In this exploratory study, we propose a questionnaire-derived human sensing framework for assessing functional health support demands using perceived health and lifestyle signals. A structured questionnaire was completed by 40 participants. The six functional demands differed significantly (Friedman test, χ2 = 28.023, p < 0.001), with sleep/relaxation and heat reduction showing relatively high mean scores. Spearman correlation analysis with Benjamini–Hochberg false discovery rate (FDR) correction identified 29 significant associations among 60 signal–demand comparisons. Strong associations were observed between dryness/heat sensation and heat reduction (ρ = 0.733), fatigue and energy support (ρ = 0.644), digestive discomfort and digestive support (ρ = 0.602), and poor sleep and sleep/relaxation support (ρ = 0.547). These relationships were transformed into an interpretable FDR-supported association network. The findings demonstrate the potential of structured self-reported responses as complementary human sensing information for personalized health support assessment.