Computer-Aided Decision Support System for Hepatic Encephalopathy

The goal of this project is to provide deep speech and handwriting analysis and investigate whether speech and handwriting can be used for diagnosis and monitoring of hepatic encephalopathy and whether there exists relationship between speech, handwriting and other biomarkers in hepatic encephalopathy. The number of novel signal processing algorithms, which reveal alteration in handwriting and speech more accurately than existing approaches, are proposed, giving rise to new group of features. The robust feature selection algorithms select the optimal subset of these features, which are fed into non-parametric regression and classification algorithms, mapping the signal processing algorithm outputs to stage of hepatic encephalopathy. Even though proposed project is focused on particular disease, we expect that some of the outputs, such as new features will be applicable also for other diseases.