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EEG correlates of motor control difficulty in physical human-robot interaction: A frequency domain analysis

  • SUNY Buffalo

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

15 Scopus citations

Abstract

This study investigates the relationship between electroencephalogram (EEG) activity and motor control difficulty during physical interaction with an admittance controlled robot. Subjects performed a fine cooperative manipulation task, in which the motor control difficulty was manipulated by altering admittance dynamics. To quantify motor control difficulty, an interaction instability index is proposed based on the spectral information of interaction forces. Regression analysis is then performed to construct a model to estimate motor control difficulty from EEG spectral features. The results indicate the reliability of EEG signals as an indicator of motor control difficulty in pHRI.

Original languageEnglish
Title of host publicationIEEE Haptics Symposium, HAPTICS 2018 - Proceedings
EditorsYon Visell, Katherine J. Kuchenbecker, Gregory J. Gerling
PublisherIEEE Computer Society
Pages229-234
Number of pages6
ISBN (Electronic)9781538654248
DOIs
StatePublished - May 9 2018
Event2018 IEEE Haptics Symposium, HAPTICS 2018 - San Francisco, United States
Duration: Mar 25 2018Mar 28 2018

Publication series

NameIEEE Haptics Symposium, HAPTICS
Volume2018-March
ISSN (Print)2324-7347
ISSN (Electronic)2324-7355

Conference

Conference2018 IEEE Haptics Symposium, HAPTICS 2018
Country/TerritoryUnited States
CitySan Francisco
Period03/25/1803/28/18

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