Biosensors And Intelligent Algorithms for Heart Failure Monitoring

Abstract

Heart failure is one of the most common causes of mortality and the final stage of cardiovascular disease. The prognosis of individuals with chronic heart failure has improved to some extent which is thanks to our increased understanding of heart failure. Both invasive and non-invasive biosensors have advanced significantly during the previous ten years. It has been demonstrated that biosensors can identify heart failure early and lower the need for hospitalization. In the past, biosensors mainly detected the general condition of patients' vital signs, but now they have been developed into invasive biosensors for monitoring pressure changes such as a pulmonary artery pressure, right ventricle pressure, left atrium pressure and so on. It allows clinicians to observe the function of the heart more intuitively. Non-invasive biosensors can monitor electrocardiograms, heart sounds, pleural effusion and so on, and evaluate the risk of recurrent heart failure by observing the risk factors of heart failure deterioration. Although this kind of sensor cannot cause harm to patients, often not as accurate and timely as invasive sensors. There are intelligent algorithms based on biosensors, which belongs to machine learning, which can greatly improve the specificity of patient diagnosis. These biosensors and intelligent algorithms can further improve the survival rate of patients.