Questionnaire-derived Human Sensing for Health Need Assessment

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, χ 2 = 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 signaldemand 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.