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Utilizing touch interactions from smartphones for gathering data and identifying digital markers for screening and monitoring neurological disorders, such as Autism Spectrum Disorder (ASD), is an emerging area of research. Smartphones provide multiple benefits for this kind of study, including unobtrusive data collection via built-in sensors, integrated haptic feedback systems, and the capability to create specialized applications. Acknowledging the significant yet understudied presence of tactile processing differences in individuals with ASD, we designed and developed Feel and Touch, a mobile game that leverages the haptic capabilities of smartphones. This game provides vibrotactile feedback in response to touch interactions and collects data on these interactions. We conducted a deployment study with 83 Mexican children who played Feel and Touch to capture their interactions with the game. Our analysis, comparing touch interactions between children with ASD and neurotypical (NT) peers, uncovered three digital markers based on phone tilt and touch patterns that distinguish the two groups. Additionally, we demonstrated the ability of a machine learning model to accurately classify these interactions between ASD and NT children. Our findings discuss the implications in terms of accessibility and ubiquity, as well as the possibilities for the development of digital markers and their application in pervasive computing for healthcare.