# Heart DT: Monitoring and Preventing Cardiac Pathologies Using AI and IoT Sensors
## 2 Related Work  
The concept of DTs have been investigated in different fields of research for several years now. However, they are currently gaining increasing importance, and were the third-highest trending technology in 2020 according to the IEEE Computer Society [6]. The key elements of DTs are the physical component, the digital component, and the communication link between them, involving bidirectional communication to keep the two mirror elements constantly updated. The digital counterpart is the element that allows to increase the capabilities of a normal physical object or system by adding, for example, an AI component. In general, DTs are employed in many sectors, including the manufacturing industry [7; 8], and in energy production [9; 10], agriculture [11], transportation [12], and many others [13; 14]. Due to their multiple application possibilities and their ability to improve the efficiency and effectiveness of processes and systems, it is expected that their use will be sustained in the future. Particular attention is paid to the application of this technology in the healthcare field [15; 16; 17]. It is considered that by applying such technology it is possible to provide doctors with a valuable tool to analyze data in real time, monitor patients' conditions, and prevent possible diseases by correlating the obtained information with AI techniques [18; 19]. In the medical field, DTs can be used to simulate the behavior of organs, tissues, or parts of the human body [20]. These models can be used to improve the current understanding of diseases, predict possible complications, and develop new therapies. For example, a DT that replicates the cardiovascular system can be used to simulate synthetic photoplethysmogram (PPG) data to evaluate blood flow and pressure, as well as to predict possible obstructions and arteriosclerosis [21], thus assisting doctors in making decisions concerning the most suitable treatment for the patient. Another example of the use of DTs in medicine concerns the design of customized prostheses and medical devices [22]. DTs can also be used for simulations of complex surgical procedures [23], analysis of medical device performance, and disease prevention through the collection and analysis of patient data. The use of DTs in the medical field is not only aimed at the services provided by the healthcare facility, but also to optimize the structure itself, as described by [PERSON] et al. [24], where a tool is proposed to evaluate the efficiency of healthcare services in real time using predictive analysis. There are other papers that focus on assisting the elderly [25] and systems for detecting ischemic heart disease (IHD) [26]. Finally, some papers aim at analyzing healthcare assistance based on the metaverse [27]. Among the various application contexts discussed, extensive studies have focused on the use of DTs in the cardiac field, which is also the subject of the current research. In fact, it is well known that there are some pathologies, such as myocardial infarction, which--if properly monitored--could decrease the mortality rate [28]. As proposed by [PERSON] et al. [29] cardiac digital twins (CDTs) may be used as digital replicas of patients' hearts, thus assisting in clinical decision making and testing of new therapies. A study proposed by [PERSON] et al. [30] focuses on the use of computer graphics to visualize the electrical activity of the heart using a voxel representation of a 3D heart model and a spring voxel as a unit volume. The paper also discusses the process of voxelization and the use of mathematical models for visualization based on the Aliev-Panfilov model. The possibility of presenting ischemic myocardial damage using the developed model is also considered. Similarly, a study proposed by [PERSON] et al. [26] describes the architecture referred to as the cardio twin, designed to detect IHD and prevent heart problems such as ischemia and stroke.