Neural Engineering

2013 ◽  
pp. 713-744
Author(s):  
Charles J. Robinson
Keyword(s):  
Cochlear Implants ◽  
Artificial Limbs ◽  
Neural Engineering ◽  
Brain Computer Interfaces ◽  
Functional Neuromuscular Stimulation ◽  
Neuromuscular Stimulation ◽  
Engineering Applications ◽  
Computer Interfaces ◽  
The Future

This chapter provides a definition for Neural Engineering and briefly describes its history. An introduction to neuroscientific principles is presented to provide a basis for understanding neurally-engineered developments. Specific advances in neuroprosthetics are described, including visual prosthetics, cochlear implants, myoelectric artificial limbs, brain-computer interfaces, and functional neuromuscular stimulation applications. Other neural engineering applications and the future potentials of the field are also considered.

Brain-Computer Interface for Cyberpsychology

2019 ◽  
pp. 102-122
Author(s):  
Yujia Peng
Keyword(s):  
General Population ◽  
Brain Computer Interface ◽  
Computer Interface ◽  
Clinical Population ◽  
Human Computer Interface ◽  
Brain Computer Interfaces ◽  
User Experiences ◽  
Future Directions ◽  
Computer Interfaces ◽  
The Future

As a new way of implementing human-computer interface, brain-computer interfaces (BCI) dramatically changed the user experiences and have broad applications in cyber behavior research. This chapter aims to provide an overall picture of the BCI science and its role in cyberpsychology. The chapter starts with an introduction of the concept, components, and the history and development of BCI. It is then followed by an overview of neuroimaging technologies and signals commonly used in BCI. Then, different applications of BCI on both the clinical population and the general population are summarized in connection with cyberpsychology. Specifically, applications include communication, rehabilitation, entertainments, learning, marketing, and authentication. The chapter concludes with the future directions of BCI.

From Cochlear Implants and Neurotology to Brain Computer Interfaces

2016 ◽  
pp. 988-1015
Author(s):  
Dionysios Politis ◽  
Miltiadis Tsaligopoulos ◽  
Georgios Kyriafinis
Keyword(s):  
Hearing Loss ◽  
Human Computer Interaction ◽  
Cochlear Implants ◽  
Communication Skills ◽  
Long Memory ◽  
Brain Computer Interfaces ◽  
Direct Manipulation ◽  
Computer Interfaces ◽  
The World ◽  
Special Subgroup

This chapter focuses on the framework of non-deterministic Brain Computer Interfaces within the context of Human Computer Interaction. A very special subgroup of these interfaces, emerging from the world of hearing loss, comprises the Cochlear Implants that affirmatively expose direct manipulation techniques. Short and long memory experiments with musical exploitation can prove shortcomings in inner-knowledge handling and provide understanding of how the language mechanism provides steady, un-biased speech. A model and a protocol for parameterizing sustainable aural communication skills are presented.

scholarly journals Role and Scope Coverage of Speech-Related Professionals Linked to Neuro-Advancements within the Academic Literature and Canadian Newspapers

2019 ◽  
Vol 9 (2) ◽  
pp. 98 ◽  
Author(s):  
Valentina Villamil ◽  
Gregor Wolbring
Keyword(s):  
Lifelong Learning ◽  
Cochlear Implants ◽  
Service Provision ◽  
English Language ◽  
Professional Organizations ◽  
Brain Computer Interfaces ◽  
Academic Literature ◽  
Computer Interfaces ◽  
Ebsco Host ◽  
Deep Brain

Speech-related professionals such as speech language pathologists (SLPs) and audiologists make use of neuro-advancements including neurotechnologies such as cochlear implants (CIs), brain-computer interfaces, and deep brain stimulation. Speech-related professionals could occupy many roles in relation to their interaction with neuro-advancements reflecting the roles expected of them by their professional organizations. These roles include: service provider, promoter of neuro-products such as CIs, educator of others, neuro-related knowledge producer and researcher, advocates for their fields and their clients in relation to neuro-advancements, and influencers of neuro-policy, neuroethics and neuro-governance discussions. Lifelong learning, also known as professional development, is used as a mechanism to keep professionals up to date on knowledge needed to perform their work and could be used to support the fulfillment of all the roles in relation to neuro-advancements. Using 300 English language Canadian newspapers and academic articles from SCOPUS and the 70 databases of EBSCO-Host as sources, we found that the neuro-advancement content linked to speech-related professionals centered around CIs and brain computer interfaces, with other neuro-technologies being mentioned much less. Speech-related professionals were mostly mentioned in roles linked to clinical service provision, but rarely to not at all in other roles such as advocate, researcher or influencer of neuroethics and neuro-governance discussions. Furthermore, lifelong learning was not engaged with as a topic. The findings suggest that the mentioning of and engagement with roles of speech-related professionals linked to neuro-advancements falls short given the expectations of roles of speech-related professionals for example. We submit that these findings have implications for the education of speech-related professionals, how others perceive the role and identity of speech-related professionals, and how speech-related professionals perceive their own role.

A Research on Implantable Microelectrodes for EMG Signal Acquisition

2011 ◽  
Vol 483 ◽  
pp. 387-391
Author(s):  
Zheng Han Zhu ◽  
Jing Quan Liu ◽  
Yue Feng Rui ◽  
Chun Sheng Yang
Keyword(s):  
Power Spectrum ◽  
Frequency Domain ◽  
Time Domain ◽  
Signal Acquisition ◽  
Neural Engineering ◽  
Functional Neuromuscular Stimulation ◽  
Neuromuscular Stimulation ◽  
Emg Signal ◽  
Mems Technology

Signal acquisition microelectrode works as an interface between tissue and circuit in neural engineering. Stable, precise and lossless detection of EMG is important to functional neuromuscular stimulation. In this paper, we propose an implantable microelectrode for EMG acquisition fabricated by MEMS technology and test the impedance of several microelectrodes fabricated with different parameters. By analyzing the amplitudes and power spectrum of the EMG signals acquired from rabbits by fabricated microelectrodes, the signal acquisition performances of the microelectrodes are evaluated and compared both in time domain and frequency domain.

scholarly journals Brain-Computer Interfaces, Open-Source, and Democratizing the Future of Augmented Consciousness

2021 ◽  
Vol 3 ◽  
Author(s):  
Guillermo Bernal ◽  
Sean M. Montgomery ◽  
Pattie Maes
Keyword(s):  
Open Source ◽  
Conflicts Of Interest ◽  
Brain Computer Interfaces ◽  
New Paradigm ◽  
Domain Experts ◽  
Computer Interfaces ◽  
The Future ◽  
Loop Feedback ◽  
Closed Loop Feedback ◽  
Summary Data

Accessibility, adaptability, and transparency of Brain-Computer Interface (BCI) tools and the data they collect will likely impact how we collectively navigate a new digital age. This discussion reviews some of the diverse and transdisciplinary applications of BCI technology and draws speculative inferences about the ways in which BCI tools, combined with machine learning (ML) algorithms may shape the future. BCIs come with substantial ethical and risk considerations, and it is argued that open source principles may help us navigate complex dilemmas by encouraging experimentation and making developments public as we build safeguards into this new paradigm. Bringing open-source principles of adaptability and transparency to BCI tools can help democratize the technology, permitting more voices to contribute to the conversation of what a BCI-driven future should look like. Open-source BCI tools and access to raw data, in contrast to black-box algorithms and limited access to summary data, are critical facets enabling artists, DIYers, researchers and other domain experts to participate in the conversation about how to study and augment human consciousness. Looking forward to a future in which augmented and virtual reality become integral parts of daily life, BCIs will likely play an increasingly important role in creating closed-loop feedback for generative content. Brain-computer interfaces are uniquely situated to provide artificial intelligence (AI) algorithms the necessary data for determining the decoding and timing of content delivery. The extent to which these algorithms are open-source may be critical to examine them for integrity, implicit bias, and conflicts of interest.

scholarly journals Neurophysiology of motor imagery in neurorehabilitation and BCI technologies

2019 ◽  
Vol 4 (3) ◽  
pp. 30-35
Author(s):  
E. S Korovina ◽  
M. S Segreeva ◽  
A. V Zakharov ◽  
V. F Pyatin
Keyword(s):  
Embodied Cognition ◽  
Motor Imagery ◽  
Study Design ◽  
Neural Correlates ◽  
Brain Computer Interfaces ◽  
Computer Interfaces ◽  
The Future

Over the last few decades, motor imagery was in the focus of the researchers' attention as a prototypical example of "embodied cognition", and as a basis for neuro-rehabilitation and brain-computer interfaces. This review reveals the concept of motor imagery, the factors characterizing and influencing this process, its neural correlates, and the possibilities for using in neurorehabilitation and brain-computer interfaces. The article explains some discrepancies and variability in findings from previous studies, that will help to optimize a study design in accordance with the purpose of each study in the future.

A Study of Frontal Signals in Brain Computer Interfaces: Interpretation of EEG & FNIRS

2020 ◽  
pp. 136-142
Author(s):  
S. Srilekha ◽  
B. Vanathi
Keyword(s):  
Infrared Spectroscopy ◽  
Healthy Subject ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Economic Conditions ◽  
Brain Computer Interfaces ◽  
Functional Near Infrared Spectroscopy ◽  
Computer Interfaces ◽  
Rehabilitation Devices

This paper focuses on electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) comparison to help the rehabilitation patients. Both methods have unique techniques and placement of electrodes. Usage of signals are different in application based on the economic conditions. This study helps in choosing the signal for the betterment of analysis. Ten healthy subject datasets of EEG & FNIRS are taken and applied to plot topography separately. Accuracy, Sensitivity, peaks, integral areas, etc are compared and plotted. The main advantages of this study are to prompt their necessities in the analysis of rehabilitation devices to manage their life as a typical individual.

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