Electroencephalography

Shahriari, Yalda; Besio, Walter G.; Hosni, Sarah Ismail; Zisk, Alyssa Hillary; Borgheai, Seyyed Bahram; Deligani, Roohollah Jafari; McLinden, John

doi:10.1007/978-3-030-41854-0_1

Cited by 2 publications

(9 citation statements)

References 30 publications

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“…This class of paradigms typically requires a large extent of individual training but do not depend on external stimuli. EEG sensors employed for MI paradigms need to be typically positioned in correspondence to the motor cortex, over scalp locations across the top of the head, specifically C3, C4, and Cz of the international 10-20 system, as in figure 2(A) [12]. (A) shows a representation of the international 10-20 international system [12].…”

Section: Bci Systems and Common Paradigmsmentioning

confidence: 99%

“…EEG sensors employed for MI paradigms need to be typically positioned in correspondence to the motor cortex, over scalp locations across the top of the head, specifically C3, C4, and Cz of the international 10-20 system, as in figure 2(A) [12]. (A) shows a representation of the international 10-20 international system [12]. The necessary electrode locations for BCIs are related to the chosen paradigm.…”

Section: Bci Systems and Common Paradigmsmentioning

confidence: 99%

“…C3, C4, and Cz are used for motor imagery paradigms, while visual paradigms need recording of occipital areas, in correspondence to the visual cortex. Reproduced from [12], with permission from Springer Nature. The schematic in (B) represents the typical components of an ERP response.…”

Section: Bci Systems and Common Paradigmsmentioning

confidence: 99%

“…While scalp EEG records the post-synaptic summation of synchronous activity (oscillations) of thousands to millions of neurons, iEEG readings include local field potentials (LFPs) down to multi-unit and single-unit biopotentials [12]. LFPs are relatively slow electrical changes in brain activity typically found at low frequencies, akin to the oscillations recorded by scalp EEG, but corresponding to a much smaller neuronal population [21].…”

Section: Intracranial Versus Scalp Eegmentioning

confidence: 99%

“…EEG sensors and EEG helmet systems are thus required to have a low intrinsic SNR [44]. The brain itself can be another source of artefacts, which often can be eliminated by band-pass filtering [12]. Environmental noise can be mitigated by using active sensors, i.e.…”

Section: Sensors For Scalp Eeg: Requirements and Evolutionmentioning

confidence: 99%

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A perspective on electroencephalography sensors for brain-computer interfaces

Iacopi

Lin²

2022

Prog. Biomed. Eng.

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This Perspective offers a concise overview of the current state-of-the-art of neural sensors for brain-machine interfaces, with particular attention towards brain-controlled robotics. We first describe current approaches, decoding models and associated choice of common paradigms, and their relation to the position and requirements of the neural sensors. While implanted intracortical sensors offer unparalleled spatial, temporal and frequency resolution, the risks related to surgery and post-surgery complications pose a significant barrier to deployment beyond severely disabled individuals. For less critical and larger scale applications, we emphasize the need to further develop dry scalp electroencephalography (EEG) sensors as non-invasive probes with high sensitivity, accuracy, comfort and robustness for prolonged and repeated use. In particular, as many of the employed paradigms require placing EEG sensors in hairy areas of the scalp, ensuring the aforementioned requirements becomes particularly challenging. Nevertheless, neural sensing technologies in this area are accelerating, also thanks to the advancement of miniaturised technologies and the engineering of novel biocompatible nanomaterials. The development of novel multifunctional nanomaterials is also expected to enable the integration of redundancy by probing the same type of information through different mechanisms for increased accuracy, as well as the integration of complementary and synergetic functions that could range from the monitoring of physiological states to incorporating optical imaging.

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Section: Bci Systems and Common Paradigmsmentioning

confidence: 99%

Section: Bci Systems and Common Paradigmsmentioning

confidence: 99%

Section: Bci Systems and Common Paradigmsmentioning

confidence: 99%

Section: Intracranial Versus Scalp Eegmentioning

confidence: 99%

Section: Sensors For Scalp Eeg: Requirements and Evolutionmentioning

confidence: 99%

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A perspective on electroencephalography sensors for brain-computer interfaces

Iacopi

Lin²

2022

Prog. Biomed. Eng.

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Summary of over Fifty Years with Brain-Computer Interfaces—A Review

et al. 2021

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Over the last few decades, the Brain-Computer Interfaces have been gradually making their way to the epicenter of scientific interest. Many scientists from all around the world have contributed to the state of the art in this scientific domain by developing numerous tools and methods for brain signal acquisition and processing. Such a spectacular progress would not be achievable without accompanying technological development to equip the researchers with the proper devices providing what is absolutely necessary for any kind of discovery as the core of every analysis: the data reflecting the brain activity. The common effort has resulted in pushing the whole domain to the point where the communication between a human being and the external world through BCI interfaces is no longer science fiction but nowadays reality. In this work we present the most relevant aspects of the BCIs and all the milestones that have been made over nearly 50-year history of this research domain. We mention people who were pioneers in this area as well as we highlight all the technological and methodological advances that have transformed something available and understandable by a very few into something that has a potential to be a breathtaking change for so many. Aiming to fully understand how the human brain works is a very ambitious goal and it will surely take time to succeed. However, even that fraction of what has already been determined is sufficient e.g., to allow impaired people to regain control on their lives and significantly improve its quality. The more is discovered in this domain, the more benefit for all of us this can potentially bring.

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Electroencephalography

Cited by 2 publications

References 30 publications

A perspective on electroencephalography sensors for brain-computer interfaces

A perspective on electroencephalography sensors for brain-computer interfaces

Summary of over Fifty Years with Brain-Computer Interfaces—A Review

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