| Abstract: |
Wearable-based monitoring systems are increasingly applied in preventive healthcare to support early identification of health risks in both clinical and general populations. Young adults are typically regarded as a low-risk group due to preserved physical function and low disease prevalence and are therefore less frequently prioritized for intensive health monitoring. As a result, health assessment in this population often relies on self-reported measures. However, such approaches may not adequately capture underlying behavioral patterns, including reduced physical activity or associated psychological vulnerability. From a monitoring system design perspective, examining discrepancies between objective sensor-derived data and subjective health perception is important for evaluating current monitoring approaches and informing the development of user-centered healthcare monitoring systems.
As a wearable-based health monitoring case study, 26 healthy adults aged ≥19 years (mean age ± SD: 43.15 ± 18.9 years; 9 males, 17 females) were recruited from Yonsei University Mirae Campus, South Korea, and stratified into two age groups (<40 years, n = 11; ≥40 years, n = 15). Objective physical activity was monitored for two consecutive days using a triaxial accelerometer-based wearable sensor (ActiGraph LEAP) worn on the non-dominant wrist. Outcome measures included step count, activity-related energy expenditure, moderate-to-vigorous physical activity (MVPA), sedentary time, and light-intensity activity. Subjective health perception and mental health status were assessed using validated questionnaires: the EuroQol five-dimension five-level questionnaire (EQ-5D-5L), the EuroQol visual analogue scale (EQ-VAS), DSM-5–based screening tools, the Short Geriatric Depression Scale (SGDS), and the Mini Nutritional Assessment (MNA). Between-group comparisons were performed using nonparametric statistical tests.
Objective wearable-derived measures demonstrated significant age-related differences in physical activity patterns. Participants aged ≥40 years exhibited 39% higher daily step counts and 60.39% greater moderate-to-vigorous physical activity compared with younger adults, despite greater sedentary time. Younger adults showed slightly higher light-intensity activity. However, activity-related energy expenditure was only marginally higher (+4.5%), indicating lower overall physical activity levels. Subjective health perception, assessed using the EQ-VAS, was significantly lower in younger adults (78.18 vs. 91.53, p = 0.0034), whereas EQ-5D index scores did not differ significantly between groups. Elevated risks of depression, insomnia, and nutritional deficiency were observed predominantly in the younger group and were consistent with objectively measured inactivity patterns.
This study indicates that wearable-based monitoring systems can identify physical activity patterns and associated health risks missed by self-reports, particularly in populations traditionally considered low-risk. The observed age-group differences should be interpreted in the context of monitoring system design rather than as evidence of age-related health advantage. From a design and evaluation perspective, integrating objective sensor-derived data with subjective assessments may support more accurate health risk identification and inform the development of scalable, user-centered healthcare monitoring systems aimed at early detection and health promotion in young adult populations. |