Automatic speech analysis in patients with parkinson's disease using feature dimension reduction

I El Moudden, M Ouzir, S ElBernoussi - Proceedings of the 3rd …, 2017 - dl.acm.org
Dysphonia is a common speech disorder in Parkinson's disease. Speech analyses have
already been used in patients with Parkinson's disease and class prediction is an essential …

Feature selection and extraction for class prediction in dysphonia measures analysis: A case study on Parkinson's disease speech rehabilitation

I El Moudden, M Ouzir… - Technology and Health …, 2017 - content.iospress.com
BACKGROUND: Speech disorders such as dysphonia and dysarthria represent an early
and common manifestation of Parkinson's disease. Class prediction is an essential task in …

An efficient dimensionality reduction method using filter-based feature selection and variational autoencoders on Parkinson's disease classification

H Gunduz - Biomedical Signal Processing and Control, 2021 - Elsevier
Parkinson's disease (Pd) is a progressive disease caused by the loss of brain cells and
brings about speech and pronunciation defects during the early stages. This study revealed …

An adaptive intelligent diagnostic system to predict early stage of parkinson's disease using two-stage dimension reduction with genetically optimized lightgbm …

J Dhar - Neural Computing and Applications, 2022 - Springer
Parkinson's disease is one of the most prevalent neurodegenerative sicknesses
distinguished by motor function impairment. Parkinson's disease (PD) diagnosis is a …

[HTML][HTML] Effective dysphonia detection using feature dimension reduction and kernel density estimation for patients with Parkinson's disease

S Yang, F Zheng, X Luo, S Cai, Y Wu, K Liu, M Wu… - PloS one, 2014 - journals.plos.org
Detection of dysphonia is useful for monitoring the progression of phonatory impairment for
patients with Parkinson's disease (PD), and also helps assess the disease severity. This …

Speech recognition using feed forward neural network and principle component analysis

N Momo, Abdullah, J Uddin - … of Third International Symposium on Signal …, 2018 - Springer
Various models have been proposed with many dimension reduction techniques and
classifiers in the field of pattern recognition by using audio signal processing. In this paper …

Local discriminant preservation projection embedded ensemble learning based dimensionality reduction of speech data of Parkinson's disease

Y Liu, Y Li, X Tan, P Wang, Y Zhang - Biomedical Signal Processing and …, 2021 - Elsevier
Speech has been widely used in the diagnosis of Parkinson's disease (PD). However, the
collected PD speech data has the characteristics of high data redundancy, high aliasing and …

Speech analysis for the detection of Parkinson's disease by combined use of empirical mode decomposition, Mel frequency cepstral coefficients, and the K-nearest …

N Boualoulou, B Nsiri, TB Drissi… - ITM Web of …, 2022 - itm-conferences.org
Parkinson's disease (PD) is one of the neurodegenerative diseases. The neuronal loss
caused by this disease leads to symptoms such as lack of initiative, depressive states …

Voice Biomarkers for Parkinson's Disease Prediction Using Machine Learning Models with Improved Feature Reduction Techniques

N Chintalapudi, VR Dhulipalla… - Journal of Data …, 2023 - ojs.bonviewpress.com
As a chronic and life-threatening disease, Parkinson's disease (PD) causes people to
become rigid and inactive and have shaky voices. There is an argument that current PD …

[HTML][HTML] Weighted hybrid feature reduction embedded with ensemble learning for speech data of parkinson's disease

Z Hameed, WU Rehman, W Khan, N Ullah… - Mathematics, 2021 - mdpi.com
Parkinson's disease (PD) is a progressive and long-term neurodegenerative disorder of the
central nervous system. It has been studied that 90% of the PD subjects have voice …