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

2021 ◽  
Vol 11 (1) ◽  
pp. 43
Author(s):  
Aleksandra Kawala-Sterniuk ◽  
Natalia Browarska ◽  
Amir Al-Bakri ◽  
Mariusz Pelc ◽  
Jaroslaw Zygarlicki ◽  
...  
Keyword(s):  
Science Fiction ◽  
Technological Development ◽  
Brain Activity ◽  
Signal Acquisition ◽  
Brain Computer Interfaces ◽  
Computer Interfaces ◽  
History Of ◽  
Common Effort ◽  
Signal Acquisition And Processing ◽  
The Brain

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.

Automated System for Epileptic Seizures Prediction based on Multi-Channel Recordings of Electrical Brain Activity

2018 ◽  
pp. 115-122 ◽  
Author(s):  
V. A. Maksimenko ◽  
A. A. Harchenko ◽  
A. Lüttjohann
Keyword(s):  
Epileptic Seizure ◽  
Brain Activity ◽  
Epileptic Seizures ◽  
Automated System ◽  
Brain Computer Interfaces ◽  
Electrical Brain Activity ◽  
Computer Interfaces ◽  
Prediction And Prevention ◽  
The Brain

Introduction: Now the great interest in studying the brain activity based on detection of oscillatory patterns on the recorded data of electrical neuronal activity (electroencephalograms) is associated with the possibility of developing brain-computer interfaces. Braincomputer interfaces are based on the real-time detection of characteristic patterns on electroencephalograms and their transformation  into commands for controlling external devices. One of the important areas of the brain-computer interfaces application is the control of the pathological activity of the brain. This is in demand for epilepsy patients, who do not respond to drug treatment.Purpose: A technique for detecting the characteristic patterns of neural activity preceding the occurrence of epileptic seizures.Results:Using multi-channel electroencephalograms, we consider the dynamics of thalamo-cortical brain network, preceded the occurrence of an epileptic seizure. We have developed technique which allows to predict the occurrence of an epileptic seizure. The technique has been implemented in a brain-computer interface, which has been tested in-vivo on the animal model of absence epilepsy.Practical relevance:The results of our study demonstrate the possibility of epileptic seizures prediction based on multichannel electroencephalograms. The obtained results can be used in the development of neurointerfaces for the prediction and prevention of seizures of various types of epilepsy in humans. 

scholarly journals Anytime collaborative brain–computer interfaces for enhancing perceptual group decision-making

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Saugat Bhattacharyya ◽  
Davide Valeriani ◽  
Caterina Cinel ◽  
Luca Citi ◽  
Riccardo Poli
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Brain Activity ◽  
Event Related Potentials ◽  
Brain Computer Interfaces ◽  
Appearance Time ◽  
Perceptual Group ◽  
Computer Interfaces ◽  
Related Potentials

AbstractIn this paper we present, and test in two realistic environments, collaborative Brain-Computer Interfaces (cBCIs) that can significantly increase both the speed and the accuracy of perceptual group decision-making. The key distinguishing features of this work are: (1) our cBCIs combine behavioural, physiological and neural data in such a way as to be able to provide a group decision at any time after the quickest team member casts their vote, but the quality of a cBCI-assisted decision improves monotonically the longer the group decision can wait; (2) we apply our cBCIs to two realistic scenarios of military relevance (patrolling a dark corridor and manning an outpost at night where users need to identify any unidentified characters that appear) in which decisions are based on information conveyed through video feeds; and (3) our cBCIs exploit Event-Related Potentials (ERPs) elicited in brain activity by the appearance of potential threats but, uniquely, the appearance time is estimated automatically by the system (rather than being unrealistically provided to it). As a result of these elements, in the two test environments, groups assisted by our cBCIs make both more accurate and faster decisions than when individual decisions are integrated in more traditional manners.

scholarly journals Counterfactuality as a Polyphonic Assemblage. Entangled Human and Nonhuman Stories of Early Modern Sciences in Neal Stephenson’s The Baroque Cycle

2018 ◽  
Vol 14 (1) ◽  
pp. 110-121
Author(s):  
Mateusz Chaberski
Keyword(s):  
Science Fiction ◽  
Technological Development ◽  
Vital Role ◽  
Multispecies Ethnography ◽  
The Past ◽  
Political Effects ◽  
Neal Stephenson ◽  
History Of ◽  
Ways Of Being ◽  
Point Of Departure

Summary In recent science-fiction literature, we can witness a proliferation of new counterfactual narratives which take the 17th century as their point of departure. Unlike steampunk narratives, however, their aim is not to criticise the socio-political effects caused by contemporary technological development. Such authors as Neal Stephenson or Ian Tregillis, among others, are interested in revisiting the model of development in Western societies, routing around the logic of progress. Moreover, they demonstrate that modernity is but an effect of manifold contingent and indeterminate encounters of humans and nonhumans and their distinct temporalities. Even the slightest modification of their ways of being could have changed Western societies and cultures. Thus, they necessitate a rather non-anthropocentric model of counterfactuality which is not tantamount to the traditional alternative histories which depart from official narratives of the past. By drawing on contemporary multispecies ethnography, I put forward a new understanding of counter-factuality which aims to reveal multiple entangled human and nonhuman stories already embedded in the seemingly unified history of the West. In this context, the concept of “polyphonic assemblage” (Lowenhaupt-Tsing) is employed to conceptualize the contingent and open-ended encounters of human and nonhuman historical actors which cut across different discourses and practices. I analyse Stephenson’s The Baroque Cycle to show the entangled stories of humans and nonhumans in 17th century sciences, hardly present in traditional historiographies. In particular, Stephenson’s depiction of quicksilver and coffeehouse as nonhuman historical actors is scrutinized to show their vital role in the production of knowledge at the dawn of modernity.

scholarly journals The current state of electrocorticography-based brain–computer interfaces

2020 ◽  
Vol 49 (1) ◽  
pp. E2 ◽  
Author(s):  
Kai J. Miller ◽  
Dora Hermes ◽  
Nathan P. Staff
Keyword(s):  
Functional Limitations ◽  
Brain Computer Interfaces ◽  
Brain Surface ◽  
Computer Interfaces ◽  
Brain Signals ◽  
Current State ◽  
Temporal And Spatial ◽  
Direct Feedback ◽  
The Brain ◽  
Lateral Sclerosis

Brain–computer interfaces (BCIs) provide a way for the brain to interface directly with a computer. Many different brain signals can be used to control a device, varying in ease of recording, reliability, stability, temporal and spatial resolution, and noise. Electrocorticography (ECoG) electrodes provide a highly reliable signal from the human brain surface, and these signals have been used to decode movements, vision, and speech. ECoG-based BCIs are being developed to provide increased options for treatment and assistive devices for patients who have functional limitations. Decoding ECoG signals in real time provides direct feedback to the patient and can be used to control a cursor on a computer or an exoskeleton. In this review, the authors describe the current state of ECoG-based BCIs that are approaching clinical viability for restoring lost communication and motor function in patients with amyotrophic lateral sclerosis or tetraplegia. These studies provide a proof of principle and the possibility that ECoG-based BCI technology may also be useful in the future for assisting in the cortical rehabilitation of patients who have suffered a stroke.

The Effect of Crystal Dependence on Brain Activity Related to the Perception of Pleasure Using fMRI

2021 ◽  
Vol 8 (3) ◽  
Author(s):  
Ali Yoonessi ◽  
Seyed Amir Hossein Batouli ◽  
Iman Ahmadnezhad ◽  
Hamid Soltanian-zadeh
Keyword(s):  
Case Control Study ◽  
Brain Activity ◽  
Economic Status ◽  
Smoking History ◽  
Control Group ◽  
Human Society ◽  
Significant Difference ◽  
History Of ◽  
The Brain ◽  
Control Study

Background: Addiction is currently one of the problems of human society. Drug abuse is one of the most important issues in the field of addiction. Methamphetamine (crystal) is one of the drugs that has been abused in recent decades. Methods: In this case-control study, 10 individuals aged 20 to 40 years old with at least 2 years of experience of methamphetamine consumption without any history of drug use or other stimulants from clients and drug withdrawal centers in Tehran City, and 10 healthy volunteers were selected. Age, social status, and economic status of addicts were included in the fMRI apparatus, and 90 selected pleasurable, non-pleasurable, and neutral images (IAPS) were displayed by the projector through an event-related method. The playback time of each photo was 3 s, and after this process, the person outside the device, without the time limit selected the enjoyable and unpleasant images. Results: The results showed that there was no significant difference between the groups in terms of age, alcohol use, and smoking history (P < 0.05). There was no significant difference in terms of the age at first use between members of the methamphetamine-dependent group. Also, the methamphetamine-dependent group showed more brain activity in their pre-center and post-center gyrus than the normal (control) group. Conclusions: According to the results obtained in this study, in general, it can be concluded that there are some areas in the brain of addicts that are activated when watching pleasant photos, while these areas are not active in the brains of normal people.

scholarly journals Brain–Computer Interfaces for Human Augmentation

2019 ◽  
Vol 9 (2) ◽  
pp. 22 ◽  
Author(s):  
Davide Valeriani ◽  
Caterina Cinel ◽  
Riccardo Poli
Keyword(s):  
Brain Activity ◽  
Severe Disabilities ◽  
Assistive Technologies ◽  
Brain Computer Interfaces ◽  
Computer Interfaces ◽  
Control Signals ◽  
Human Augmentation

The field of brain–computer interfaces (BCIs) has grown rapidly in the last few decades, allowing the development of ever faster and more reliable assistive technologies for converting brain activity into control signals for external devices for people with severe disabilities [...]

scholarly journals Brain-Computer Interfaces for Internet of Things

Proceedings ◽  
2018 ◽  
Vol 2 (18) ◽  
pp. 1179 ◽  
Author(s):  
Francisco Laport ◽  
Francisco J. Vazquez-Araujo ◽  
Paula M. Castro ◽  
Adriana Dapena
Keyword(s):  
Internet Of Things ◽  
Communication Protocol ◽  
Brain Activity ◽  
Brain Computer Interface ◽  
Computer Interface ◽  
Event Classification ◽  
Computer Interfaces ◽  
Controlling Elements ◽  
Artefact Reduction ◽  
The Brain

A brain-computer interface for controlling elements commonly used at home is presented in this paper. It includes the electroencephalography device needed to acquire signals associated to the brain activity, the algorithms for artefact reduction and event classification, and the communication protocol.

Research on Signal Acquisition Based on Wireless Sensor for Foot Compressive Characteristics on Basketball Movement

2013 ◽  
Vol 483 ◽  
pp. 401-404
Author(s):  
Jiu Hui Wang ◽  
Qiang Ji
Keyword(s):  
Mechanical Characteristics ◽  
Brain Activity ◽  
Wireless Sensor ◽  
Experimental Result ◽  
Basketball Player ◽  
Signal Acquisition ◽  
Digital Memory ◽  
Memory Card ◽  
And Storage ◽  
The Brain

The signal acquisition system (SAS) operated by battery is designed in this paper. SAS includes signal acquisition and statistics function based on movement joints of basketball player. SAS is a recording of the electrical activity of the brain and pulse from the scalp and the recorded waveforms provide insights into the dynamic aspects of brain activity. The amplified SAS signals are digitized by an A/D converter. The digitized signal is transmitted to PC by a wireless serial port or stored in secure digital memory card. Experimental result shows that the system could implement the acquisition and storage of the foot compressive mechanical characteristics signals efficiently. This system would be of benefit to all involved in the use of SAS for sports training.

Learning from brain control: clinical application of brain–computer interfaces

e-Neuroforum ◽  
2015 ◽  
Vol 21 (4) ◽  
Author(s):  
Niels Birbaumer ◽  
Ujwal Chaudhary
Keyword(s):  
Clinical Application ◽  
Motor Function ◽  
Brain Activity ◽  
Chronic Stroke ◽  
Skill Learning ◽  
Brain Computer Interfaces ◽  
Brain Machine Interfaces ◽  
Positive Effects ◽  
Computer Interfaces ◽  
Brain Signals

AbstractBrain-computer interfaces (BCI) use neuroelectric and metabolic brain activity to activate peripheral devices and computers without mediation of the motor system. In order to activate the BCI patients have to learn a certain amount of brain control. Self-regulation of brain activity was found to follow the principles of skill learning and instrumental conditioning. This review focuses on the clinical application of brain-computer interfaces in paralyzed patients with locked-in syndrome and completely locked-in syndrome (CLIS). It was shown that electroencephalogram (EEG)-based brain-computer interfaces allow selection of letters and words in a computer menu with different types of EEG signals. However, in patients with CLIS without any muscular control, particularly of eye movements, classical EEG-based brain-computer interfaces were not successful. Even after implantation of electrodes in the human brain, CLIS patients were unable to communicate. We developed a theoretical model explaining this fundamental deficit in instrumental learning of brain control and voluntary communication: patients in complete paralysis extinguish goal-directed responseoriented thinking and intentions. Therefore, a reflexive classical conditioning procedure was developed and metabolic brain signals measured with near infrared spectroscopy were used in CLIS patients to answer simple questions with a “yes” or “no”-brain response. The data collected so far are promising and show that for the first time CLIS patients communicate with such a BCI system using metabolic brain signals and simple reflexive learning tasks. Finally, brain machine interfaces and rehabilitation in chronic stroke are described demonstrating in chronic stroke patients without any residual upper limb movement a surprising recovery of motor function on the motor level as well as on the brain level. After extensive combined BCI training with behaviorally oriented physiotherapy, significant improvement in motor function was shown in this previously intractable paralysis. In conclusion, clinical application of brain machine interfaces in well-defined and circumscribed neurological disorders have demonstrated surprisingly positive effects. The application of BCIs to psychiatric and clinical-psychological problems, however, at present did not result in substantial improvement of complex behavioral disorders.

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