P1‐112: A brain computer interface to detect Alzheimer's disease

Simon, Adam J.; Bernstein, Allan L.; Hess, Terry; Ashrafiuon, Hashem; Devilbiss, David M.; Verma, Ajay

doi:10.1016/j.jalz.2011.05.391

Cited by 3 publications

(1 citation statement)

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“…Traditionally, BCI technologies have been used for medical purposes, including the treatment of neurodegenerative diseases such as Alzheimer's and the autonomic nervous system [6], the detection of anomalous neural activity [7], and mental speech systems where the BCIs analyze the user's neural activity to determine each spelled letter [8]. But due to technological advancements, the application field of BCI technologies has expanded into fields other than medicine.…”

Section: Introductionmentioning

confidence: 99%

Perspective Chapter: Making Space for Neuro Rights in the Context of Brain-Computer Interfaces: One Small Step for Human Rights, One Giant Leap for Mankind

Botes

2023

New Insights in Brain-Computer Interface Systems [Working Title]

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Brain-Computer Interfaces (BCIs) are compelling technologies that allow for bidirectional communication and control between the human brain and the outside world (via a computer) by exchanging brain activity data. Although being admired for their clinical promises, they raise novel ethical and legal issues. Legal debates centre around patient autonomy, equity, data protection and security, dehumanization, machine learning-based decision-making limitations, and the influence of BCIs on human rights—and whether we need new rights to protect our neuro data and mental privacy or not. This chapter will reconsider existing rights and weigh up the argument for sui generis rights.

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Section: Introductionmentioning

confidence: 99%

Perspective Chapter: Making Space for Neuro Rights in the Context of Brain-Computer Interfaces: One Small Step for Human Rights, One Giant Leap for Mankind

Botes

2023

New Insights in Brain-Computer Interface Systems [Working Title]

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Transfer learning-based EEG analysis of visual attention and working memory on motor cortex for BCI

Kant

Laskar

Hazarika

2022

Neural Comput & Applic

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SecBrain

Beltrán

Pérez

Bernal

et al. 2022

Advances in Malware and Data-Driven Network Security

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In recent years, the growth of brain-computer interfaces (BCIs) has been remarkable in specific application fields, such as the medical sector or the entertainment industry. Most of these fields use evoked potentials, like P300, to obtain neural data able to handle prostheses or achieve greater immersion experience in videogames. The natural use of BCI involves the management of sensitive users' information as behaviors, emotions, or thoughts. In this context, new security breaches in BCI are offering cybercriminals the possibility of collecting sensitive data and affecting subjects' physical integrity, which are critical issues. For all these reasons, the fact of applying efficient cybersecurity mechanisms has become a main challenge. To improve this challenge, this chapter proposes a framework able to detect cyberattacks affecting one of the most typical scenarios of BCI, the generation of P300 through visual stimuli. A pool of experiments demonstrates the performance of the proposed framework.

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P1‐112: A brain computer interface to detect Alzheimer's disease

Cited by 3 publications

References 0 publications

Perspective Chapter: Making Space for Neuro Rights in the Context of Brain-Computer Interfaces: One Small Step for Human Rights, One Giant Leap for Mankind

Perspective Chapter: Making Space for Neuro Rights in the Context of Brain-Computer Interfaces: One Small Step for Human Rights, One Giant Leap for Mankind

Transfer learning-based EEG analysis of visual attention and working memory on motor cortex for BCI

SecBrain

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