A Facial Affect Analysis System for Autism Spectrum Disorder
In this paper, we introduce an end-to-end machine learning-based system for classifying autism spectrum disorder (ASD) using facial attributes such as expressions, action units, arousal, and valence. Our system classifies ASD using representations of different facial attributes from convolutional neural networks, which are trained on images in the wild. Our experimental results show that different facial attributes used in our system are statistically significant and improve sensitivity, specificity, and F1 score of ASD classification by a large margin. In particular, the addition of different facial attributes improves the performance of ASD classification by about 7% which achieves a F1 score of 76%.
Code (0)
등록된 구현이 없습니다.
Tasks
BIG-bench Machine LearningClassificationGeneral ClassificationSensitivitySpecificitySimilar Papers 제목 키워드 기반
A Two-stage Multi-modal Affect Analysis Framework for Children with Autism Spectrum Disorder
Autism spectrum disorder (ASD) is a developmental disorder that influences the communication and social behavior of a person in a way that those in the spectrum have difficulty in perceiving other people's facial express…
Proposing a System Level Machine Learning Hybrid Architecture and Approach for a Comprehensive Autism Spectrum Disorder Diagnosis
Autism Spectrum Disorder (ASD) is a severe neuropsychiatric disorder that affects intellectual development, social behavior, and facial features, and the number of cases is still significantly increasing. Due to the vari…
DiagnosticViTASD: Robust Vision Transformer Baselines for Autism Spectrum Disorder Facial Diagnosis
Autism spectrum disorder (ASD) is a lifelong neurodevelopmental disorder with very high prevalence around the world. Research progress in the field of ASD facial analysis in pediatric patients has been hindered due to a …
DecoderHuman vs. NAO: A Computational-Behavioral Framework for Quantifying Social Orienting in Autism and Typical Development
Responding to one's name is among the earliest-emerging social orienting behaviors and is one of the most prominent aspects in the detection of Autism Spectrum Disorder (ASD). Typically developing children exhibit near-r…
Face DetectionPilot Study to Discover Candidate Biomarkers for Autism based on Perception and Production of Facial Expressions
Purpose: Facial expression production and perception in autism spectrum disorder (ASD) suggest potential presence of behavioral biomarkers that may stratify individuals on the spectrum into prognostic or treatment subgro…