Comparison of CNN-Learned vs. Handcrafted Features for Detection of Parkinson's Disease Dysgraphia in a Multilingual Dataset.

Parkinson's disease dysgraphia (PDYS), one of the earliest signs of Parkinson's disease (PD), has been researched as a promising biomarker of PD and as the target of a noninvasive and inexpensive approach to monitoring the progress of the disease. However, although several approaches to supportive PDYS diagnosis have been proposed (mainly based on handcrafted features (HF) extracted from online handwriting or the utilization of deep neural networks), it remains unclear which approach provides the highest discrimination power and how these approaches can be transferred between different datasets and languages. This study aims to compare classification performance based on two types of features: features automatically extracted by a pretrained convolutional neural network (CNN) and HF designed by human experts.

Articulatory network reorganization in Parkinson's disease as assessed by multimodal MRI and acoustic measures.

Introduction: Hypokinetic dysarthria (HD) is common in Parkinson's disease (PD). Our objective was to evaluate articulatory networks and their reorganization due to PD pathology in individuals without overt speech impairment using a multimodal MRI protocol and acoustic analysis of speech.

Methods: A total of 34 PD patients with no subjective HD complaints and 25 age-matched healthy controls (HC) underwent speech task recordings, structural MRI, and reading task-induced and resting-state fMRI.

Patterns of diffusion kurtosis changes in Parkinson's disease subtypes.

Background: Diffusion kurtosis imaging has been applied to evaluate white matter and basal ganglia microstructure in mixed Parkinson's disease (PD) groups with inconclusive results.

Objectives: To evaluate specific patterns of kurtosis changes in PD and to assess the utility of diffusion imaging in differentiating between healthy subjects and cognitively normal PD, and between PD with and without mild cognitive impairment.

Methods: Diffusion scans were obtained in 92 participants using 3T MRI.

Psychometric Properties of Screening Questionnaires for Children With Handwriting Issues.

Dysgraphia (D) is a complex specific learning disorder with a prevalence of up to 30%, which is linked with handwriting issues. The factors recognized for assessing these issues are legibility and performance time. Two questionnaires, the Handwriting Proficiency Screening Questionnaire (HPSQ) for teachers and its modification for children (HPSQ-C), were established as quick and valid screening tools along with a third factor - emotional and physical well-being.

Quantitative Analysis of Relationship Between Hypokinetic Dysarthria and the Freezing of Gait in Parkinson's Disease.

Hypokinetic dysarthria (HD) and freezing of gait (FOG) are both axial symptoms that occur in patients with Parkinson's disease (PD). It is assumed they have some common pathophysiological mechanisms and therefore that speech disorders in PD can predict FOG deficits within the horizon of some years. The aim of this study is to employ a complex quantitative analysis of the phonation, articulation and prosody in PD patients in order to identify the relationship between HD and FOG, and establish a mathematical model that would predict FOG deficits using acoustic analysis at baseline.

Non-invasive stimulation of the auditory feedback area for improved articulation in Parkinson's disease.

Introduction: Hypokinetic dysarthria (HD) is a common symptom of Parkinson's disease (PD) which does not respond well to PD treatments. We investigated acute effects of repetitive transcranial magnetic stimulation (rTMS) of the motor and auditory feedback area on HD in PD using acoustic analysis of speech.

Methods: We used 10 Hz and 1 Hz stimulation protocols and applied rTMS over the left orofacial primary motor area, the right superior temporal gyrus (STG), and over the vertex (a control stimulation site) in 16 PD patients with HD.

Vowel Articulation Dynamic Stability Related to Parkinson's Disease Rating Features: Male Dataset.

Neurodegenerative pathologies as Parkinson's Disease (PD) show important distortions in speech, affecting fluency, prosody, articulation and phonation. Classically, measurements based on articulation gestures altering formant positions, as the Vocal Space Area (VSA) or the Formant Centralization Ratio (FCR) have been proposed to measure speech distortion, but these markers are based mainly on static positions of sustained vowels. The present study introduces a measurement based on the mutual information distance among probability density functions of kinematic correlates derived from formant dynamics.

Parkinson Disease Detection from Speech Articulation Neuromechanics.

The research described is intended to give a description of articulation dynamics as a correlate of the kinematic behavior of the jaw-tongue biomechanical system, encoded as a probability distribution of an absolute joint velocity. This distribution may be used in detecting and grading speech from patients affected by neurodegenerative illnesses, as Parkinson Disease. The work hypothesis is that the probability density function of the absolute joint velocity includes information on the stability of phonation when applied to sustained vowels, as well as on fluency if applied to connected speech.

Prosodic analysis of neutral, stress-modified and rhymed speech in patients with Parkinson's disease.

Background And Objective: Hypokinetic dysarthria (HD) is a frequent speech disorder associated with idiopathic Parkinson's disease (PD). It affects all dimensions of speech production. One of the most common features of HD is dysprosody that is characterized by alterations of rhythm and speech rate, flat speech melody, and impairment of speech intensity control.