To investigate the current status of sensor- and IoT-enabled internet medical service utilization and its influencing factors among elderly patients with chronic diseases, in this study, we aim to provide evidence-based references for optimizing digital health service adoption, fostering an “active health” mindset, and promoting active aging. In particular, in this study, we emphasize how user-related cognitive and psychosocial factors shape the effective utilization of sensor-integrated and IoT-supported medical services, which is critical for the real-world performance of sensing-enabled healthcare systems. A convenient sampling method was employed to recruit elderly participants aged 60–70 years from cities with heterogeneous economic development levels in Guangdong Province for a cross-sectional survey. The investigated internet medical services primarily encompassed remote health monitoring, online registration, digital medical payment, and data-supported medical consultation, which are increasingly integrated with wearable sensors and connected health devices. These services rely on continuous data acquisition, transmission reliability, and user–sensor interaction as fundamental sensing components. IBM SPSS Statistics 25.0 and IBM SPSS Amos 28.0 software were used to conduct a serial mediation model analysis, with the active utilization of internet medical services as the core outcome variable, aiming to systematically identify the multifaceted factors affecting service adoption in this population. This analytical framework helps explain how sensing-enabled medical technologies are translated from technical availability into actual use. The results showed that the active utilization rate of internet medical services among elderly patients with chronic diseases was 35.7%, with online registration and medical payment being the most frequently used functions. Furthermore, self-efficacy and satisfaction with internet medical services exhibited a significant serial mediating effect in the relationship between social support and the willingness to adopt IoT-supported digital health services. These results provide user-oriented insights relevant to the design and deployment of sensor-based healthcare systems. These findings highlight the importance of enhancing user-centered sensor-integrated service design and digital health literacy to improve utilization among elderly individuals with chronic conditions. From a sensing perspective, our study contributes empirical evidence linking human factors with the effective deployment of IoT-based medical sensing systems.