Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder that has gained global attention due to its prevalence. Clinical assessment measures rely heavily on manual scoring conducted by specialized physicians. However, this approach exhibits subjectivity and challenges in regions without sufficient medical resources. This study presents paradigms designed to automatically evaluate various aspects of social skills in children with ASD, utilizing our multiview and multimodal behavior system. Moreover, we propose a new pipeline to predict autism-related social skill scores using the language-image pre-training model. Our multimodal behavioral database comprises 12 subjects (511 videos with labeled social skill scores). Finally, we achieve 81.46% accuracy on the paradigm success prediction task and 69.23% accuracy on the social skill ability scoring task. The results demonstrate that the language-image pre-training model can effectively introduce domain knowledge into video assessment tasks. 

Assessing the Social Skills of Children with Autism Spectrum Disorder via Language-Image Pre-training Models

The assessment of children at risk of autism typically involves a clinician observing, taking notes, and rating children's behaviors. A machine learning model that can label adult and child audio may largely save labor in coding children's behaviors, helping clinicians capture critical events and better communicate with parents. In this study, we leverage Wav2Vec 2.0 (W2V2), pre-trained on 4300-hour of home audio of children under 5 years old, to build a unified system for tasks of clinician-child speaker diarization and vocalization classification (VC). To enhance children's VC, we build a W2V2 phoneme recognition system for children under 4 years old, and we incorporate its phonetically-tuned embeddings as auxiliary features or recognize pseudo phonetic transcripts as an auxiliary task. We test our method on two corpora (Rapid-ABC and BabbleCor) and obtain consistent improvements. Additionally, we outperform the state-of-the-art performance on the reproducible subset of BabbleCor. 

pdf/enhancing-child-vocalization-classification-with-lkn0ea3dldmq.pdf

Enhancing Child Vocalization Classification with Phonetically-Tuned Embeddings for Assisting Autism Diagnosis

Adaptive functioning constitutes a fundamental aspect of the phenotype associated with autism spectrum disorder (ASD) in preschool-aged children, exerting a significant influence on both the child and the family’s overall quality of life. The aim of this study was to investigate the predictors of the adaptive functioning domains in preschool-age children with ASD at two time points, providing a snapshot of this fundamental developmental step. Methods: Ninety-five children with ASD (M = 3.89, SD = 1.13) were included in the study and longitudinal data (the mean length of the longitudinal data collection was 1 year) on ASD features such as social communication and social interaction, repetitive and restricted behavior, cognitive level, and adaptive functioning were collected. We considered autistic features, cognitive level, and sociodemographic factors as possible predictors of the different adaptive functioning domains one year later. Results: Data obtained showed a worsening of the ASD features and adaptive functioning after one year. Furthermore, the severity of repetitive and restricted behavior predicted adaptive functioning, especially in the social and practical domains of the child, one year later. This prediction was observed alongside the child’s cognitive level. Conclusions: The study identifies some potential predictive factors of specific adaptive functioning domains in preschoolers with ASD. Considering how critical adaptive functioning is for the well-being of both the child and their family, it becomes imperative to design early-stage interventions focused on nurturing adaptive skills in children with ASD.

What Factors Predict Adaptive Functioning in Preschool Children with Autism Spectrum Disorder? A Longitudinal Study

Diferenças no Comportamento Adaptativo entre Crianças e Adolescentes com Transtorno do Espectro Autista e com Desenvolvimento Típico e Efeitos de Características Sociodemográficas

Mind the Gap: Executive Function Is Associated with the Discrepancy Between Cognitive and Adaptive Functioning in Autistic Children Without Cognitive Delay

Exploring Tactile Initiation of Joint Attention in Autistic Children.

Cognitive-adaptive Functioning Gap and Mediating Factors that Impact Adaptive Functioning in Chinese Preschool-aged Children with Autism Spectrum Disorder.

Behavioral observation plays an essential role in the diagnosis of Autism Spectrum Disorder (ASD) by analyzing children’s atypical patterns in social activities (e.g., impaired social interaction, restricted interests, and repetitive behavior). To date, this process still heavily relies on the questionnaire survey, clinical observation, or retrospective video analysis, leading to high demand for professionals with massive labor costs. This paper proposes a standardized platform for stimulating, gathering, analyzing, modeling, and interpreting human behavioral data in the application of computer-aided ASD diagnosis. By a structured assessment process, the proposed system can automatically evaluate children’s multiple social interaction skills using the captured audio-visual data and provide the final diagnostic suggestions. We collect a multimodal behavioral database of 95 participants (71 children with ASD and 24 age-matched typical controls) in a real clinic environment, the Third Affiliated Hospital of Sun Yat-sen University, China. On the clinical database, our proposed computer-aided ASD diagnosis system obtains an accuracy of 88.42% for identifying ASD children with an average age of 24 months, representing a performance comparable to top-level human experts. As a unified and replicable solution, it has good potential to be promoted to less developed areas with limited high-quality medical resources. 

Computer-Aided Autism Spectrum Disorder Diagnosis With Behavior Signal Processing

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Exploring Tactile Initiation of Joint Attention in Autistic Children.

Cognitive-adaptive Functioning Gap and Mediating Factors that Impact Adaptive Functioning in Chinese Preschool-aged Children with Autism Spectrum Disorder.

Computer-Aided Autism Spectrum Disorder Diagnosis With Behavior Signal Processing