Work

MindTS-MMD: A Chinese Multimodal Dataset for Emotion Expression Analysis in Children with Tourette Syndrome

Year: 2026

Type: data-paper

Abstract: Multimodal resources for emotion expression analysis in pediatric clinical populations remain limited, particularly for children with Tourette syndrome (TS). MindTS-MMD was developed as a Chinese multimodal dataset to support computational research on emotional expression and tic-related behavior in this population. The dataset contains 10,034 instance-level samples from 60 children with TS aged 6-12 years, collected through semi-structured emotion-elicitation tasks. Each sample includes available symbolic representations from three modalities-visual, acoustic, and semantic-and is linked to a corresponding annotation record. The annotations cover seven categories: anxious, calm, focused, irritable, relaxed, shy, and tense, together with child-reported and experimenter-observed valence-arousal ratings and tic occurrence, anatomical location, and frequency when observable. Annotation reliability, signal quality, audiovisual synchronization, facial tracking, modality completeness, and tic-emotion co-occurrence were evaluated. Unimodal and multimodal baselines are provided to illustrate the computational usability of the released representations.

Source: Scientific Data

DOI: 10.1038/s41597-026-08006-4

Authors: Jianping Wang, Haoyu Wu, Liping Li, Xiaoxia Fang, Qian Li

Institutions: Henan Institute of Science and Technology, Xinxiang Central Hospital, Henan Medical University

Language: English

Topic: Emotion and Mood Recognition

Subfield: Experimental and Cognitive Psychology

Field: Psychology

Domain: Social Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $2,490