Foundations and Trends® in Human-Computer Interaction > Vol 13 > Issue 4

Improving HCI with Brain Input: Review, Trends, and Outlook

Erin T. Solovey, Worcester Polytechnic Institute, USA, esolovey@wpi.edu , Felix Putze, University of Bremen, Germany, felix.putze@uni-bremen.de
 
Suggested Citation
Erin T. Solovey and Felix Putze (2021), "Improving HCI with Brain Input: Review, Trends, and Outlook", Foundations and Trends® in Human-Computer Interaction: Vol. 13: No. 4, pp 298-379. http://dx.doi.org/10.1561/1100000078

Publication Date: 29 Apr 2021
© 2021 Erin T. Solovey and Felix Putze
 
Subjects
Multimodal Interaction,  Technology: Input technologies,  Sensor-based or tangible interaction
 

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In this article:
1. Introduction
2. Foundations and Broader Context
3. Human–Computer Interaction Application Domains
4. Brain Input Paradigms in HCI
5. Cognitive/Neural States and Processes
6. Brain Sensing Technology
7. Architecture and Development Tools
8. Evaluation Methods, Generalizability, and Reproducibility
9. Research Directions
10. Conclusions
Acknowledgements
References

Abstract

In the field of HCI, researchers from diverse backgrounds have taken a broad view of application domains that could benefit from brain signals, both by applying HCI methods to improve interfaces using brain signals (e.g., human-centered design and evaluation of brain-based user interfaces), as well as integrating brain signals into HCI methods (e.g., using brain metrics in user experience evaluation). Recent advances in brain sensing technologies, new analysis methods, and hardware improvements have opened the door for such research, which will accelerate with the increased commercialization of wearable technology containing brain sensors. In this monograph, we examine brain signals from an HCI perspective, focusing on work that makes an HCI-related contribution. We pursue three main goals. First, we give a primer for HCI researchers on the necessary technology, the possibilities, and limitations for using brain signals in user interfaces. Second, we systematically map out the research field by constructing a taxonomy of applications, input paradigms, and interface designs. For this purpose, we reviewed more than 100 publications in major HCI conferences and journals. Finally, we identify gaps and areas of emerging work to lay a foundation for future research on HCI for and with brain signals.

DOI:10.1561/1100000078
ISBN: 978-1-68083-814-5
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Table of contents:
1. Introduction
2. Foundations and Broader Context
3. Human–Computer Interaction Application Domains
4. Brain Input Paradigms in HCI
5. Cognitive/Neural States and Processes
6. Brain Sensing Technology
7. Architecture and Development Tools
8. Evaluation Methods, Generalizability, and Reproducibility
9. Research Directions
10. Conclusions
Acknowledgements
References

Improving HCI with Brain Input: Review, Trends, and Outlook

As long as there have been computers, there has been a desire to integrate one’s thoughts directly with them. As the technology progressively comes into contact with human users, new challenges and opportunities arise that are central to human-computer interaction (HCI). In the field of HCI, researchers from diverse backgrounds have taken a broad view of application domains that could benefit from brain signals, both by applying HCI methods to improve interfaces using brain signals and integrating brain signals into HCI methods. Recent advances in brain sensing technologies, new analysis methods, and hardware improvements have opened the door for such research, which will accelerate with the increased commercialization of wearable technology containing brain sensors.

In this monograph, the authors examine brain signals from an HCI perspective, focusing on work that makes an HCI-related contribution. They pursue three main goals: (1) give a primer for HCI researchers on the necessary technology, possibilities, and limitations for using brain signals in user interfaces; (2) systematically map out the research field by constructing a taxonomy of applications, input paradigms, and interface designs; and (3) identify gaps and areas of emerging work to lay a foundation for future research on HCI for and with brain signals.

 
HCI-078