Classification of dynamic in-hand manipulation based on SEMG and kinect

Yaxu Xue, Zhaojie Ju, Kui Xiang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Abstract

This paper proposes a hand motion capture system for recognizing dynamic in-hand manipulation of the subjects based on the famous sensing techniques, then transferring the manipulation skills into different bionic hand applications, such as prosthetic hand, animation hand, human computer interaction. By recoding the ten defined in-hand manipulations demonstrated by different subjects, the hand motion information is captured with hybrid SEMG and Kinect. Through the data preprocessing including motion segmentation and feature extraction, recognizing ten different types of hand motions based on the rich feature information are investigated by using Marquardt-Levenberg algorithm based artificial neural network, and the experimental results show the effectiveness and feasibility of this method.
Original languageEnglish
Title of host publication2018 Eighth International Conference on Information Science and Technology
Subtitle of host publicationICIST
PublisherIEEE
Pages342-346
ISBN (Electronic)978-1-5386-3782-1
ISBN (Print)978-1-5386-3783-8
DOIs
Publication statusPublished - 9 Aug 2018
Event2018 Eighth International Conference on Information Science and Technology - Cordoba, Spain
Duration: 30 Jun 20186 Jul 2018

Publication series

NameIEEE ICIST Proceedings Series
ISSN (Electronic)2573-3311

Conference

Conference2018 Eighth International Conference on Information Science and Technology
CountrySpain
Period30/06/186/07/18

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