scholarly journals Clinical Applications of Brain Computer Interfaces : A Boon for the Future

2021 ◽  
pp. 131-137
Author(s):  
Ishita Singh ◽  
Adwin Manhar
Keyword(s):  
Clinical Applications ◽  
Computer Interface ◽  
External Device ◽  
P300 Speller ◽  
Computer Interfaces ◽  
Brainstem Stroke ◽  
Cord Injury ◽  
The Future ◽  
The Brain ◽  
Lateral Sclerosis

Brain-computer interface (BCI) is the technology act as a interface between the brain and an external device. It converts the signals emitted by the CNS of the brain to artificial output to be understood by the computer. This technology will be most useful to the severely disabled individual or people suffering from amyotrophic lateral sclerosis, brainstem stroke, or any spinal cord injury and thus are impaired of tier ability to communicate and physical functioning. With the fast-paced development and interest of various top-notch companies in this arena due to its positive future Efforts have begun recently to provide safe and secure BCI systems to severely disabled individuals to make their lives easier. In this paper, we will know about BCI , its basic functioning. We will also discuss its clinical application, p300 speller, and its potential for future. Lastly expectation from the future.

scholarly journals Single-Channel Region-Based Speller for Controlling Home Appliances

2022 ◽  
pp. 541-569
Author(s):  
Praveen Kumar Shukla ◽  
Rahul Kumar Chaurasiya ◽  
Shrish Verma
Keyword(s):  
Single Channel ◽  
Low Cost ◽  
P300 Speller ◽  
Cord Injury ◽  
Control Translation ◽  
Ann Classifier ◽  
The Brain ◽  
Channel Region ◽  
Bci System ◽  
Lateral Sclerosis

The brain-computer interface (BCI) system uses electroencephalography (EEG) signals for correspondence between the human and the outside world. This BCI communication system does not require any muscle action; hence, it can be controlled with the help of brain activities only. Therefore, this kind of system is helpful for patients, who are completely paralyzed or suffering from diseases like ALS (Amyotrophic Lateral Sclerosis), and spinal cord injury, etc., but having a normal functioning brain. A region-based P300 speller system for controlling home electronic appliances is proposed in this article. With the help of the proposed system, users can control and use appliances like an electronic door, fan, light, system, etc., without carrying out any physical movement. The experiments are conducted for five, ten, and fifteen trails for each subject. Among all classifiers, the ANN classifier provides the best off-line experiment accuracy of the order of 80% for fifteen flashes. Moreover, for the control translation, the Arduino module is also designed which is low cost and low power-based and physically controlled a device.

scholarly journals Brain-Machine Interfaces: Powerful Tools for Clinical Treatment and Neuroscientific Investigations

2018 ◽  
Vol 25 (2) ◽  
pp. 139-154 ◽  
Author(s):  
Marc W. Slutzky
Keyword(s):  
Brain Machine Interfaces ◽  
Brain Physiology ◽  
The Past ◽  
Computer Interfaces ◽  
Cord Injury ◽  
Behavior Learning ◽  
Primary Focus ◽  
The Brain ◽  
Lateral Sclerosis

Brain-machine interfaces (BMIs) have exploded in popularity in the past decade. BMIs, also called brain-computer interfaces, provide a direct link between the brain and a computer, usually to control an external device. BMIs have a wide array of potential clinical applications, ranging from restoring communication to people unable to speak due to amyotrophic lateral sclerosis or a stroke, to restoring movement to people with paralysis from spinal cord injury or motor neuron disease, to restoring memory to people with cognitive impairment. Because BMIs are controlled directly by the activity of prespecified neurons or cortical areas, they also provide a powerful paradigm with which to investigate fundamental questions about brain physiology, including neuronal behavior, learning, and the role of oscillations. This article reviews the clinical and neuroscientific applications of BMIs, with a primary focus on motor BMIs.

scholarly journals Single-Channel Region-Based Speller for Controlling Home Appliances

2020 ◽  
Vol 11 (4) ◽  
pp. 65-89
Author(s):  
Praveen Kumar Shukla ◽  
Rahul Kumar Chaurasiya ◽  
Shrish Verma
Keyword(s):  
Single Channel ◽  
Low Cost ◽  
P300 Speller ◽  
Cord Injury ◽  
Control Translation ◽  
Ann Classifier ◽  
The Brain ◽  
Channel Region ◽  
Bci System ◽  
Lateral Sclerosis

The brain-computer interface (BCI) system uses electroencephalography (EEG) signals for correspondence between the human and the outside world. This BCI communication system does not require any muscle action; hence, it can be controlled with the help of brain activities only. Therefore, this kind of system is helpful for patients, who are completely paralyzed or suffering from diseases like ALS (Amyotrophic Lateral Sclerosis), and spinal cord injury, etc., but having a normal functioning brain. A region-based P300 speller system for controlling home electronic appliances is proposed in this article. With the help of the proposed system, users can control and use appliances like an electronic door, fan, light, system, etc., without carrying out any physical movement. The experiments are conducted for five, ten, and fifteen trails for each subject. Among all classifiers, the ANN classifier provides the best off-line experiment accuracy of the order of 80% for fifteen flashes. Moreover, for the control translation, the Arduino module is also designed which is low cost and low power-based and physically controlled a device.

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.

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.

Designing Better, Cost-Effective Brain–Computer Interfaces

2015 ◽  
Vol 23 (4) ◽  
pp. 13-19 ◽  
Author(s):  
Chang S. Nam ◽  
Matthew Moore ◽  
Inchul Choi ◽  
Yueqing Li
Keyword(s):  
Steady State ◽  
Research And Development ◽  
Evoked Potential ◽  
Brain Computer Interface ◽  
Cost Effective ◽  
Computer Interface ◽  
Computer Interfaces ◽  
The Brain ◽  
Bci System ◽  
Users With Special Needs

Despite the increase in research interest in the brain–computer interface (BCI), there remains a general lack of understanding of, and even inattention to, human factors/ergonomics (HF/E) issues in BCI research and development. The goal of this article is to raise awareness of the importance of HF/E involvement in the emerging field of BCI technology by providing HF/E researchers with a brief guide on how to design and implement a cost-effective, steady-state visually evoked potential (SSVEP)–based BCI system. We also discuss how SSVEP BCI systems can be improved to accommodate users with special needs.

scholarly journals The Use of a Brain Computer Interface Remote Control to Navigate a Recreational Device

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Shih Chung Chen ◽  
Aaron Raymond See ◽  
Yeou Jiunn Chen ◽  
Chia Hong Yeng ◽  
Chih Kuo Liang
Keyword(s):  
Remote Control ◽  
Information Transfer ◽  
Brain Computer Interface ◽  
Computer Interface ◽  
Brain Response ◽  
Brain Signals ◽  
Information Transfer Rate ◽  
Cord Injury ◽  
Remote Controller ◽  
The Brain

People suffering from paralysis caused by serious neural disorder or spinal cord injury also need to be given a means of recreation other than general living aids. Although there have been a proliferation of brain computer interface (BCI) applications, developments for recreational activities are scarcely seen. The objective of this study is to develop a BCI-based remote control integrated with commercial devices such as the remote controlled Air Swimmer. The brain is visually stimulated using boxes flickering at preprogrammed frequencies to activate a brain response. After acquiring and processing these brain signals, the frequency of the resulting peak, which corresponds to the user’s selection, is determined by a decision model. Consequently, a command signal is sent from the computer to the wireless remote controller via a data acquisition (DAQ) module. A command selection training (CST) and simulated path test (SPT) were conducted by 12 subjects using the BCI control system and the experimental results showed a recognition accuracy rate of 89.51% and 92.31% for the CST and SPT, respectively. The fastest information transfer rate demonstrated a response of 105 bits/min and 41.79 bits/min for the CST and SPT, respectively. The BCI system was proven to be able to provide a fast and accurate response for a remote controller application.

scholarly journals Brain computer interface with the P300 speller: Usability for disabled people with amyotrophic lateral sclerosis

2018 ◽  
Vol 61 (1) ◽  
pp. 5-11 ◽  
Author(s):  
Violaine Guy ◽  
Marie-Hélène Soriani ◽  
Mariane Bruno ◽  
Théodore Papadopoulo ◽  
Claude Desnuelle ◽  
...  
Keyword(s):  
Amyotrophic Lateral Sclerosis ◽  
Brain Computer Interface ◽  
Computer Interface ◽  
Disabled People ◽  
P300 Speller ◽  
Lateral Sclerosis

scholarly journals Brain-Computer Interfaces and Creative Expression: Interface Considerations for Rehabilitative and Therapeutic Interactions

2021 ◽  
Vol 3 ◽  
Author(s):  
Stephanie M. Scott ◽  
Chris Raftery
Keyword(s):  
Personal Experience ◽  
Meaning Making ◽  
Digital Health ◽  
Computer Interface ◽  
Creative Arts ◽  
Embodied Interaction ◽  
Computer Interfaces ◽  
Brain Signals ◽  
Digital Environments ◽  
The Brain

By translating brain signals into new kinds of outputs, Brain-Computer Interface (BCI) systems hold tremendous potential as both transformative rehabilitation and communication tools. BCIs can be considered a unique technology, in that they are able to provide a direct link between the brain and the external environment. By affording users with opportunities for communication and self-expression, BCI systems serve as a bridge between abled-bodied and disabled users, in turn reducing existing barriers between these groups. This perspective piece explores the complex shifting relationship between neuroadaptive systems and humans by foregrounding personal experience and embodied interaction as concepts through which to evaluate digital environments cultivated through the design of BCI interfaces. To underscore the importance of fostering human-centered experiences through technologically mediated interactions, this work offers a conceptual framework through which the rehabilitative and therapeutic possibilities of BCI user-system engagement could be furthered. By inviting somatic analysis towards the design of BCI interfaces and incorporating tenets of creative arts therapies practices into hybrid navigation paradigms for self-expressive applications, this work highlights the need for examining individual technological interactions as sites with meaning-making potentiality, as well as those conceived through unique exchanges based on user-specific needs for communication. Designing BCI interfaces in ways that afford users with increased options for navigation, as well as with the ability to share subjective and collective experiences, helps to redefine existing boundaries of digital and physical user-system interactions and encourages the reimagining of these systems as novel digital health tools for recovery.

scholarly journals Historical perspectives, challenges, and future directions of implantable brain-computer interfaces for sensorimotor applications

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Santosh Chandrasekaran ◽  
Matthew Fifer ◽  
Stephan Bickel ◽  
Luke Osborn ◽  
Jose Herrero ◽  
...  
Keyword(s):  
Computer Technology ◽  
Traumatic Injury ◽  
The Body ◽  
Computer Interface ◽  
Future Directions ◽  
Historical Perspectives ◽  
Computer Interfaces ◽  
Wide Range ◽  
Study Participants ◽  
The Brain

AbstractAlmost 100 years ago experiments involving electrically stimulating and recording from the brain and the body launched new discoveries and debates on how electricity, movement, and thoughts are related. Decades later the development of brain-computer interface technology began, which now targets a wide range of applications. Potential uses include augmentative communication for locked-in patients and restoring sensorimotor function in those who are battling disease or have suffered traumatic injury. Technical and surgical challenges still surround the development of brain-computer technology, however, before it can be widely deployed. In this review we explore these challenges, historical perspectives, and the remarkable achievements of clinical study participants who have bravely forged new paths for future beneficiaries.

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