A Cluster Analysis for Parkinson's Disease Phenotyping with Gait Parameters-Reference-Cited by-同舟云学术

A Cluster Analysis for Parkinson's Disease Phenotyping with Gait Parameters

Published:2023-10-25 Issue: Volume:951 Page:882-887
ISSN:
Container-title:2023 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE)
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Author:

Russo Michela¹,Ricciardi Carlo¹,Amboni Marianna²,Volzone Antonio³,Barone Paolo²,Romano Maria¹,Francesco Amato¹

Affiliation:

1. University of Naples Federico II,Department of Electrical Engineering and Information Technologies,Naples,Italy,80125

2. University of Salerno,Department of Medicine, Surgery and Dentistry “Scuola Medica Salernitana ”,Baronissi,Sa,Italy,84081

3. University of Salerno,Center for Neurodegenerative Diseases (CEMAND),Department of Medicine, Surgery and Dentistry “Scuola Medica Salernitana ”,Baronissi,SA,Italy,84081

Funder

University of Salerno

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10405419/10405547/10405572.pdf?arnumber=10405572

Reference46 articles.

1. Parkinson's disease

2. Non-motor symptoms in Parkinson’s disease

3. The clinical heterogeneity of Parkinson's disease and its therapeutic implications

4. Comparing postural instability and gait disorder and akinetic‐rigid subtyping of Parkinson disease and their stability over time

5. Postural Instability in Patients with Parkinson’s Disease

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1. The Role of Deep Learning and Gait Analysis in Parkinson’s Disease: A Systematic Review;Sensors;2024-09-13