion valences, whereas irritability predicted increased probability of misrecognizing neutral and positive but not negative emotions. Irritability did not increase the probability for erroneously recognizing emotions as negative. ADHD and irritability traits fully explained the association between RMET and social skills. ADHD and irritability traits might impact the ability to identify emotions portrayed in faces. However, irritability traits appear to selectively impair recognition of neutral and positive but not negative emotions. ADHD and irritability are important when examining the link between FER and social difficulties.

The COVID-19 pandemic, mask-wearing, and emotion recognition during late-childhood.

Face masks are an effective and important tool to prevent the spread of COVID‐19, including among children. However, occluding parts of the face can impact emotion recognition, which is fundamental to effective social interactions. Social distancing, stress, and changes to routines because of the pandemic have also altered the social landscape of children, with implications for social development. To better understand how social input and context impact emotion recognition, the current study investigated emotion recognition in children (7–12 years old, N = 131) using images of both masked and unmasked emotional faces. We also assessed a subsample of participants (“pre‐pandemic subsample,” n = 35) who had completed the same emotion recognition task with unmasked faces before and during the pandemic. Masking of faces was related to worse emotion recognition, with more pronounced effects for happy, sad, and fearful faces than angry and neutral faces. Masking was more strongly related to emotion recognition among children whose families reported greater social disruption in response to the pandemic. Finally, in the pre‐pandemic subsample, emotion recognition of sad faces was lower during versus before the pandemic relative to other emotions. Together, findings show that occluding face parts and the broader social context (i.e., global pandemic) both impact emotion‐relevant judgments in school‐aged children.

Early Neuro-Psychomotor Therapy Intervention for Theory of Mind and Emotion Recognition in Neurodevelopmental Disorders: A Pilot Study.

The aim of the present study is to explore the effect of early neuro-psychomotor therapy to improve theory of mind skills and emotion recognition in children with neurodevelopmental disorders. A pilot study was set up, consisting of in-group training activities based on the neuro-psychomotor approach. Children were evaluated using Neuropsychological Assessment for Child (Nepsy-II), Test of Emotion Comprehension (TEC), and Social Communication Questionnaire (SCQ). For data analysis, one-sample Wilcoxon signed rank test was used with a significance of p < 0.05. Two children with a developmental language disorder and four children with autism spectrum disorders participated in a 3-month training program. Our findings revealed significant improvement in emotion recognition, as measured with Nepsy-II (p = 0.04), while no statistical improvement was found for theory of mind. Despite the limited sample, early neuro-psychomotor therapy improves emotion recognition skills in children with neurodevelopmental disorders. However, considering the explorative nature of the study, findings should be interpreted with caution.

Effects of a Video-Based Intervention on Emotion Recognition for Children With Autism Who Have Limited Speech in China

Children with autism spectrum disorder (ASD) have difficulties with emotion recognition and a number of interventions have been designed to address this problem. The purpose of this study was to examine the effects of video-based intervention (The Transporters) on emotion recognition in four children (aged 4–8 years old) with ASD who have limited speech in China. This study employed a multiple baseline across participants. The results indicated that the video-based intervention effectively improved emotion recognition in all children with limited speech. However, there was a limited effect in the generalization phase after 7 and 15 days completing the intervention phase. Results of this study have important implications for early intervention educators working with children with ASD.

Improved Digital Therapy for Developmental Pediatrics Using Domain-Specific Artificial Intelligence: Machine Learning Study.

BackgroundAutomated emotion classification could aid those who struggle to recognize emotions, including children with developmental behavioral conditions such as autism. However, most computer vision emotion recognition models are trained on adult emotion and therefore underperform when applied to child faces.ObjectiveWe designed a strategy to gamify the collection and labeling of child emotion–enriched images to boost the performance of automatic child emotion recognition models to a level closer to what will be needed for digital health care approaches.MethodsWe leveraged our prototype therapeutic smartphone game, GuessWhat, which was designed in large part for children with developmental and behavioral conditions, to gamify the secure collection of video data of children expressing a variety of emotions prompted by the game. Independently, we created a secure web interface to gamify the human labeling effort, called HollywoodSquares, tailored for use by any qualified labeler. We gathered and labeled 2155 videos, 39,968 emotion frames, and 106,001 labels on all images. With this drastically expanded pediatric emotion–centric database (>30 times larger than existing public pediatric emotion data sets), we trained a convolutional neural network (CNN) computer vision classifier of happy, sad, surprised, fearful, angry, disgust, and neutral expressions evoked by children.ResultsThe classifier achieved a 66.9% balanced accuracy and 67.4% F1-score on the entirety of the Child Affective Facial Expression (CAFE) as well as a 79.1% balanced accuracy and 78% F1-score on CAFE Subset A, a subset containing at least 60% human agreement on emotions labels. This performance is at least 10% higher than all previously developed classifiers evaluated against CAFE, the best of which reached a 56% balanced accuracy even when combining “anger” and “disgust” into a single class.ConclusionsThis work validates that mobile games designed for pediatric therapies can generate high volumes of domain-relevant data sets to train state-of-the-art classifiers to perform tasks helpful to precision health efforts.

Vocal emotion recognition by native Turkish children with normal hearing and with hearing aids

Development of vocal emotion recognition in children with normal hearing takes many years before reaching adult-like levels. In children with hearing loss, decreased audibility and potential loss of sensitivity to relevant acoustic cues may additionally affect vocal emotion perception. Hearing aids (HAs) are traditionally optimized for speech understanding, and it is not clear how children with HAs are performing in perceiving vocal emotions. In this study, we investigated vocal emotion recognition in native Turkish normal hearing children (NHC, age range: 5–18 years), normal hearing adults (NHA, age range: 18–45 years), and children with HAs (HAC, age range: 5–18 years), using pseudo-speech sentences expressed in one of the three emotions, happy, sad, or angry (Geneva Multimodal Emotion Portrayal (GEMEP) Corpus by Banziger and Scherer, 2010; EmoHI Test by Nagels et al., 2021). Visual inspection of the preliminary data suggests that performance increases with increasing age for NHC and that in general, HAC have lower recognition scores compared to NHC. Further analyses will be presented, along with acoustical analysis of the stimuli and an exploration of effects of HA settings. In addition, for cross-language comparison, these data will be compared to previously collected data with the same paradigm in children from the UK and the Netherlands.

Automatic Emotion Recognition in Children with Autism: A Systematic Literature Review.

The automatic emotion recognition domain brings new methods and technologies that might be used to enhance therapy of children with autism. The paper aims at the exploration of methods and tools used to recognize emotions in children. It presents a literature review study that was performed using a systematic approach and PRISMA methodology for reporting quantitative and qualitative results. Diverse observation channels and modalities are used in the analyzed studies, including facial expressions, prosody of speech, and physiological signals. Regarding representation models, the basic emotions are the most frequently recognized, especially happiness, fear, and sadness. Both single-channel and multichannel approaches are applied, with a preference for the first one. For multimodal recognition, early fusion was the most frequently applied. SVM and neural networks were the most popular for building classifiers. Qualitative analysis revealed important clues on participant group construction and the most common combinations of modalities and methods. All channels are reported to be prone to some disturbance, and as a result, information on a specific symptoms of emotions might be temporarily or permanently unavailable. The challenges of proper stimuli, labelling methods, and the creation of open datasets were also identified.