Computational Intelligence and Neuroscience

Ergonomic Issues in Brain-Computer Interface Technologies: Current Status, Challenges, and Future Direction

Publishing date
01 Nov 2019
Submission deadline
21 Jun 2019

Lead Editor

1Soonchunhyang University, Asan, Republic of Korea

2Korea University, Seoul, Republic of Korea

3Handong Global University, Pohang, Republic of Korea

4Wadsworth Center, Albany, USA

5University of North Carolina at Chapel Hill, Chapel Hill, USA

Ergonomic Issues in Brain-Computer Interface Technologies: Current Status, Challenges, and Future Direction


The brain-computer interface is a fast-growing technology that involves the brain to sense, analyze, and translate signals into commands for the purpose of providing a human computer interaction that will enable communication with computers and control of external devices such as robotic agents. It emerged a few decades ago, and BCI research has mainly focused on signal processing methods to increase its accuracy for its applications such as virtual keyboards, wheelchair control, or rehabilitation training. BCI is now maturing towards being more realistic and practically plausible; therefore it is time to take ergonomics (or human factors) into account as part of the BCI design process. In addition to improving BCI system performance such as accuracy, brain signal measurements should be more convenient and easier, and the BCI paradigm including audio or visual stimulation should not make the user tired.

The goal of this special issue is to bring researchers and practitioners from academia and industry together to present their vision for research and development of future user-friendly BCI technologies. We invite original research papers as well as review articles that describe current and expected challenges along with potential solutions for brain-computer interface technology.

Potential topics include but are not limited to the following:

  • New innovative BCI devices for improvement of user experience
  • Artificial intelligence and signal processing methods to improve the reliability and performance of BCI systems
  • Evaluating the ergonomics of BCI devices, paradigms, and systems
  • New BCI paradigm and stimulus methods for reducing user fatigue
  • Effective integration of BCI systems with other control functions such as muscle, eye, tongue, or speech behavior
  • Clinical and nonclinical application of BCI technologies such as rehabilitation, assistive robotics, and entertainments
  • Literature and systematic reviews on the field
Computational Intelligence and Neuroscience
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