A Task‐Level AR‐BCI for Enhanced Interactive Experiences
ABSTRACT Augmented reality (AR) technology can provide immersive and natural interactive interfaces for brain‐computer interface (BCI) systems. The control architecture of existing AR‐BCIs is at joint‐level (JL) or action‐level (AL), which brings a huge user burden and poor interactive experiences. A task‐level (TL) BCI control method was proposed in this study to enhance interactive experiences. The TL AR‐BCI system based on steady‐state visual evoked potentials was implemented controlling a robotic arm to grab and drop blocks. The online experiment of ten subjects shows TL AR‐BCI can effectively reduce the number of control steps and stimulation time while maintaining the same performance as JL and AL AR‐BCIs. The performance of three AR‐BCIs (JL, AL, TL) was calculated (mean accuracy: 90.66%, 92.52% and 92.2%. Mean information transfer rates: 77.56, 80.06, and 82.71 bits/min. Mean numbers of control steps: 35.48, 17.32, and 13.05. Mean stimulation time: 0.97, 0.97 and 0.89 s). The results show that TL AR‐BCI can effectively reduce the number of control steps and stimulation time while maintaining the same performance as JL and AL AR‐BCIs.
Authors
- Xinzhou Xie (ORCID: https://orcid.org/0000-0001-9294-5885)
- Songyun Xie (ORCID: https://orcid.org/0000-0002-8774-7291)
- Dalu Zheng (ORCID: https://orcid.org/0009-0007-7251-1714)
- Qing Liu (ORCID: https://orcid.org/0009-0008-9320-450X)
Institutions
- Northwestern Polytechnical University (CN)
Publication Details
- Journal
- Electronics Letters
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1049/ell2.70465
- Primary Topic
- EEG and Brain-Computer Interfaces
- Type
- article
- Field-Weighted Citation Impact
- 0.00