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Soft Computing

, Volume 23, Issue 21, pp 11199–11215 | Cite as

Indoor space target searching based on EEG and EOG for UAV

  • Tianwei ShiEmail author
  • Hong Wang
  • Wenhua Cui
  • Ling Ren
Methodologies and Application
  • 64 Downloads

Abstract

This paper puts forward a noninvasive electrooculography (EOG) and electroencephalogram (EEG)-based hybrid computer interface (HCI) system to implement the indoor target searching in three-dimensional (3D) space for a low-speed multi-rotor aircraft. The HCI system mainly consists of three subsystems, including the interface switching, decision and semi-autonomous navigation. The interface switching subsystem is accomplished by detecting the eyeblink EOG. The continuous wavelet transform is employed to indentify eyeblink features which are used to switch interfaces between horizontal and vertical motor imagery (MI) tasks. The average accuracy of the eyeblink feature detection reaches to 97.95%. The decision subsystem employs the joint regression (JR) model and spectral powers methods to extract the time and frequency domain features of MI tasks by analyzing the left- and right-hand MI EEG. Simultaneously, the support vector machine is applied to accomplish the MI tasks classification and final decision. The average classification accuracy of the HCI system reaches to 93.99%. The semi-autonomous navigation subsystem extracts the environmental features to avoid obstacles semi-automatically in 3D space and provide feasible directions for the decision subsystem. The actual indoor 3D space target searching experiments are put forward to verify the feasibility and adaptation performances of this proposed HCI system.

Keywords

Electrooculography Electroencephalogram Motor imagery Continuous wavelet transform Joint regression model Spectral powers Support vector machine 

Notes

Acknowledgements

Tianwei Shi has been supported by the Department of Education of Liaoning Province (2017FWDF03), Natural Science Foundation of Liaoning Province of China (20180550567) and University of Science and Technology Liaoning Youth Fund (2017QN05). Wenhua Cui has been supported by the Department of Education of Liaoning Province (2016HZZD05).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Human and animal rights

This article contains the calibration experiments and actual indoor 3D space target searching experiments with human participants performed by the authors. Five males and five females participated in the experiments. This study was approved by the Human Research Protections Program of University of Science and Technology Liaoning and Northeastern University. Simultaneously, it was performed in accordance with the Declaration of Helsinki. All participants were asked to read and sign an informed consent form before participating in the study.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of International Finance and BankingUniversity of Science and Technology LiaoningAnshanChina
  2. 2.Department of Mechanical Engineering and AutomationNortheastern UniversityShenyangChina
  3. 3.Research and Development CenterLiaoning Systemteq Information Technology Co., Ltd.AnshanChina

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