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Coding Schemes for Observational Studies of Usability in Collaborative Tangible User Interfaces Read chapter Read first chapter

2015 | OriginalPaper | Chapter

Decoding of Upper Limb Movement Using EEG and Sparse Coding

Author : Masashi Yamashita

Published in: HCI International 2015 - Posters’ Extended Abstracts

Publisher: Springer International Publishing

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Abstract

In this paper, a system is proposed for decoding upper limb movement from EEG. The signal processing procedure consists of a learning phase and test phase. In the learning phase, a Kinect sensor is utilized to measure the true values for a hand’s movement. Sparse coding is applied to calculate the weight of a linear decoding model. Because sparse coding can be used to derive the sparse weight, most of the elements are zero, with the remaining elements being non-zero. Thus, it is an effective method for reducing the calculation costs. Sparse coding was combined with noise reduction of the EEG signals to achieve good estimation for upper limb movements in the experimental results.

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Metadata
Title
Decoding of Upper Limb Movement Using EEG and Sparse Coding
Author
Masashi Yamashita
Copyright Year
2015
Publisher
Springer International Publishing
Book
HCI International 2015 - Posters’ Extended Abstracts

Print ISBN: 978-3-319-21379-8

Electronic ISBN: 978-3-319-21380-4

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-3-319-21380-4_124