Development of a medical system to indicate risk of cardiovascular disease - Sooriamoorthy, Denesh (2022)
One significant issue that is encountered by individuals who experience ill effects of cardiovascular sickness, is not having the option to distinguish their illness until the manifestations give an evident sign, generally at the critical stage, which brings about a high threat of death. Furthermore, the most common method of treating severe cases is by invasive medical treatment, which is agonizing to patients. As a means to reduce this threat of severe cases or abrupt demise among individuals today due to cardiovascular disease, this research proposes to create a medical system focusing on the upstream blood pressure waveform and artificial intelligence, which would indicate the risk of cardiovascular disorder. The work in this thesis lays the groundwork for a novel risk indication system with three key sub systems. First a data acquisition system that uses a human wrist wearable device for acquiring data non-invasively, next a signal conversion system to transform radial waveforms to aortic waveforms, and finally the risk prediction system that uses a combination of a Convolutional Neural Network (CNN) and a zero-dimensional cardiovascular model’s parameters. In today's world, this combination of methods to indicate the risk of cardiovascular diseases has yet to be explored and developed, giving rise to a new pathway of risk indication. This thesis shows the details of the proposed medical system, along with testing of the hardware and the various sub systems.