Patients suffering from renal failure face an increased risk of sudden cardiac death. The connection between those two diseases is not fully understood, yet. One possible reason could be the varying ionic concentrations of Ca2+ and K+ in this patient group. However, the monitoring of the concentrations is always done with a blood sample and a subsequent laboratory analysis.
It is widely known, that ionic concentrations have an impact on the ECG waves. For example, hyperkalaemia can result in spiky narrow T waves. In previous studies, it was tried to estimate the ionic concentrations continuously with the help of the ECG. First results were promising but results were not as precise as needed. Another step could be to classify hypo-/hyperkalaemia and hypo-/hypercalcaemia with the ECG instead of the precise concentration value. This would allow to alarm patients during critical states and to advise them to go to a hospital.
At first, a extensive literature research is needed. The goal is to analyse existing features from the ECG to be used to detect changed ionic concentrations in the blood. These features and additional ones will be detected robustly by newly developed algorithms. The algorithms will be evaluated regarding their robustness.
In the second part of the project, different classification algorithms will be investigated to solve the problem described above. Therefore, real measured data will be used. If possible, results will be compared to those from regression.