scholarly journals Are Brain–Computer Interfaces Feasible With Integrated Photonic Chips?

2022 ◽  
Vol 15 ◽  
Author(s):  
Vahid Salari ◽  
Serafim Rodrigues ◽  
Erhan Saglamyurek ◽  
Christoph Simon ◽  
Daniel Oblak
Keyword(s):  
High Speed ◽  
Near Infrared ◽  
Light Emission ◽  
Photon Emission ◽  
High Yield ◽  
Computer Interfaces ◽  
Brain Signals ◽  
Computer Based ◽  
Neuronal Functions ◽  
The Brain

The present paper examines the viability of a radically novel idea for brain–computer interface (BCI), which could lead to novel technological, experimental, and clinical applications. BCIs are computer-based systems that enable either one-way or two-way communication between a living brain and an external machine. BCIs read-out brain signals and transduce them into task commands, which are performed by a machine. In closed loop, the machine can stimulate the brain with appropriate signals. In recent years, it has been shown that there is some ultraweak light emission from neurons within or close to the visible and near-infrared parts of the optical spectrum. Such ultraweak photon emission (UPE) reflects the cellular (and body) oxidative status, and compelling pieces of evidence are beginning to emerge that UPE may well play an informational role in neuronal functions. In fact, several experiments point to a direct correlation between UPE intensity and neural activity, oxidative reactions, EEG activity, cerebral blood flow, cerebral energy metabolism, and release of glutamate. Therefore, we propose a novel skull implant BCI that uses UPE. We suggest that a photonic integrated chip installed on the interior surface of the skull may enable a new form of extraction of the relevant features from the UPE signals. In the current technology landscape, photonic technologies are advancing rapidly and poised to overtake many electrical technologies, due to their unique advantages, such as miniaturization, high speed, low thermal effects, and large integration capacity that allow for high yield, volume manufacturing, and lower cost. For our proposed BCI, we are making some very major conjectures, which need to be experimentally verified, and therefore we discuss the controversial parts, feasibility of technology and limitations, and potential impact of this envisaged technology if successfully implemented in the future.

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.

Role of 5G Communication Along With Blockchain Security in Brain-Computer Interfacing

2022 ◽  
pp. 65-85
Author(s):  
Mohammad Mudassir Ahmad ◽  
Kiran Ahuja
Keyword(s):  
High Speed ◽  
Body Parts ◽  
Blockchain Technology ◽  
Computer Interfaces ◽  
5G Network ◽  
5G Technologies ◽  
Transfer Of Information ◽  
Brain Computer Interfacing ◽  
The Brain

The electroencephalogram is used in brain-computer interface (BCI) in which signal from the human brain is sensed with the help of EEG and then sent to the computer to control the external device without having any touch of muscular body parts. On the other hand, the brain chip interfacing (BCHIs) is a microelectronic chip that has physical connections with the neurons for the transfer of information. The BCI needs a reliable, high-speed network and new security tool that can assist BCI technology. 5G network and blockchain technology is ideal to support the growing needs of brain chip interfacing. Further, the Cloudmind, which is an emerging application of BCI, can be conceptualized by using blockchain technology. In this chapter, brain-computer interfaces (BCIs) are expedient to bridge the connectivity chasm between human and machine (computer) systems via 5G technologies, which offers minimal latency, faster speeds, and stronger bandwidth connectivity with strong cryptographic qualities of blockchain technologies.

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.

Brain-Computer Interfaces and Visual Activity

2013 ◽  
pp. 1549-1570
Author(s):  
Carmen Vidaurre ◽  
Andrea Kübler ◽  
Michael Tangermann ◽  
Klaus-Robert Müller ◽  
José del R. Millán
Keyword(s):  
Video Game ◽  
Brain Activity ◽  
Visual Stimuli ◽  
Robot Arm ◽  
Virtual Keyboard ◽  
Computer Interfaces ◽  
Brain Signals ◽  
Brain States ◽  
Physically Disabled People ◽  
The Brain

There is growing interest in the use of brain signals for communication and operation of devices, in particular, for physically disabled people. Brain states can be detected and translated into actions such as selecting a letter from a virtual keyboard, playing a video game, or moving a robot arm. This chapter presents what is known about the effects of visual stimuli on brain activity and introduces means of monitoring brain activity. Possibilities of brain-controlled interfaces, either with the brain signals as the sole input or in combination with the measured point of gaze, are discussed.

Implications of NIRS Brain Signals

2013 ◽  
pp. 120-128
Author(s):  
Munetaka Haida
Keyword(s):  
Cross Sections ◽  
Near Infrared ◽  
High Signal ◽  
Intensity Level ◽  
Brain Signals ◽  
Signal Environment ◽  
Nirs Signal ◽  
Hb Concentration ◽  
The Brain ◽  
Very High

Near Infrared Spectroscopy (NIRS) is commonly used for functional brain studies. With this method, brain signals can be easily obtained, but the interpretation of these signals still remains unclear. This chapter provides a simple model to interpret the NIRS signal, which is based on the following assumptions: 1. The NIRS signal may reflect Hb levels only in the capillaries and not in large vessels; 2. The brain has a lighter color than the other tissues, indicating that the Hb concentration in brain tissue is very low and intensity level of the NIRS signal is very high; 3. A photon that hits a large vessel is too weak to be detected in the surrounding high signal environment; 4. Cerebral blood flow (CBF) can be separated into cross-sections (the number of capillary beds) that are multiplied by the velocity. This model can explain the typical signal pattern observed during task performance, where oxy-Hb levels increase and deoxy-Hb levels slightly decrease.

scholarly journals Discovering Patterns in Brain Signals Using Decision Trees

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Narusci S. Bastos ◽  
Diana F. Adamatti ◽  
Cleo Z. Billa
Keyword(s):  
Decision Trees ◽  
Blind People ◽  
Spatial Problem ◽  
Common Belief ◽  
Data Mining Technique ◽  
Computer Interfaces ◽  
Brain Signals ◽  
The Difference ◽  
Difficult Challenge ◽  
The Brain

Even with emerging technologies, such as Brain-Computer Interfaces (BCI) systems, understanding how our brains work is a very difficult challenge. So we propose to use a data mining technique to help us in this task. As a case of study, we analyzed the brain’s behaviour of blind people and sighted people in a spatial activity. There is a common belief that blind people compensate their lack of vision using the other senses. If an object is given to sighted people and we asked them to identify this object, probably the sense of vision will be the most determinant one. If the same experiment was repeated with blind people, they will have to use other senses to identify the object. In this work, we propose a methodology that uses decision trees (DT) to investigate the difference of how the brains of blind people and people with vision react against a spatial problem. We choose the DT algorithm because it can discover patterns in the brain signal, and its presentation is human interpretable. Our results show that using DT to analyze brain signals can help us to understand the brain’s behaviour.

scholarly journals Infrared Light Emission From Semiconductor Devices

1996 ◽  
Author(s):  
D.L. Barton ◽  
P. Tangyunyong ◽  
J.M. Soden ◽  
A.Y. Liang ◽  
F.J. Low ◽  
...  
Keyword(s):  
Integrated Circuits ◽  
Quantum Efficiency ◽  
Near Infrared ◽  
Light Emission ◽  
Photon Emission ◽  
Ccd Camera ◽  
Infrared Light ◽  
High Quantum Efficiency ◽  
High Quantum ◽  
Cooled Ccd

Abstract We present results using near-infrared (NIR) cameras to study emission. characteristics of common defect classes for integrated circuits (ICs). The cameras are based on a liquid nitrogen cooled HgCdTe imaging array with high quantum efficiency and very low read noise. The array was developed for infrared astronomy and has high quantum efficiency in the wavelength range from 0.8 to 2.5 µm. For comparison, the same set of samples used to characterize the performance of the NIR camera were studied using a non-intensified, liquidnitrogen- cooled, slow scan CCD camera (with a spectral range from 400-1100 nm). Our results show that the NIR camera images all of the defect classes studied here with much shorter integration times than the cooled CCD, suggesting that photon emission beyond 1 µm is significantly stronger than at shorter wavelengths.

scholarly journals Progress in Brain Computer Interface: Challenges and Opportunities

2021 ◽  
Vol 15 ◽  
Author(s):  
Simanto Saha ◽  
Khondaker A. Mamun ◽  
Khawza Ahmed ◽  
Raqibul Mostafa ◽  
Ganesh R. Naik ◽  
...  
Keyword(s):  
Affective Computing ◽  
Global Scale ◽  
Communication Link ◽  
Computer Interfaces ◽  
Brain Signals ◽  
Challenges And Opportunities ◽  
Significant Research ◽  
Potential Applications ◽  
Related Feature ◽  
The Brain

Brain computer interfaces (BCI) provide a direct communication link between the brain and a computer or other external devices. They offer an extended degree of freedom either by strengthening or by substituting human peripheral working capacity and have potential applications in various fields such as rehabilitation, affective computing, robotics, gaming, and neuroscience. Significant research efforts on a global scale have delivered common platforms for technology standardization and help tackle highly complex and non-linear brain dynamics and related feature extraction and classification challenges. Time-variant psycho-neurophysiological fluctuations and their impact on brain signals impose another challenge for BCI researchers to transform the technology from laboratory experiments to plug-and-play daily life. This review summarizes state-of-the-art progress in the BCI field over the last decades and highlights critical challenges.

scholarly journals Effect of quantized conductivity on the anomalous photon emission radiated from atomic-size point contacts

Nanophotonics ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 413-425 ◽  
Author(s):  
Mickaël Buret ◽  
Igor V. Smetanin ◽  
Alexander V. Uskov ◽  
Gérard Colas des Francs ◽  
Alexandre Bouhelier
Keyword(s):  
Near Infrared ◽  
Light Emission ◽  
Electrical Power ◽  
Photon Emission ◽  
Electromagnetic Emission ◽  
Hot Electrons ◽  
Point Contacts ◽  
Atomic Size ◽  
Metal Boundary ◽  
Bremsstrahlung Process

AbstractWe observe anomalous visible to near-infrared electromagnetic emission from electrically driven atomic-size point contacts. We show that the number of photons released strongly depends on the quantized conductance steps of the contact. Counterintuitively, the light intensity features an exponential decay dependence with the injected electrical power. We propose an analytical model for the light emission considering an out-of-equilibrium electron distribution. We treat photon emission as a Bremsstrahlung process resulting from hot electrons colliding with the metal boundary, and find qualitative accord with the experimental data.

Brain-Computer Interfaces and Visual Activity

2012 ◽  
pp. 153-174
Author(s):  
Carmen Vidaurre ◽  
Andrea Kübler ◽  
Michael Tangermann ◽  
Klaus-Robert Müller ◽  
José del R. Millán
Keyword(s):  
Video Game ◽  
Brain Activity ◽  
Visual Stimuli ◽  
Robot Arm ◽  
Virtual Keyboard ◽  
Computer Interfaces ◽  
Brain Signals ◽  
Brain States ◽  
Physically Disabled People ◽  
The Brain

There is growing interest in the use of brain signals for communication and operation of devices – in particular, for physically disabled people. Brain states can be detected and translated into actions such as selecting a letter from a virtual keyboard, playing a video game, or moving a robot arm. This chapter presents what is known about the effects of visual stimuli on brain activity and introduces means of monitoring brain activity. Possibilities of brain-controlled interfaces, either with the brain signals as the sole input or in combination with the measured point of gaze, are discussed.

Sign in / Sign up

Export Citation Format

Share Document