A Graded Assessment System for Parkinson’s Upper-Limb Bradykinesia Based on a Temporal Convolutional Network Model-Reference-Cited by-同舟云学术

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A Graded Assessment System for Parkinson’s Upper-Limb Bradykinesia Based on a Temporal Convolutional Network Model

Published:2023-12-01 Issue:23 Volume:23 Page:29283-29292
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Tong Lina¹^ORCID,Liu Dai-Song¹,Peng Liang²^ORCID,Hao Hong-Lin³,Wang Chen²^ORCID

Affiliation:

1. School of Mechanical Electronic and Information Engineering, Chinese University of Mining and Technology-Beijing, Beijing, China

2. State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China

3. Department of Neurology, Peking Union Medical College Hospital, Beijing, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Beijing Natural Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/7361/10336249/10292564.pdf?arnumber=10292564

Reference47 articles.

1. Evaluation for Parkinsonian Bradykinesia by deep learning modeling of kinematic parameters

2. A Mobile Application for a Daily Assessment of Forearm Pronation and Supination Motor Activities as an Early Diagnostic Tool of Parkinson's Disease

3. Wearable sensors during drawing tasks to measure the severity of essential tremor

4. Parkinson’s disease severity estimation using deep learning and cloud technology;channa;Proc IEEE Int Conf Omni-Layer Intell Syst (COINS),2022

5. Validation of Inertial Sensing-Based Wearable Device for Tremor and Bradykinesia Quantification

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