Diadochokinetic tasks analysis tool


Ing. Peter Kukučka, Ing. Jiří Mekyska, prof. Ing. Zdeněk Smékal, CSc.


It is possible to download software here.

Publication to be cited

SMÉKAL, Z.; MEKYSKA, J.; REKTOROVÁ, I.; FAÚNDEZ ZANUY, M. Analysis of neurological disorders based on digital processing of speech and handwritten text. In 2013 International Symposium on Signals, Circuits and Systems (ISSCS). 2013. pp. 1-6. ISBN: 978-1-4799-3193-4.

MEKYSKA, J.; SMÉKAL, Z.; KOŠŤÁLOVÁ, M.; MRAČKOVÁ, M.; SKUTILOVÁ, S.; REKTOROVÁ, I. Motor Aspects of Speech Imparment in Parkinson’s Disease and their Assessment. Cesk Slov Neurol N, 2011, vol. 74, no. 6, pp. 662-668. ISSN: 1210-7859.


DDK (Diadochokinetic Tasks) are specially designed for an analysis of articulation precision in patients with Parkinson’s disease. During these tasks patients repeatedly pronounce syllables that contains combination plosive-vowel, for instance “pa-ta-ka-pa-ta-ka-pa-ta-ka…”. Fast changes in articulatory organs position can be observed during these tasks. In some cases the patients are not able to do these fast changes, in other cases they keep speech rate at the expense of decreased articulatory organs movement, therefore a speech intelligibility is decreased.

This tool quantifies DDK tasks according to local maxima that are used to split DDK task into particular cycles. These local maxima are identified in speech signal using an analysis of envelope that was calculated using Hilbert transformation or difference of consecutive speech samples. The tool provides extraction of these features: position of local DDK maxima, values of local DDK maxima, mean DDK period, number of DDK cycles, mean DDK cycle intensity, maximal DDK cycle intensity, maximal speech intensity, mean speech intensity, std of DDK period, std of DDK cycle intensity, coefficient of variation of DDK period, coefficient of variation of DDK cycle and jitter of DDK periods.

It is possible to analyse DDK in MATLAB using function results = ddk(data, vzorkovacia_frekvencia, vykresli_grafy), where variable data contains a column vector of speech samples, variable vzorkovacia_frekvencia contains sampling frequency and binary variable vykresli_grafy determines, whether some plots showing the maxima in signal (and other characteristics) will be displayed (to display the graphs, set this variable to 1). Structure results contains the calculated features. Particular features in this structure are described in help, that can be in MATLAB command line shown using command: help ddk


This work was supported by projects NT13499, VG20102014033 and 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.


To negotiate the license terms of use of this software please contact the responsible person Ing. Lukas Novak at Technology Transfer Office, Brno University of Technology, Kounicova 966/67a, Veveří, 60200, Brno, Czech Republic, novak@ro.vutbr.cz.