Developing stimulus presentation on mobile devices for a truly portable SSVEP-based BCI

@article{Wang2013DevelopingSP,
  title={Developing stimulus presentation on mobile devices for a truly portable SSVEP-based BCI},
  author={Yu-Te Wang and Yijun Wang and Chung-Kuan Cheng and Tzyy-Ping Jung},
  journal={2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)},
  year={2013},
  pages={5271-5274}
}
  • Yu-Te Wang, Yijun Wang, T. Jung
  • Published 3 July 2013
  • Computer Science
  • 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
This study integrates visual stimulus presentation and near real-time data processing on a mobile device (e.g. a Tablet or a cell-phone) to implement a steady-state visual evoked potentials (SSVEP)-based brain-computer interface (BCI). The goal of this study is to increase the practicability, portability and ubiquity of an SSVEP-based BCI for daily use. The accuracy of flickering frequencies on the mobile SSVEP BCI system was tested against that on a laptop/desktop used in our previous studies… 

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References

SHOWING 1-10 OF 14 REFERENCES

A cell-phone-based brain–computer interface for communication in daily life

This study implemented and tested online signal processing methods in both time and frequency domains for detecting SSVEPs and showed that the performance of the proposed cell-phone-based platform was comparable with other BCI systems using bulky commercial EEG systems and personal computers.

Design and implementation of a brain-computer interface with high transfer rates

A brain-computer interface that can help users to input phone numbers based on the steady-state visual evoked potential (SSVEP), which has noninvasive signal recording, little training required for use, and high information transfer rate.

Development of a Low-Cost FPGA-Based SSVEP BCI Multimedia Control System

Experimental results show that the subjects' SSVEP can successfully control the multimedia device through the proposed BCI system with high identification accuracy, and implementing a prototype of the SSVEp-based BCI multimedia control system verifies the effectiveness of the proposed system.

Visual spatial attention tracking using high-density SSVEP data for independent brain-computer communication

Strong evidence is presented suggesting that the SSVEP can be used as an electrophysiological correlate of visual spatial attention that may be harnessed on its own or in conjunction with other correlates to achieve control in an independent BCI.

An online multi-channel SSVEP-based brain–computer interface using a canonical correlation analysis method

An online multi-channel SSVEP-based BCI system using a canonical correlation analysis (CCA) method for extraction of frequency information associated with theSSVEP, showing that channel selection and parameter optimization are not required, the possible use of harmonic frequencies, low user variation and easy setup.

Practical Designs of Brain–Computer Interfaces Based on the Modulation of EEG Rhythms

Electroencephalogram (EEG) is the main interest due to its advantages of low cost, convenient operation and non-invasiveness, and these systems offer some practical solutions for patients with motor disabilities.

A BCI-based environmental controller for the motion-disabled

An environmental controller using a BCI technique based on steady-state visual evoked potential composed of a stimulator, a digital signal processor, and a trainable infrared remote-controller that has been applied to the control of an electric apparatus successfully.

Visual stimulus design for high-rate SSVEP BCI

A new approach to realise computer monitor flickers that can be used to elicit steady-state visual evoked potentials (SSVEP) at a flexible frequency is proposed. An SSVEP-based brain-computer

Brain-computer interface based on the high-frequency steady-state visual evoked potential

The signal-to-noise ratio versus frequency curve suggests that the high-frequency SSVEP (>20Hz) could help to construct a practical BCI system.

Steady-state visual evoked potentials to computer monitor flicker.