The speech of individuals with Parkinson's disease (PD) is typically characterized as lacking in proper prosody because of its monopitch and monoloud quality, in addition to its reduced intensity. These qualities make it difficult for others to understand speakers with PD. The purpose of the current study was to identify what individuals with PD would do vocally, if anything at all, to improve speech production following a simulated misunderstanding of what they had just said. The study evaluated the performance of 5 individuals with PD and compared their performance to 5 age- and sex-matched controls. Specifically, measures of vocal intensity (loudness), fundamental frequency (pitch), and utterance duration were made for repetitions of a ‘misheard’ phrase. In one experimental condition noise was presented through headphones to induce the Lombard effect. Both individuals with PD and controls used increased duration as a means of enhancing clarity in a repetition. Fundamental frequency (F0) and sound pressure level (SPL) were not consistently modified in repetitions for clarification. Under most speaking conditions, individuals with PD and controls had similar F0 and SPL. Individuals with PD, like the controls, responded to the presentation of masking noise by increasing their fundamental frequency and their intensity. Therefore, not all individuals with PD exhibit difficulty using prosody.

This diploma thesis presents an analysis of speech impairments accompanying Parkinson's disease. This paper is divided into two sections - theoretical and practical. The first section gives a brief overview of available Czech and foreign literature and articles about this neurodegenerative disease. The section examines the questions of its aetiology, symptomatology, diagnostics and treatment. There can be found also a description of speech impairment connected with this disease, which is mainly hypokinetic and hyperkinetic dysarthria and dysphagia. It also deals with the problem of other limitations in communication such as facial bradykinesia or speech intelligibility. In the last chapter of theoretical part is described speech therapy and intervention with the emphasis on therapy, diagnostics and the effects of pharmacology an non-pharmacological treatment such as deep brain stimulation on speech performance in Parkinson's disease. The research part analyses speech impairment of people with Parkinson's disease. The aim of this diploma thesis was examination of this speech impairment using the Test 3F: Dysarthria profile and patient's own perception of this specific speech disorder. In this paper are presented eight case studies focusing on speech of clients with Parkinson's disease. The results...

This work deals with a design of hypokinetic dysarthria analysis system. Hypokinetic dysarthria is a speech motor dysfunction that is present in approx. 90 % of patients with Parkinson’s disease. Next there is described Parkinson's disease and change of the speech signal by this disability. The following describes the symptoms, which are used for the diagnosis of Parkinson's disease (FCR, VSA, VAI, etc.). The work is mainly focused on parameterization techniques that can be used to diagnose or monitor this disease as well as estimate its progress. A protocol of dysarthric speech acquisition is described in this work too. In combination with acoustic analysis it can be used to estimate a grade of hypokinetic dysarthria in fields of faciokinesis, phonorespiration and phonetics (correlation with 3F test). Regarding the parameterization, new features based on method RASTA. The analysis is based on parametrization sentences complicated for articulation. Experimental dataset consists of 101 PD patients with different disease progress and 53 healthy controls. For classification with feature selection have selected method mRMR.

Speech processing methods were studied to calculate parameters of pacient with Parkinon's disease. Main focus of this work is to examine diadochokinetic (DDK) tests. Algorithm for parameters extraction was proposed. It works in more parts. DC is removed from speech signal, preemphasis aplicated. Envelope of input signal is calculated, peaks of syllables are detected. Parameters and statistical results of Mann-Whitney U~test are calculated from detected peaks. Proposed algorithm is implemented in Matlab.

This project describes design of the system for diagnosis Parkinson’s disease based on speech. Parkinson’s disease is a neurodegenerative disorder of the central nervous system. One of the symptoms of this disease is disability of motor aspects of speech, called hypokinetic dysarthria. Design of the system in this work is based on the best known segmental features such as coefficients LPC, PLP, MFCC, LPCC but also less known such as CMS, ACW and MSC. From speech records of patients affected by Parkinson’s disease and also healthy controls are calculated these coefficients, further is performed a selection process and subsequent classification. The best result, which was obtained in this project reached classification accuracy 77,19%, sensitivity 74,69% and specificity 78,95%.

The diploma thesis deals with the non-invasive analysis of progression of Parkinson´s disease using the acoustic analysis of speach. Hypokinetic dysarthria in connection with Parkinson´s disease as well as speech parameters are described in this work. Speech parameters are sorted according to the speech component they affect. The work uses the phonation of vowels "a" speech task as the most commonly used speech task in the field of pathological speech processing, because of its resistance to demographic and linguistic characteristics of the speakers. Based on obtained knowledge, in MATLAB development enviroment were created systém for UPDRS III scale estimation. The UPDRS III scale is based on subjective diagnosis given by the doctor. At first, one individual parameter is used for the UPDRS III scale value estimation. Then the feature selection using SFFS algorithm is applied to gain feature combination with minimal estimation errror. Attention i salso paid to correlation between individual symptoms and UPDSR III scale.

Modern life, which is characterised by automation and mechanisation, causes laziness and inactivity in people all over the world. It in essence deprives one of movement, which negatively affects man and his body. Chronic illnesses caused by an inactive lifestyle lead to unnecessary deaths, which again impacts negatively on the community as a whole. The South African Police Service (SAPS) has far from escaped this worldwide phenomenon. It is, in fact, experiencing an abnormally high death rate, which can be linked directly to police officers’ lifestyle. This study has proven that the average police officer is in extremely poor physical condition, and that this is in all probability the cause of the unusually high natural death rate as well as the high incidence of suicide among SAPS members. The primary objective of this study is the justification of a physical maintenance programme for law enforcement officers. For this programme to be successful, it has to: (i) be relatively inexpensive and provide easily accessible facilities; (ii) be in line with critical physical job requirements; (iii) contribute directly to the maintenance of job-oriented fitness; (iv) include a section that is solely tasked with the physical maintenance of the officers; and (v) form part of the SAPS’s policy on sport. The results of this study show the dire necessity of the immediate implementation by SAPS management of the suggested physical maintenance programme. / Thesis (DPhil (Human Movement Science))--University of Pretoria, 2003. / Biokinetics, Sport and Leisure Sciences / unrestricted

Hypokinetická dysartrie (HD) je častým symptomem vyskytujícím se až u 90% pacientů trpících idiopatickou Parkinsonovou nemocí (PN), která výrazně přispívá k nepřirozenosti a nesrozumitelnosti řeči těchto pacientů. Hlavním cílem této disertační práce je prozkoumat možnosti použití kvantitativní paraklinické analýzy HD, s použitím parametrizace řeči, statistického zpracování a strojového učení, za účelem diagnózy a objektivního hodnocení PN. Tato práce dokazuje, že počítačová akustická analýza je schopná dostatečně popsat HD, speciálně tzv. dysprozodii, která se projevuje nedokonalou intonací a nepřirozeným tempem řeči. Navíc také dokazuje, že použití klinicky interpretovatelných akustických parametrů kvantifikujících různé aspekty HD, jako jsou fonace, artikulace a prozodie, může být použito k objektivnímu posouzení závažnosti motorických a nemotorických symptomů vyskytujících se u pacientů s PN. Dále tato práce prezentuje výzkum společných patofyziologických mechanizmů stojících za HD a zárazy v chůzi při PN. Nakonec tato práce dokazuje, že akustická analýza HD může být použita pro odhad progrese zárazů v chůzi v horizontu dvou let.

This work deals with a design of hypokinetic dysarthria analysis system. Hypokinetic dysarthria is a speech motor dysfunction that is present in approx. 90 % of patients with Parkinson’s disease. The work is mainly focused on parameterization techniques that can be used to diagnose or monitor this disease as well as estimate its progress. Next, features that significantly correlate with subjective tests are found. These features can be used to estimate scores of different scales like Unified Parkinson’s Disease Rating Scale (UPDRS) or Mini–Mental State Examination (MMSE). A protocol of dysarthric speech acquisition is introduced in this work too. In combination with acoustic analysis it can be used to estimate a grade of hypokinetic dysarthria in fields of faciokinesis, phonorespiration and phonetics (correlation with 3F test). Regarding the parameterization, features based on modulation spectrum, inferior colliculus coefficients, bicepstrum, approximate and sample entropy, empirical mode decomposition and singular points are originally introduced in this work. All the designed techniques are integrated into the system concept in way that it can be implemented in a hospital and used for a research on Parkinson’s disease or its evaluation.

This thesis deals with speech analysis of people who suffer from Parkinson’s disease. Purpose of this thesis is to obtain statistical sample of speech parameters which helps to determine if examined person is suffering from Parkinson’s disease. Statistical sample is based on hypokinetic dysarthria detection. For speech signal pre-processing DC-offset removal and pre-emphasis are used. The next step is to divide signal into frames. Phonation parameters, MFCC and PLP coefficients are used for characterization of framed speech signal. After parametrization the speech signal can be analyzed by statistical methods. For statistical analysis in this thesis Spearman’s and Pearson’s correlation coefficients, mutual information, Mann-Whitney U test and Student’s t-test are used. The thesis results are the groups of speech parameters for individual long czech vowels which are the best indicator of the difference between healthy person and patient suffering from Parkinson’s disease. These result can be helpful in medical diagnosis of a patient.