Characterization and classification of Parkinson’s disease patients based on symbolic dynamics analysis of heart rate variability-Reference-Cited by-同舟云学术

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Characterization and classification of Parkinson’s disease patients based on symbolic dynamics analysis of heart rate variability

Published:2022-01 Issue: Volume:71 Page:103064
ISSN:1746-8094
Container-title:Biomedical Signal Processing and Control
language:en
Short-container-title:Biomedical Signal Processing and Control

Author:

Dorantes-Méndez Guadalupe,Mendez Martin O.,Méndez-Magdaleno Laura E.,Muñoz-Mata Brenda G.,Rodríguez-Leyva Ildefonso,Mejía-Rodríguez Aldo R.

Funder

Consejo Nacional de Ciencia y Tecnología

Publisher

Elsevier BV

Subject

Health Informatics,Signal Processing

Reference53 articles.

1. Neuropathology of parkinson disease;Dickson;Parkinsonism Relat. Disord.,2018

2. Alpha-synuclein in parkinson’s disease: From pathogenetic dysfunction to potential clinical application;Xu;Parkinsons Dis.,2016

3. Stages in the development of parkinson’s disease-related pathology;Braak;Cell Tissue Res.,2004

4. Parkinson’s disease;Kalia;The Lancet,2015

5. Parkinson’s disease: a review;Beitz;Front. Biosci.,2014

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1. Combining blood pressure variability and heart rate variability to analyze the autonomic nervous function of rotenone induced Parkinson’s rat model;Journal of Neuroscience Methods;2024-09

2. Heart Rate Measurement Using the Built-In Triaxial Accelerometer from a Commercial Digital Writing Device;Sensors;2024-03-31

3. A new hybrid approach based on AOA, CNN and feature fusion that can automatically diagnose Parkinson's disease from sound signals: PDD-AOA-CNN;Signal, Image and Video Processing;2023-11-01

4. A wavelet leaders model with multiscale entropy measures for diagnosing arrhythmia and congestive heart failure;Healthcare Analytics;2023-11

5. Parkinson’s disease and cleft lip and palate of pathological speech diagnosis using deep convolutional neural networks evolved by IPWOA;Applied Acoustics;2022-10

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