In the healthcare field, workload management is important because the workload of healthcare professionals such as nurses affects the safety and quality of treatment and care for patients. However, changing circumstances surrounding operations are inevitable in healthcare, and workloads change from time to time in response to changing circumstances. Therefore, management is required to accommodate such changes. For this purpose, it is necessary to predict the workload in real time based on various factors such as the state of workers under changing conditions and reflect this in management, but no method has been established to predict the workload in healthcare in real time in response to changing conditions. Therefore, in this study, focusing on the development of wearable devices and Internet of Things (IoT) technology, we conducted a simulation experiment in a simulated ward environment and acquired data that could be acquired by wearable devices available in real time to analyze the workload change during tasks. Several indicators showed a significant main effect on workload (p < 0.01), suggesting that multiple indicators of patient and ward conditions can be obtained in real time are effective in the evaluation of workload.