Advances in Parkinson's disease detection and assessment using voice and speech: A review of the articulatory and phonatory aspects
L Moro-Velazquez, JA Gomez-Garcia… - … Signal Processing and …, 2021 - Elsevier
Parkinson's Disease (PD) affects speech in the form of dysphonia and hypokinetic
dysarthria. Multiple studies have evaluated PD's influence on different aspects of speech …
dysarthria. Multiple studies have evaluated PD's influence on different aspects of speech …
A Comprehensive review on AI-enabled models for Parkinson's disease diagnosis
Parkinson's disease (PD) is a devastating neurological disease that cannot be identified with
traditional plasma experiments, necessitating the development of a faster, less expensive …
traditional plasma experiments, necessitating the development of a faster, less expensive …
Multimodal assessment of Parkinson's disease: a deep learning approach
JC Vásquez-Correa, T Arias-Vergara… - IEEE journal of …, 2018 - ieeexplore.ieee.org
Parkinson's disease is a neurodegenerative disorder characterized by a variety of motor
symptoms. Particularly, difficulties to start/stop movements have been observed in patients …
symptoms. Particularly, difficulties to start/stop movements have been observed in patients …
Explainable machine learning models based on multimodal time-series data for the early detection of Parkinson's disease
Background and objectives Parkinson's Disease (PD) is a devastating chronic neurological
condition. Machine learning (ML) techniques have been used in the early prediction of PD …
condition. Machine learning (ML) techniques have been used in the early prediction of PD …
A deep learning based method for Parkinson's disease detection using dynamic features of speech
C Quan, K Ren, Z Luo - IEEE Access, 2021 - ieeexplore.ieee.org
Detection of voice changes in Parkinson's Disease (PD) patients would make it possible for
early detection and intervention before the onset of disabling physical symptoms. This study …
early detection and intervention before the onset of disabling physical symptoms. This study …
End-to-end deep learning approach for Parkinson's disease detection from speech signals
C Quan, K Ren, Z Luo, Z Chen, Y Ling - Biocybernetics and Biomedical …, 2022 - Elsevier
More than 90% of patients with Parkinson's disease suffer from hypokinetic dysarthria. This
paper proposes a novel end-to-end deep learning model for Parkinson's disease detection …
paper proposes a novel end-to-end deep learning model for Parkinson's disease detection …
The detection of Parkinson's disease from speech using voice source information
Developing automatic methods to detect Parkinson's disease (PD) from speech has
attracted increasing interest as these techniques can potentially be used in telemonitoring …
attracted increasing interest as these techniques can potentially be used in telemonitoring …
Multi-channel spectrograms for speech processing applications using deep learning methods
Time–frequency representations of the speech signals provide dynamic information about
how the frequency component changes with time. In order to process this information, deep …
how the frequency component changes with time. In order to process this information, deep …
X-vectors: new quantitative biomarkers for early Parkinson's disease detection from speech
L Jeancolas, D Petrovska-Delacrétaz… - Frontiers in …, 2021 - frontiersin.org
Many articles have used voice analysis to detect Parkinson's disease (PD), but few have
focused on the early stages of the disease and the gender effect. In this article, we have …
focused on the early stages of the disease and the gender effect. In this article, we have …
Residual neural network precisely quantifies dysarthria severity-level based on short-duration speech segments
Recently, we have witnessed Deep Learning methodologies gaining significant attention for
severity-based classification of dysarthric speech. Detecting dysarthria, quantifying its …
severity-based classification of dysarthric speech. Detecting dysarthria, quantifying its …