An automatic sustained attention prediction (ASAP) method for infants and toddlers using wearable device signals.

ABSTRACT: Sustained attention (SA) is a critical cognitive ability that emerges in infancy and affects various aspects of development. Research on SA typically occurs in lab settings, which may not reflect infants' real-world experiences. Infant wearable technology can collect multimodal data in natural environments, including physiological signals for measuring SA. Here we introduce an automatic sustained attention prediction (ASAP) method that harnesses electrocardiogram (ECG) and accelerometer (Acc) signals. Data from 75 infants (6- to 36-months) were recorded during different activities, with some activities emulating those occurring in the natural environment (i.e., free play). Human coders annotated the ECG data for SA periods validated by fixation data. ASAP was trained on temporal and spectr

SUBMITTER: Zhang Y 

PROVIDER: S-EPMC12006380 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature