Using virtual reality to examine the neural and physiological anxiety-related responses to balance-demanding target-reaching leaning tasks

Rachneet Kaur, Rongyi Sun, Liran Ziegelman, Richard Sowers, Manuel E. Hernandez

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

Abstract

We examine the feasibility and effectiveness of a virtual reality (VR) based experimental setup to monitor and modify the neural and physiological anxiety-related responses to balance-demanding target-reaching whole body leaning tasks. In our system, electroencephalography (EEG) and electrocardiography (EKG) signals are used to analyze the subjects' real-Time neural and cardiac activities, respectively, while subjects perform accuracy-constrained whole body movements as quickly and as accurately as possible in high fall-risk VR conditions. Salient features of neural and cardiac responses are analyzed to monitor anxiety-related changes in subjects during the performance of balance-demanding tasks. Validation of the proposed framework, integrating VR and sensor-based monitoring, may pave the way to smart and intuitive human-robot or brain-computer interface systems that can detect anxiety in human users during the performance of demanding motor tasks. The application of linear and radial basis function support vector machine classifiers suggest good performance in detecting anxiety using power of the alpha band from F3 and F4 channels of the EEG head cap. Our results suggest that frontal alpha asymmetry (FAA) may be used as bio-marker for quantifying both trait and state anxiety, and further conclude that state anxiety is correlated with motor task performance.

Original languageEnglish (US)
Title of host publication2019 IEEE-RAS 19th International Conference on Humanoid Robots, Humanoids 2019
PublisherIEEE Computer Society
Pages313-319
Number of pages7
ISBN (Electronic)9781538676301
DOIs
StatePublished - Oct 2019
Event19th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2019 - Toronto, Canada
Duration: Oct 15 2019Oct 17 2019

Publication series

NameIEEE-RAS International Conference on Humanoid Robots
Volume2019-October
ISSN (Print)2164-0572
ISSN (Electronic)2164-0580

Conference

Conference19th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2019
CountryCanada
CityToronto
Period10/15/1910/17/19

Keywords

  • Electroencephalogram
  • Heart rate variability
  • Machine learning
  • Signal processing
  • Virtual reality

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Hardware and Architecture
  • Human-Computer Interaction
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'Using virtual reality to examine the neural and physiological anxiety-related responses to balance-demanding target-reaching leaning tasks'. Together they form a unique fingerprint.

  • Cite this

    Kaur, R., Sun, R., Ziegelman, L., Sowers, R., & Hernandez, M. E. (2019). Using virtual reality to examine the neural and physiological anxiety-related responses to balance-demanding target-reaching leaning tasks. In 2019 IEEE-RAS 19th International Conference on Humanoid Robots, Humanoids 2019 (pp. 313-319). [9035020] (IEEE-RAS International Conference on Humanoid Robots; Vol. 2019-October). IEEE Computer Society. https://doi.org/10.1109/Humanoids43949.2019.9035020