Non-negative matrix factorization-based time-frequency feature extraction of voice signal for Parkinson's disease prediction

Parkinson disease prediction using intrinsic mode function based features from speech signal

(2019) Biswajit Karan et al.   Biocybernetics and Biomedical Engineering

Detecting Parkinson’s disease with sustained phonation and speech signals using machine learning techniques

(2019) Jefferson S. Almeida et al.   PATTERN RECOGNITION LETTERS

A novel octopus based Parkinson’s disease and gender recognition method using vowels

(2019) Turker Tuncer et al.   APPLIED ACOUSTICS

Principal component analysis of the spectrogram of the speech signal: Interpretation and application to dysarthric speech

(2019) Abdellah Kacha et al.   COMPUTER SPEECH AND LANGUAGE

A hybrid intelligent system for the prediction of Parkinson's Disease progression using machine learning techniques

(2018) Mehrbakhsh Nilashi et al.   Biocybernetics and Biomedical Engineering

Towards an automatic evaluation of the dysarthria level of patients with Parkinson's disease

(2018) J.C. Vásquez-Correa et al.   JOURNAL OF COMMUNICATION DISORDERS

Multimodal assessment of Parkinson's disease: a deep learning approach

(2018)   IEEE Journal of Biomedical and Health Informatics

A comparative analysis of speech signal processing algorithms for Parkinson’s disease classification and the use of the tunable Q-factor wavelet transform

(2018) C. Okan Sakar et al.   APPLIED SOFT COMPUTING

Characterizing the distribution of silent intervals in the connected speech of individuals with Parkinson disease

(2018) Jason A. Whitfield et al.   JOURNAL OF COMMUNICATION DISORDERS

Using Human Factor Cepstral Coefficient on Multiple Types of Voice Recordings for Detecting Patients with Parkinson's Disease

(2017) A. Benba et al.   IRBM

Empirical Wavelet Transform Based Features for Classification of Parkinson’s Disease Severity

(2017) Qi Wei Oung et al.   JOURNAL OF MEDICAL SYSTEMS

Discriminating Between Patients With Parkinson’s and Neurological Diseases Using Cepstral Analysis

(2016) Achraf Benba et al.   IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING

Spectral and cepstral analyses for Parkinson's disease detection in Spanish vowels and words

(2015) J. R. Orozco-Arroyave et al.   EXPERT SYSTEMS

Automatic Evaluation of Articulatory Disorders in Parkinson’s Disease

(2014) Michal Novotny et al.   IEEE-ACM Transactions on Audio Speech and Language Processing

Collection and Analysis of a Parkinson Speech Dataset With Multiple Types of Sound Recordings

(2013) B. E. Sakar et al.   IEEE Journal of Biomedical and Health Informatics

Novel Speech Signal Processing Algorithms for High-Accuracy Classification of Parkinson's Disease

(2012) A. Tsanas et al.   IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING

Time–Frequency Matrix Feature Extraction and Classification of Environmental Audio Signals

(2011) B. Ghoraani et al.   IEEE Transactions on Audio Speech and Language Processing

Quantitative acoustic measurements for characterization of speech and voice disorders in early untreated Parkinson’s disease

(2011) J. Rusz et al.   JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA

A Joint Time-Frequency and Matrix Decomposition Feature Extraction Methodology for Pathological Voice Classification

(2009) Behnaz Ghoraani et al.   EURASIP Journal on Advances in Signal Processing

Suitability of Dysphonia Measurements for Telemonitoring of Parkinson's Disease

(2008) M.A. Little et al.   IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING

Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS): Scale presentation and clinimetric testing results

(2008) Christopher G. Goetz et al.   MOVEMENT DISORDERS