Ing. Zoltán Galáž, Ing. Jiří Mekyska, prof. Ing. Zdeněk Smékal, CSc.
Date of creation: 18. 8. 2016
It is possible to download software here.
Publication to be cited
GALÁŽ, Z.; MEKYSKA, J.; MŽOUREK, Z.; KISKA, T.; SMÉKAL, Z.; REKTOROVÁ, I. Degree of Parkinson’ s Disease Severity Estimation Based on Speech Signal Processing. In Proceedings of the 39th International Conference on Telecommunication and Signal Processing, TSP 2016. 1. 2016. s. 1-4. ISBN: 978-1-5090-1287-9.
GALÁŽ, Z. Potential of Prosodic Features to Estimate Degree of Parkinson’ s disease severity. In Proceedings of the 22nd Conference STUDENT EEICT 2016. Brno: 2016. s. 533-537. ISBN: 978-80-214-5350- 0.
In the field of biomedical signal processing (e.g. pathological speech signal processing), often it is necessary to use correlation analysis first to evaluate and visualize the sufficiency of selected objective parametrization techniques to quantify and predict the health state of the analysed subject on selected subjective rating scales assessing severity of the disease.
Software CORR provides an easy way to perform correlation analysis using Pearson, Spearman and Kendall’s correlation. Software CORR also enables automatic saving of the results to tables of *.xlsx type and also visualizing so called “correlation diagrams”. This package is written in the MATLAB programming environment.
The testing scripts demo.m can be used to test functionality of the software. The script loads data from the test_corr.mat file, which includes the parametrization matrix “feat_matrix”: rows are determined for the observations; columns are determined for the parameters, names of the features and the matrix of labels “clin_matrix” (continuous numeric scale).
This work was supported by projects AZV 16-30805A, LO1401, COST IC1206 a FEKT-S-14-2335. The described research was performed in laboratories supported by the SIX project; the registration number CZ.1.05/2.1.00/03.0072, the operational program Research and Development for Innovation.