I use mathematical models to understand diseases such as cardiovascular diseases and obesity. My main research focus is modeling of the cardiovascular system to understand the underlying mechanisms of high blood pressure.
Cardiovascular models to understand hypertension
Hypertension is one of the most common health issues today with 25% men affected worldwide. Hypertension is defined in Europe as a systolic/diastolic blood pressure above 140/90 mmHg, and uncontrolled hypertension is a risk factor for cardiovascular diseases such as coronary artery disease, heart failure, and renal failure. The basic underlying mechanisms are known, but the treatment and the connection to other cardiovascular diseases is complex and there is a need of deeper understanding of the changes in hemodynamics during hypertension. My aim is to describe the complex mechanisms behind hypertension by further using and developing a mathematical lumped parameter model of the cardiovascular system.
Personalized models with individual hemodynamics can be created by including pressure cuff measurements and informative imaging data such as four-dimensional magnetic resonance imaging (4D Flow MRI) data into the model. Through comparing and using the personalized models, new insights of the hemodynamic mechanisms behind hypertension can be found. Furthermore, an updated cardiovascular model could together with automated data processing provide a new clinical tool for individualized diagnostics and treatment planning in hypertension.
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Fields of Teaching
Supervisor in bachelor projects in systems biology for students in engineering biology.
Supervisor in engineering projects for first year students at the Y, Yi and MED programs in the project “ECG registration during physical activity”.