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.