Wearable technologies have become a significant part of the healthcare industry, collecting personal health data and extracting valuable information for real-time assistance. This review paper analyzes thirty-five scientific publications on driving healthcare monitoring with IoT and wearable device applications. These papers were considered in a quantitative and qualitative analysis using the Natural Language Processing framework and the PRISMA methodology to filter the search results. The selected papers were published between January 2010 and May 2024 in one of the following scientific databases: IEEE Xplore, Springer, ScienceDirect (i.e., Elsevier), Association for Computing Machinery (ACM), Multidisciplinary Digital Publishing Institute (MDPI), or PubMed Central. The analysis considers population, methods, hardware, features, and communications. The research highlights that data collected from one or numerous sensors is processed and accessible in a database server for various uses, such as informing professional careers or assisting users. The review suggests that robust and efficient driving healthcare monitoring with IoT and wearable devices applications can be designed considering the valuable principles presented in this review.