Machine Learning Techniques for Parkinson’s Disease Detection using Wearables during a Timed-up-and-Go-Test

Machine Learning Techniques for Parkinson’s Disease Detection using Wearables during a Timed-up-and-Go-Test

In this paper, the classification models for Idiopathic Parkinson's syndrome (iPS) detection through timed-up-and-go test performed on iPS-patients are given. The models are based on the supervised learning. The data are extracted via Myo gesture armband worn on two hands. The corresponding mod...

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Bibliographic Details
Main Authors: Hossein Tabatabaei Seyed Amir, Pedrosa David, Eggers Carsten, Wullstein Max, Kleinholdermann Urs, Fischer Patrick, Sohrabi Keywan
Format: Article
Language:English
Published: De Gruyter 2020-09-01
Series:Current Directions in Biomedical Engineering
Subjects:
parkinson’s disease
supervised learning
convolutional neural network
classification
accuracy
Online Access:https://doi.org/10.1515/cdbme-2020-3097

Internet

https://doi.org/10.1515/cdbme-2020-3097

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