Privacy and Brain-Computer Interfaces: method and interim findings

Wahlstrom, Kirsten; Fairweather, Ben; Ashman, Helen

doi:10.29297/orbit.v1i2.39

Cited by 3 publications

(2 citation statements)

References 14 publications

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“…BCIs were designed from the start to gather neural data and use it to control various gadgets and appliances. BCI systems can be categorized into four types based on how brain data is elicited and utilized [36]: active, reactive, passive, and hybrid. The following sections will discuss three categories within emerging BCI-HRC solutions.…”

Section: Developing Solutions For Bci-hrcmentioning

confidence: 99%

Augmented reality and brain-computer interfaces for human-robot collaboration in manufacturing contexts

Gao

Xu²

2022

International Conference on Intelligent and Human-Computer Interaction Technology (IHCIT 2022)

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The most practical methods to allow manipulators to work together in the same workspace and collaborate with humans on the same tasks are brain-computer interfaces (BCIs) and augmented reality (AR). This paper provides a theoretical introduction to AR and BCI technologies in human-robot collaboration (HRC), fully demonstrating the practicability of AR-HRC and BCI-HRC solutions in manufacturing workspaces, including key advantages and future interests. Results show that these solutions have great potential to improve the current manufacture situation and impact the future research of HRC.

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Section: Developing Solutions For Bci-hrcmentioning

confidence: 99%

Augmented reality and brain-computer interfaces for human-robot collaboration in manufacturing contexts

Gao

Xu²

2022

International Conference on Intelligent and Human-Computer Interaction Technology (IHCIT 2022)

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“…Brain-computer interfaces were inherently conceived to acquire neural data and to exploit them to control different devices and appliances. Based on the way the neural data are elicited and used, BCI systems can be classified in four typologies [62]:…”

Section: Elicitation Of Brain Signalsmentioning

confidence: 99%

An Introductory Tutorial on Brain–Computer Interfaces and Their Applications

et al. 2021

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The prospect and potentiality of interfacing minds with machines has long captured human imagination. Recent advances in biomedical engineering, computer science, and neuroscience are making brain–computer interfaces a reality, paving the way to restoring and potentially augmenting human physical and mental capabilities. Applications of brain–computer interfaces are being explored in applications as diverse as security, lie detection, alertness monitoring, gaming, education, art, and human cognition augmentation. The present tutorial aims to survey the principal features and challenges of brain–computer interfaces (such as reliable acquisition of brain signals, filtering and processing of the acquired brainwaves, ethical and legal issues related to brain–computer interface (BCI), data privacy, and performance assessment) with special emphasis to biomedical engineering and automation engineering applications. The content of this paper is aimed at students, researchers, and practitioners to glimpse the multifaceted world of brain–computer interfacing.

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Mind Your Mind

2020

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A brain-computer interface (BCI) system is a system that leverages brainwave information acquired by a designated brain monitoring device to interact with a computerized system. Over the past 40 years, many BCI applications have been developed in a variety of domains, from entertainment to medical field and even to computer security mechanisms. Until now, the development of BCI systems has focused on improving their accuracy, functionality, and ease of use, and not enough effort and attention has been invested in securing these systems and the sensitive data they acquire. In this article, we present the principles of brain activity data acquisition, with a special focus on EEG, and we present a taxonomy of BCI applications and domains. We also provide a comprehensive survey that covers eight possible attacks aimed at BCI systems. For each BCI application, we created an ecosystem and data and attack flow-diagram, which comprehensively describes the roles and interactions of the players associated with the BCI application and presents the most vulnerable vectors and components within its ecosystem; we identified gaps between existing security solutions and the presented attacks and vulnerabilities. Finally, we provide several concrete suggestions for improving the security of BCI systems in cyber-space.

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Privacy and Brain-Computer Interfaces: method and interim findings

Cited by 3 publications

References 14 publications

Augmented reality and brain-computer interfaces for human-robot collaboration in manufacturing contexts

Augmented reality and brain-computer interfaces for human-robot collaboration in manufacturing contexts

An Introductory Tutorial on Brain–Computer Interfaces and Their Applications

Mind Your Mind

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