End-to-end deep learning approach for Parkinson’s disease detection from speech signals

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

(2021) Biswajit Karan et al.   COMPUTER SPEECH AND LANGUAGE

An improved framework for Parkinson’s disease prediction using Variational Mode Decomposition-Hilbert spectrum of speech signal

(2021) Biswajit Karan et al.   Biocybernetics and Biomedical Engineering

Detection of Parkinson’s disease using automated tunable Q wavelet transform technique with EEG signals

(2021) Smith K. Khare et al.   Biocybernetics and Biomedical Engineering

Performance Evaluation of RNN with Hyperbolic Secant in Gate Structure through Application of Parkinson’s Disease Detection

(2021) Tomohiro Fujita et al.   Applied Sciences-Basel

Cognitive Determinants of Dysarthria in Parkinson's Disease: An Automated Machine Learning Approach

(2021) Adolfo M. García et al.   MOVEMENT DISORDERS

Hilbert spectrum analysis for automatic detection and evaluation of Parkinson’s speech

(2020) Biswajit Karan et al.   Biomedical Signal Processing and Control

Speech Based Estimation of Parkinson’s Disease Using Gaussian Processes and Automatic Relevance Determination

(2020) Vladimir Despotovic et al.   NEUROCOMPUTING

Multi-Variate vocal data analysis for Detection of Parkinson disease using Deep Learning

(2020) Gayathri Nagasubramanian et al.   NEURAL COMPUTING & APPLICATIONS

Parkinson disease detection using energy direction features based on EMD from voice signal

(2020) Tao Zhang et al.   Biocybernetics and Biomedical Engineering

Deep learning for time series classification: a review

(2019) Hassan Ismail Fawaz et al.   DATA MINING AND KNOWLEDGE DISCOVERY

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

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

Automated detection of Parkinson's disease using minimum average maximum tree and singular value decomposition method with vowels

(2019) Turker Tuncer et al.   Biocybernetics and Biomedical Engineering

NeuroSpeech: An open-source software for Parkinson's speech analysis

(2018) Juan Rafael Orozco-Arroyave et al.   DIGITAL SIGNAL PROCESSING

Feature-driven machine learning to improve early diagnosis of Parkinson's disease

(2018) Luca Parisi et al.   EXPERT SYSTEMS WITH APPLICATIONS

Communication impairment in Parkinson’s disease: Impact of motor and cognitive symptoms on speech and language

(2018) Kara M. Smith et al.   BRAIN AND LANGUAGE

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

(2018)   IEEE Journal of Biomedical and Health Informatics

The Emerging Evidence of the Parkinson Pandemic

(2018) E. Ray Dorsey et al.   Journal of Parkinsons Disease

Convolutional neural networks for time series classification

(2017) Bendong Zhao et al.   Journal of Systems Engineering and Electronics

Contribution of language studies to the understanding of cognitive impairment and its progression over time in Parkinson’s disease

(2017) Noémie Auclair-Ouellet et al.   NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS

Detecting Parkinson’s disease from sustained phonation and speech signals

(2017) Evaldas Vaiciukynas et al.   PLoS One

Exploiting multi-channels deep convolutional neural networks for multivariate time series classification

(2015) Yi Zheng et al.   Frontiers of Computer Science

Characterization Methods for the Detection of Multiple Voice Disorders: Neurological, Functional, and Laryngeal Diseases

(2015) Juan Rafael Orozco-Arroyave et al.   IEEE Journal of Biomedical and Health Informatics

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