Avatar-Based Picture Exchange Communication System Enhancing Joint Attention Training for Children With Autism.

Researchers created a new version of PECS (picture communication cards) that uses virtual characters instead of just therapists. This helped children with autism feel less anxious and stay more focused during communication training. The study also developed better eye-tracking technology to measure how well children pay attention during social activities. Results showed children improved their focus and responses when using the avatar-based system.

This study developed an avatar-based Picture Exchange Communication System (PECS) to address social communication challenges in children with autism. The intervention combines traditional PECS training with virtual character technology to reduce social anxiety and improve engagement. A T-test analysis demonstrated significant improvements in children's focus and behavioral responsiveness. Additionally, the researchers developed TCG-Net, a gaze estimation algorithm using binocular images to enhance joint attention assessment.

The algorithm achieved angular errors of 4.0-6.8 degrees across three datasets, suggesting improved accuracy for tracking gaze in natural environments during social interactions.

Avatar-based PECS may be particularly beneficial for children with high social anxiety who struggle with traditional therapist-led interventions. The improved gaze tracking technology could enhance assessment and monitoring of joint attention skills in clinical settings, potentially leading to more personalized intervention approaches.

Sample size not reported, making it difficult to assess statistical power. Study design unclear from abstract. Limited details on participant characteristics, intervention duration, or comparison conditions. T-test analysis suggests small-scale preliminary investigation rather than robust clinical trial.

Children with Autism Spectrum Disorder (ASD) often struggle with social communication and feel anxious in interactive situations. The Picture Exchange Communication System (PECS) is commonly used to enhance basic communication skills in children with ASD, but it falls short in reducing social anxiety during therapist interactions and in keeping children engaged. This paper proposes the use of virtual character technology alongside PECS training to address these issues. By integrating a virtual avatar, children's communication skills and ability to express needs can be gradually improved.

This approach also reduces anxiety and enhances the interactivity and attractiveness of the training. After conducting a T-test, it was found that PECS assisted by a virtual avatar significantly improves children's focus on activities and enhances their behavioral responsiveness. To address the problem of poor accuracy of gaze estimation in unconstrained environments, this study further developed a visual feature-based gaze estimation algorithm, the three-channel gaze network (TCG-Net). It utilizes binocular images to refine the gaze direction and infer the primary focus from facial images.

Our focus was on enhancing gaze tracking accuracy in natural environments, crucial for evaluating and improving Joint Attention (JA) in children during interactive processes.TCG-Net achieved an angular error of 4.0 on the MPIIGaze dataset, 5.0 on the EyeDiap dataset, and 6.8 on the RT-Gene dataset, confirming the effectiveness of our approach in improving gaze accuracy and the quality of social interactions.