NeuroVoz: a Castillian Spanish corpus of parkinsonian speech.

The screening of Parkinson's Disease (PD) through speech is hindered by a notable lack of publicly available datasets in different languages. This fact limits the reproducibility and further exploration of existing research. To address this gap, this manuscript presents the NeuroVoz corpus consisting of 112 native Castilian-Spanish speakers, including 58 healthy controls and 54 individuals with PD, all recorded in ON state.

Depression in Alzheimer's Disease: A Delphi Consensus on Etiology, Risk Factors, and Clinical Management.

Alzheimer's disease (AD) and other forms of dementia are among the most common causes of disability in the elderly. Dementia is often accompanied by depression, but specific diagnostic criteria and treatment approaches are still lacking. This study aimed to gather expert opinions on dementia and depressed patient management to reduce heterogeneity in everyday practice.

Focus on Depression in Parkinson's Disease: A Delphi Consensus of Experts in Psychiatry, Neurology, and Geriatrics.

Major and minor forms of depression are significant contributors to Parkinson's disease morbidity and caregiver burden, affecting up to 50% of these patients. Nonetheless, symptoms of depression are still underrecognized and undertreated in this context due to scarcity of evidence and, consequently, consistent clinical guideline recommendations. Here, we carried out a prospective, multicentre, 2-round modified Delphi survey with 49 questions about the aetiopathological mechanisms of depression in Parkinson's disease (10), clinical features and connections with motor and nonmotor symptoms (10), diagnostic criteria (5), and therapeutic options (24).

Phonetic relevance and phonemic grouping of speech in the automatic detection of Parkinson's Disease.

Literature documents the impact of Parkinson's Disease (PD) on speech but no study has analyzed in detail the importance of the distinct phonemic groups for the automatic identification of the disease. This study presents new approaches that are evaluated in three different corpora containing speakers suffering from PD with two main objectives: to investigate the influence of the different phonemic groups in the detection of PD and to propose more accurate detection schemes employing speech. The proposed methodology uses GMM-UBM classifiers combined with a technique introduced in this paper called phonemic grouping, that permits observation of the differences in accuracy depending on the manner of articulation.