The Internet of Things (IoT) has become the main platform for the interaction of interconnected devices, representing a new paradigm and the next step in the evolution of the internet. Its importance is especially noticeable in health care, where the IoT monitors medical services. By analyzing the data collected from different devices, it is possible to predict the development of certain diseases. One of the promising areas is stress control through wearable sensors and IoT, which significantly increases well-being and improves preventive health management. Medical professionals are already using reliable systems that include wearable devices on batteries and wireless communication channels to economically monitor the state of health in various diseases. Sensors connected to the network, deployed both at home and in the human body, collect important data necessary to assess the health of patients. The integration of machine learning and advanced technologies has aroused great interest in the study and solution of problems related to stress levels. Psychological stress significantly affects the physiological parameters of a person and can lead to negative consequences, sometimes requiring expensive treatment. Acute levels of stress can be life-threatening, especially for people diagnosed with borderline personality disorder or schizophrenia. This article provides a systematic review of the literature on Wearable IoT devices in healthcare. The review begins with a search for publications by given keywords and ordering them by relevance and publication date. The article discusses the use of wearable devices to address health problems such as disease detection, control, and treatment, and describes their architecture. In addition, promising areas of future research are outlined.