A study of features of EEG signals during upper-limb motion

Yoshiaki Hayashi, Kazuo Kiguchi

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

7 Citations (Scopus)

Abstract

A sEMG signal is useful for the control of the wearable robots because its measurement is relative-easy and the joint torque can be estimated from sEMG signals of related multiple muscles. However, estimation methods of sEMG signals are not always available for all users. On the other hand, an EEG signal is one of the biological signals which might be the substitute for a sEMG signal because an EEG signal can be measured even with persons who cannot provide some sEMG signals. In general the estimation of the user's motion-intention from EEG signals is more difficult than the estimation from sEMG signals. The robot might work against the user's motion-intention when the user does not concentrate on the control of the robot and is distracted by other things. In this paper, to estimate user's motion-intention from EEG signals, the feature of EEG signals during upper-limb motion is investigated and we estimate whether or not the user moves the upper-limb.

Original languageEnglish
Title of host publicationAIM 2015 - 2015 IEEE/ASME International Conference on Advanced Intelligent Mechatronics
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages943-946
Number of pages4
ISBN (Electronic)9781467391078
DOIs
Publication statusPublished - Aug 25 2015
EventIEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2015 - Busan, Korea, Republic of
Duration: Jul 7 2015Jul 11 2015

Publication series

NameIEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM
Volume2015-August

Other

OtherIEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2015
CountryKorea, Republic of
CityBusan
Period7/7/157/11/15

Fingerprint

Electroencephalography
Robots
Muscle
Torque

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Software
  • Computer Science Applications
  • Electrical and Electronic Engineering

Cite this

Hayashi, Y., & Kiguchi, K. (2015). A study of features of EEG signals during upper-limb motion. In AIM 2015 - 2015 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (pp. 943-946). [7222660] (IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM; Vol. 2015-August). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/AIM.2015.7222660

A study of features of EEG signals during upper-limb motion. / Hayashi, Yoshiaki; Kiguchi, Kazuo.

AIM 2015 - 2015 IEEE/ASME International Conference on Advanced Intelligent Mechatronics. Institute of Electrical and Electronics Engineers Inc., 2015. p. 943-946 7222660 (IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM; Vol. 2015-August).

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

Hayashi, Y & Kiguchi, K 2015, A study of features of EEG signals during upper-limb motion. in AIM 2015 - 2015 IEEE/ASME International Conference on Advanced Intelligent Mechatronics., 7222660, IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM, vol. 2015-August, Institute of Electrical and Electronics Engineers Inc., pp. 943-946, IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2015, Busan, Korea, Republic of, 7/7/15. https://doi.org/10.1109/AIM.2015.7222660
Hayashi Y, Kiguchi K. A study of features of EEG signals during upper-limb motion. In AIM 2015 - 2015 IEEE/ASME International Conference on Advanced Intelligent Mechatronics. Institute of Electrical and Electronics Engineers Inc. 2015. p. 943-946. 7222660. (IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM). https://doi.org/10.1109/AIM.2015.7222660
Hayashi, Yoshiaki ; Kiguchi, Kazuo. / A study of features of EEG signals during upper-limb motion. AIM 2015 - 2015 IEEE/ASME International Conference on Advanced Intelligent Mechatronics. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 943-946 (IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM).
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