An Age-Adaptive Multimedia Platform for Task-Load Elicitation for Future Physiological Monitoring Studies

Abstract

Controlled experimental phases combining cognitive activation and recovery are valuable for physiological monitoring research, since resting-state measurements alone provide limited autonomic variation for evaluating biomedical acquisition workflows. This paper presents the design and preliminary feasibility evaluation of an age-adaptive multimedia platform for task-load elicitation, developed in Python/Tkinter and designed for three age groups: preschool children, school-age children (7–14 years), and adults (15 years and above). The platform implements a five-phase protocol combining cognitive and visuomotor tasks—serial backward counting, a Stroop-based color-word task, and a time-pressure reaction task—with relaxation stimuli (music and guided breathing), all inspired by established cognitive and stress-related paradigms. A post-phase subjective questionnaire was administered to 16 participants (4 children, 12 adults) to capture perceived task load and self-reported activation. Among adult participants, the time-pressure and backwards-counting tasks produced the highest perceived-load ratings $(M=2.7$ and $M=2.1$ on a 0–4 scale), while both relaxation phases yielded low self-reported activation ratings $(M \leq 0.4)$. A single BIOPAC MP36/PPG SS4LA session confirmed technical compatibility with external acquisition hardware but does not constitute physiological validation. The platform is intended as a first-stage feasibility version for controlled task-load elicitation and future synchronized physiological data acquisition.