Linear and Non-linear Dimensionality-Reduction Techniques on Full Hand Kinematics

Linear and Non-linear Dimensionality-Reduction Techniques on Full Hand Kinematics

The purpose of this study was to find a parsimonious representation of hand kinematics data that could facilitate prosthetic hand control. Principal Component Analysis (PCA) and a non-linear Autoencoder Network (nAEN) were compared in their effectiveness at capturing the essential characteristics of...

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Bibliographic Details
Main Authors: Alexandra A. Portnova-Fahreeva, Fabio Rizzoglio, Ilana Nisky, Maura Casadio, Ferdinando A. Mussa-Ivaldi, Eric Rombokas
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-05-01
Series:Frontiers in Bioengineering and Biotechnology
Subjects:
kinematics
neural networks
principal component analysis
dimensionality reduction
unsupervised learning
prosthetics
Online Access:https://www.frontiersin.org/article/10.3389/fbioe.2020.00429/full

Internet

https://www.frontiersin.org/article/10.3389/fbioe.2020.00429/full

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