Autism spectrum disorder (ASD) is a developmental disorder characterized by significant social communication impairments and difficulties perceiving and presenting communication cues. Machine learning techniques have been broadly adopted to facilitate autism studies and assessments. However, computational models are primarily concentrated on specific analysis and validated on private datasets in the autism community, which limits comparisons across models due to privacy-preserving data sharing complications. This work presents a novel privacy-preserving open-source dataset, MMASD as a MultiModal ASD benchmark dataset, collected from play therapy interventions of children with Autism. MMASD includes data from 32 children with ASD, and 1,315 data samples segmented from over 100 hours of intervention recordings. To promote public access, each data sample consists of four privacy-preserving modalities of data; some of which are derived from original videos: (1) optical flow, (2) 2D skeleton, (3) 3D skeleton, and (4) clinician ASD evaluation scores of children, e.g., ADOS scores. MMASD aims to assist researchers and therapists in understanding children's cognitive status, monitoring their progress during therapy, and customizing the treatment plan accordingly. It also has inspiration for downstream tasks such as action quality assessment and interpersonal synchrony estimation. MMASD dataset can be easily accessed at https://github.com/Li-Jicheng/MMASD-A-Multimodal-Dataset-for-Autism-Intervention-Analysis.

翻译：自闭症谱系障碍（ASD）是一种以显著社交沟通障碍及沟通线索感知与呈现困难为特征的发育障碍。机器学习技术已被广泛应用于促进自闭症研究与评估。然而，自闭症研究领域的计算模型通常专注于特定分析场景，并在私有数据集上进行验证，这因数据隐私保护共享难题而限制了模型之间的横向比较。本研究提出了一个新型隐私保护开源数据集MMASD——即多模态自闭症谱系障碍基准数据集，该数据集采集自自闭症儿童游戏治疗干预过程。MMASD包含32名自闭症儿童的数据，以及从超过100小时干预记录中分割得到的1315个数据样本。为促进公共访问，每个数据样本包含四种隐私保护模态数据，其中部分数据来源于原始视频：（1）光流、（2）二维骨骼、（3）三维骨架，以及（4）临床医生对儿童的自闭症评估分数（如ADOS评分）。MMASD旨在帮助研究人员和治疗师理解儿童的认知状态，监测其在治疗过程中的进展，并据此制定个性化治疗方案。该数据集对动作质量评估与人际同步估计等下游任务也具有启发意义。MMASD数据集可通过https://github.com/Li-Jicheng/MMASD-A-Multimodal-Dataset-for-Autism-Intervention-Analysis 便捷访问。