Monday, July 02, 2018

Learning with BCIs - from Prof. Aaron Batista

A very interesting 30 minutes presentation about BCI / Machine Learning and NeuroScience explained by Professor Aaron Batista.

When we learn, the brain changes at nearly every level of organization. Synapses form and strengthen, individual neurons change their tuning properties, and cortical maps expand. My research examines how learning alters the coordinated activity of populations of neurons. This is a particularly important level at which to study learning because it is the action of populations of neurons that drive behavior, generate perceptions, and undergird our cognition.


For more information about BCI/EEG press here.


Monday, June 25, 2018

3 BCI Jobs - Inria Bordeaux Sud Ouest

3 New BCI vacancies are available to start in September / October 2018:
  • Computational Modeling of Mental Imagery-based BCI user training - PhD position;
  • Redefining EEG Signal Processing and Machine Learning to ensure efficient Mental Imagery-based BCI user training - Post-doc position;
  • R&D Engineer position to implement brain signal processing tools and BCI applications in the OpenViBE software platform - Engineer position

For more information about BCI/EEG press here.

Thursday, June 14, 2018

Poster and Exhibitor Demonstrations at 7th International BCI Meeting

In the 7th International BCI meeting at Asilomar, California - USA, many papers presentations took place during the congress. This PDF provided by BCI Society, with more than 200 pages, describes a resume of each poster and exhibitor demonstrations divided by the following themes:
  • BCI Implant- Control / Other;
  • BCI Non-Invasive- Control / Other;
  • Signal Acquisition / Analysis;
  • User Aspect: Experience and Ethics.


For more information about BCI/EEG press here.


Wednesday, June 13, 2018

EPOC Flex - The new EEG device from Emotiv

EMOTIV company has a new EEG device available for $2100. The EPOC Flex as 32 channels (+ 2 references), CMS/DRL configurable in any 10-20 location or on ears, 1024 internal downsampled to 128 SPS, realtime CQ monitor (patented), 0.16 – 43Hz, 16 bit per channel, 0.51μV @ 16 bit,  ±4.17 mV, sintered silver-silver chloride, 9 axis sensor, proprietary 2.4GHz wireless and li-poly battery, 680 mAh up to 9 hours.

EPOC Flex combines the award-winning wireless technology of our EPOC+ headset with the flexibility and high density afforded by more traditional EEG head cap systems. EPOC Flex is a wireless control box that works alongside the EasyCap system. It can be configured to record from any of the standard 10-20 EEG positions for up to 32 channels.

For more information about BCI/EEG press here.


Wednesday, April 18, 2018

Highly Interactive BCI based on Flicker-Free SSVEP

Visual evoked potential-based brain–computer interfaces (BCIs) have been widely investigated because of their easy system configuration and high information transfer rate (ITR). However, the uncomfortable flicker or brightness modulation of existing methods restricts the practical interactivity of BCI applications. In our study, a flicker-free steady-state motion visual evoked potential (FF-SSMVEP)-based BCI was proposed. Ring-shaped motion checkerboard patterns with oscillating expansion and contraction motions were presented by a high-refresh-rate display for visual stimuli, and the brightness of the stimuli was kept constant. 


Compared with SSVEPs, few harmonic responses were elicited by FF-SSMVEPs, and the frequency energy of SSMVEPs was concentrative. These FF-SSMVEPs evoked “single fundamental peak” responses after signal processing without harmonic and subharmonic peaks. More stimulation frequencies could thus be selected to elicit more responding fundamental peaks without overlap with harmonic peaks. A 40-target online SSMVEP-based BCI system was achieved that provided an ITR up to 1.52 bits per second (91.2 bits/min), and user training was not required to use this system. This study also demonstrated that the FF-SSMVEP-based BCI system has low contrast and low visual fatigue, offering a better alternative to conventional SSVEP-based BCIs.

For more information about BCI/EEG press here.


Tuesday, April 17, 2018

"BCI: Two Concurrent Learning Problems" by Maureen Clerc

Brain-Computer Interfaces (BCI) are systems which provide real-time interaction through brain activity, bypassing traditional interfaces such as keyboard or mouse. A target application of BCI is to restore mobility or autonomy to severely disabled patients. In BCI, new modes of perception and interaction come into play, which users must learn, just as infants learn to explore their sensorimotor system. Feedback is central in this learning. From the point of view of the system, features must be extracted from the brain activity, and translated into commands. (...) It is for instance possible to monitor the brain's reaction to the BCI outcome. In this talk I will present some of the current machine learning methods which are used in BCI, and the adaptation of BCI to users' needs.


For more information about BCI/EEG press here.


Thursday, April 05, 2018

BCI and EEG Projects in European Commission

It is the European Commission's primary public repository and portal to disseminate information on all EU-funded research projects and their results in the broadest sense. The website and repository include all public information held by the Commission (project factsheets, publishable reports and deliverables), editorial content to support communication and exploitation (news, events, success stories, magazines, multilingual "results in brief" for the broader public) and comprehensive links to external sources such as open access publications and websites.


If you want to know all the European Research Projects about a specified area, as "BCI" or "EEG", you can use the Community Research and Development Information Service (CORDIS). 
For example, to get all the results containning BCI, written in english, from September, 1 - 2017, type in the search field "('BCI') AND language='en' AND contentUpdateDate>=2017-09-01" or just use the "advanced search" option.


For more information about BCI/EEG press here.


Wednesday, April 04, 2018

PhyCS 2018 - 5th International Conference on Physiological Computing Systems

PhyCS is the annual meeting of the physiological interaction and computing community, and serves as the main international forum for engineers, computer scientists and health professionals, interested in outstanding research and development that bridges the gap between physiological data handling and human-computer interaction. 


PhyCS brings together people interested in creating novel interaction devices, adaptable interfaces, algorithms and tools, through the study, planning, and design of interfaces between people and computers that are supported by multimodal biosignals. 

TOPIC AREAS:

DEVICES
  • Biomedical Devices for Computer Interaction
  • Brain-computer Interfaces
  • Wearable Sensors and Systems
  • Cybernetics and User Interface Technologies
  • (...)

METHODOLOGIES AND METHODS
  • Biosignal Acquisition, Analysis and Processing
  • Simulation of Physiological Processes
  • Pattern Recognition
  • Neural Networks
  • (...)

HUMAN FACTORS
  • User Experience
  • Usability
  • Adaptive Interfaces
  • Human Factors in Physiological Computing
  • (...)
APPLICATIONS
  • Physiology-driven Computer Interaction
  • Biofeedback Technologies
  • Assistive Technologies
  • Physiological Computing in Mobile Devices
  • (...)

For more information about BCI/EEG press here.

 

Wednesday, March 07, 2018

Artificial Intelligence + Machine Learning = Deep Learning EEG

How can we apply AI and Machine Learning to EEG data? There is evidence that EEG characteristics can be used as an indication (a biomarker) of some diseases. For example, in a project funded by The Michael J. Fox Foundation, our findings indicate that there are significant differences in the EEG data of different RBD patients compared to healthy populations. More specifically, RBD subjects as a group had larger power in the frontal EEG electrodes than healthy subjects. Again taken as a group. Therefore, there is statistical significance in the difference between one group and the other. 


However, if we want to use this as a means for diagnosis, we need to take into account that diagnostic decisions are made on individuals, not on groups. For this to happen we need a decision system. We would input the data of a particular individual subject. Then we would get an answer on whether this individual is likely to develop, for instance, a neurodegenerative disease. Here is where Machine Learning and Deep Learning come into play.


For more information about BCI/EEG press here.


Friday, March 02, 2018

Open Database of Live Human Brain Cells

The Allen Institute for Brain Science has added the first data from human nerve cells to the Allen Cell Types Database: a publicly available tool for researchers to explore and understand the building blocks of the human brain. This first release includes electrical properties from approximately 300 living cortical neurons of different types derived from 36 patients, with accompanying 3D reconstructions of their shape or anatomy for 100 cells, and computer models simulating the electrical behavior of these neurons. 


The database will also contain gene expression profiles, based on measurements of all genes used by 16,000 individual cells, from three adult human brains. Data from these human cells provide an unparalleled window into the intricate components, circuitry and function of the human neocortex, including features that make our brains unique.

For more information about BCI/EEG press here.


Saturday, February 24, 2018

Workshops Schedule - 7th International BCI Meeting, 2018

The 7th International BCI Meeting:BCIs: Not Getting Lost in Translation”, is scheduled for May 21 – 25, 2018 at the Asilomar, California, USA.


SESSION 1- WEDNESDAY, MAY 23 (9:00-12:00)
  • BCIs for stroke rehabilitation­­­
  • Progress in Decoding Speech processes using intracranial signals
  • Noninvasive BCI-control of FES for grasp restoration in high spinal cord injured humans
  • Collaborative and Competing Multi-Brain BCI’s
  • ECoG based BCIs
  • Examining Ethical Assumptions About Neural Engineering and BCI Development
  • Towards the Elusive Killer App for BCIs
  • User-Centered Design in BCI development; A Broad Perspective
  • ­­­­­­­­­­­­­­­Lower-limb brain-machine interfaces and their applications 

SESSION 2- THURSDAY, MAY 24 (9:00-12:00)
  • BCIs for assessment of locked-in and DOC patients
  • Turning negative into positives! Exploiting “negative” results in BCI research
  • ­­­­­­­­Eye Tracking, Vision, and BCI
  • Natural Language Processing & BCI
  • ­­­­­­­­BCI and Augmented/Virtual Reality
  • ­Recent Developments in Non-Invasive EEG SensorTechnology
  • Making use of the future of BCI implant technology
  • Clinical Applications of Brain-Computer Interfaces in Neurorehabilitation

SESSION 3- THURSDAY, MAY 24 (13:15-16:15)
  • ECoG for control and mapping
  • Real-time BCI communication for non-verbal individuals with cerebral palsy
  • Tools for establishing neuroadaptive technology through passive BCIs
  • Neurofeedback during Artistic Expression as Therapy
  • Unsupervised Learning for BCIs
  • Perception of Sensation Restored through Neural Interfaces
  • From the lab into the wild: shaping methods and technologies for large-scale BCI research
  • Standards for Neurotechnologies and Brain-Machine Interfacing


For more information about BCI/EEG press here.


Wednesday, February 21, 2018

28 Workshops from the 6th International BCI Meeting

The 6th International BCI Meeting was held 30 May–3 June 2016 at the Asilomar, California, USA. The conference included 28 workshops covering topics in BCI and brain–machine interface research. Topics included BCI for specific populations or applications, advancing BCI research through use of specific signals or technological advances, and translational and commercial issues to bring both implanted and non-invasive BCIs to market. To download the complete OpenAccess document in PDF format press here


For more information about BCI/EEG press here.


Tuesday, February 20, 2018

New features in "BCI over EEG" Blog

In this Blog header there is a new feature making possible to group the information by topics (BCI, EEG, Brain, Jobs, Conference,...) allowing a more organized search of the several published posts.


For more information about BCI/EEG press here.


Monday, February 19, 2018

Professor in Brain-Computer Interfaces and Neural Engineering

The School of Computer Science and Electronic Engineering from the University of Essex - UK, is looking for Professor in BCI and neural engineering. 


As part of the continued expansion of the School, we are seeking to appoint two Professorships in two of the four areas of specialism in the school. We are also recruiting in the areas of:
  • Artificial Intelligence and Computer Games
  • Cyber Physical Systems
  • Human Language Technology/Natural Language Processing.
The successful candidate will have a PhD in a relevant discipline and relevant academic expertise in a related area. You will have a proven track record of internationally excellent research relevant to the post, a strong track record of published academic output at international levels of recognition, success in raising grant income appropriate to the research discipline, and a sustained record of effectiveness in relation to teaching and learning at both undergraduate and postgraduate levels.


For more information about BCI/EEG press here.


Saturday, February 10, 2018

A Multi-APP Framework for BCI/EEG on Android Smartphones

If you want to process EEG on an Android smartphone then this paper EEG Recording and Online Signal Processing on Android: A Multiapp Framework for Brain-Computer Interfaces on Smartphone from School of Medicine and Health Sciences - University of Oldenburg, published in Biomed Research International, may be of great interest: .


Our aim was the development and validation of a modular signal processing and classification application enabling online EEG signal processing on off-the-shelf mobile Android devices. The software application SCALA (Signal ProCessing and Classification on Android) supports a standardized communication interface to exchange information with external software and hardware. Approach. In order to implement a closed-loop BCI on the smartphone, we used a multiapp framework, which integrates applications for stimulus presentation, data acquisition, data processing, classification, and delivery of feedback to the user. We have implemented the open source signal processing application SCALA. We present timing test results supporting sufficient temporal precision of audio events. We also validate SCALA with a well-established auditory selective attention paradigm and report above chance level classification results for all participants. Regarding the 24-channel EEG signal quality, evaluation results confirm typical sound onset auditory evoked potentials as well as cognitive event-related potentials that differentiate between correct and incorrect task performance feedback. Significance. We present a fully smartphone-operated, modular closed-loop BCI system that can be combined with different EEG amplifiers and can easily implement other paradigms.

For more information about BCI/EEG press here.


Thursday, February 08, 2018

cEEGrids: Concealed, Unobtrusive Ear-Centered EEG Acquisition

Martin G. Bleichner and Stefan Debener from University of Oldenburg, Germany, created the cEEGrids: an EEG system motion tolerant, highly portable, unobtrusive, and near invisible data acquisition with minimum disturbance of a user's daily activities. This new solution represents one more important step in the portability of EEG that can be used in a much more natural way.


We discuss work showing that miniature electrodes placed in and around the human ear are a feasible solution, as they are sensitive enough to pick up electrical signals stemming from various brain and non-brain sources. We also describe the cEEGrid flex-printed sensor array, which enables unobtrusive multi-channel EEG acquisition from around the ear. In a number of validation studies we found that the cEEGrid enables the recording of meaningful continuous EEG, event-related potentials and neural oscillations. 

For more information about BCI/EEG press here.


Wednesday, February 07, 2018

BioSignals 2019 - 12th International Joint Conference on Biomedical Engineering Systems and Technologies

The purpose of the International Conference on Bio-inspired Systems and Signal Processing is to bring together researchers and practitioners from multiple areas of knowledge, including biology, medicine, engineering and other physical sciences, interested in studying and using models and techniques inspired from or applied to biological systems. (...) The analysis and use of these signals is a multidisciplinary area including signal processing, pattern recognition and computational intelligence techniques, amongst others.


UPCOMING DEADLINES
  • Regular Paper Submission: October 1, 2018
  • Regular Paper Authors Notification: November 29, 2018
  • Regular Paper Camera Ready and Registration : December 13, 2018

For more information about BCI/EEG press here.


Friday, February 02, 2018

NoiseTag BCI - High Accuracy without Trainning

The Donders Research Group from Radboud University created a BCI/EEG platform which aims high accuracy, speed reaction and user-friendly. The main features improved are CCA-based Reconvolution, Dynamic stopping, Zero-training, Asynchronous, Headsets, Adaptive and Applications.


We found a method that turns BCI into plug and play. The first button you look at will take the system a bit longer to figure out, taking about 30 seconds. Then the second button goes down to 10 seconds. Then the 3rd-4th is down to 1-2 seconds. A person can get up to 1 button per second. 
The headband uses dry electrodes, so we do not have to use water.
In the Noise-Tagging project we utilize pseudo-random noise-codes as stimulation sequences (i.e., stimuli are tagged with noise) for evoked Brain BCI. These so-called noise-tags exhibit a spread-spectrum signal and when applied as stimuli, these evoke Broad-Band Evoked Potentials (BBEP) visible in the EEG. We have designed a generative method – Reconvolution – which combines both deconvolution and convolution to learn and predict responses to these noise-tags. Specifically, adhering to the superposition hypothesis, the complex BBEP can be decomposed into a summation of time-shifted versions of a/some transient response(s). 



For more information about BCI/EEG press here


Thursday, February 01, 2018

10 EEG Headsets Technical Overview Comparison

The IMOTIONS company published a recent comparison about the 10 headsets more used in EEG research. Number of channels, Sampling Rate, Type of Communication Medically Certified are some of the characteristics analyzed.

Finding the right EEG device for your research can be a tricky process. There are a multitude of aspects to consider, and the importance of each can depend on your approach. To add to the confusion, each manufacturer shows (or doesn’t show!) the information in different ways, making the search for the right device even more difficult. Below, we’ve put together a listing of some of the most important variables that you’ll want to consider when investing in an EEG headset.



Headset Devices:

All this study can be found in IMOTIONS headset comparison.


For more information about BCI/EEG press here.

Monday, January 29, 2018

JASP - Open-source project for Data Analysis resulting in Fast Conclusions with Minimal Work

JASP is an open-source project supported by the University of Amsterdam with an intuitive interface offering standard data analysis in classical or bayesian form.


JASP was designed with the user in mind: APA-formatted tables can be copy-pasted in your word processor, output can be extensively annotated, adjustment of input options dynamically changes the output, and selecting old output revives the associated input choices for inspection and adjustment.


JASP is open-source and free of charge, and we provide it as a service to the community. JASP is also statistically inclusive, as it offers both frequentist and Bayesian analysis methods. Indeed, the primary motivation for JASP is to make it easier for statistical practitioners to conduct Bayesian analyses.
Feature List:


For more information about BCI/EEG press here.


Tuesday, January 16, 2018

OpenVibe - One of the Best BCI Software

OpenViBE is a free software platform dedicated to design, process and classify EEG data to be used in brain-computer interfaces. The package includes some tools to create and run custom applications (drag & drop), it is compatible with many EEG devices and demo programs are ready for use. Programming in Python is also possible.


OpenVibe is, in my opinion, one of the best software platform in BCIs so, if you want to learn how to use it, the tutorial from MENSIA enterprise is the best way to start. 


OpenViBE Consortium is the future management and funding structure for OpenViBE. Interested parties can join the consortium as members or donate to it. The consortium will be a non-profit that uses its funds to hire dedicated engineers. The engineers in turn develop the platform to directions that are of interest to the consortium members.


For more information about BCI/EEG press here.


Wednesday, January 10, 2018

NeuroTechNix 2018 Congress - Neuro: Prosthetics, Imaging, Sensing, Informatics, Computing, Modulation and Engineering

Neurotechnology shows a very high potential of enhancing human activities, involving technologies such as neural rehabilitation, neural prosthesis, neuromodulation, neurosensing and diagnosis, and other combinations of neurological and biomedical knowledge with engineering technologies.


Congress Areas

AREA 1: NEURAL REHABILITATION AND NEUROPROSTHETICS


  • Assistive Technologies
  • Telerehabilitation
  • Virtual Reality Tools
  • Augmentative and Alternative Communication
  • Biofeedback Therapy
  • Brain/Neural Computer Interfaces
  • Clinical and Social Impact of Neurotechnology
  • Human Augmentation
  • Mobile Technologies
  • Privacy, Security and Neuroethics
  • Robotic Assisted Therapy

AREA 2: NEUROIMAGING AND NEUROSENSING


  • Artificial Intelligence for Neuroimaging
  • Sleep Analysis
  • Brain imaging
  • Diagnostic Sensors
  • EEG and EMG Signal Processing and Applications
  • Intelligent Diagnosis Systems
  • Mobile and Embedded Devices
  • Neural Signal Processing
  • Positron Emission Tomography
  • Real Time Monitoring of Neuromuscular and Neural Activity

AREA 3: NEUROINFORMATICS AND NEUROCOMPUTING


  • (Artificial) Neural Networks
  • Brain Models and Functions
  • Cognitive Science and Psychology
  • Computational Neuroscience
  • Learning Systems and Memory
  • Neurobiology
  • Reverse Engineering the Brain
  • Self-organization and Evolution

AREA 4: NEUROMODULATION AND NEURAL ENGINEERING


  • Biochips and Nanotechnology
  • Transcranial Magnetic Stimulation
  • Translating into Clinical and Industrial Outcomes
  • Bionic Vision
  • Cochlear implants
  • Cybernetics
  • Deep Brain Stimulation
  • Functional Electrical Stimulation (FES)
  • Neuro-interface Prosthetic Devices
  • Non-Invasive Brain Stimulation
  • Optogenetics

The congress will be held in Seville - Spain, from 20 to 21 September 2018 and the Paper submission is May 2, 2018

For more information about BCI/EEG press here.


Tuesday, January 09, 2018

Next Generation of Neural Interfaces

The Imperial College of London has a Next Generation Neural Interfaces research group to "create interfaces that will change the way the people interact with surroundings". Another team of researchers that surely contribute in advancing of BCIs area.



For more information about BCI/EEG press here.


Thursday, January 04, 2018

Open-Source Python Code for BCI/EEG

Visbrain is an open-source python 3 package dedicated to brain signals visualization. It is based on top of VisPy and PyQt and is distributed under the 3-Clause BSD license.


Visbrain includes six visualization modules :
  • Brain : visualize EEG/MEG/Intracranial data, connectivity in a standard MNI 3D brain 
  • Sleep : visualize polysomnographic data and hypnogram edition 
  • Signal : data-mining module for time-series inspection 
  • Topo : display topographical maps 

For more information about BCI/EEG press here.


Wednesday, December 20, 2017

Massachusetts Medical School aims to introduce Mindfulness into Medical Care

Dr. Judson Brewer, has been named as chief of the Division of Mindfulness. “The creation of a stand-alone Division of Mindfulness embedded within a Department of Medicine highlights how far the field has progressed and matured, and will create the infrastructure and support for researchers dedicated to furthering our neuroscientific knowledge of how the mind works, and for what medical conditions mindfulness is efficacious,” 


The move comes more than 30 years after the center’s Mindfulness Based Stress Reduction (MBSR) clinic was established at the university. Since then, more than 24,000 people have been trained in Mindfulness-based Stress Reduction (MBSR) at the clinic.

There are several studies on mindfulness meditation someones using electroencephalography. One of the major challenges is to prove scientifically functional changes in the cerebral cortex by comparing results on individuals during, at least, 8 weeks of therapy.

For more information about BCI/EEG press here.


Monday, December 18, 2017

Intheon are Wiring for BCI/EEG Data Processing

At Intheon, our vision is to embed advanced neurotechnology into everyday life. We offer a middleware platform for biosignal interpretation, which is easily integrated into existing mobile and desktop applications through a cloud API. NeuroScale™ empowers developers to rapidly create transformative brain- and body-aware applications impacting medicine and health, interactive technology, marketing, education, and more.


Deep Learning Research Engineer – Neurotechnology

We are seeking a highly talented and motivated research engineer who is fascinated by the latest developments in ML/AI and is looking for the most exciting, challenging, and high-impact areas to apply them. You will be part of team of senior researchers and engineers where you will focus on designing and implementing advanced brain-computer interface technology using state of the art deep learning techniques. Your research & development will help power the coming generation of brain-based human-machine interfaces where neurotechnology is integrated into everyday life.

  • You will work directly with senior staff on developing new methods for applying deep learning on EEG and other physiological data.
  • You will write production-grade code and train Brain-Computer Interface models on large amounts of EEG data.


Staff Scientist – Neuroscientist

Taking advantage of large-scale electrophysiological (e.g. EEG) data is essential for training robust powerful machine learning systems capable of decoding brain state in complex environments. At Intheon you will be responsible for developing and applying technologies for large-scale EEG data analysis, powering the coming generation of brain-based human-machine interfaces where neurotechnology is integrated into everyday life.

  • You will work directly with our senior staff on advancing the state of the art in large-scale EEG data processing and management.
  • You will develop new computational methods for combining EEG features across multiple studies (meta-analysis).
  • You will interpret analysis results and publish them in scientific journals.


For more information about BCI/EEG press here.


Saturday, December 16, 2017

Brain-Computer Interfaces: Applications, Challenges and the Future

The Brain-Computer Interfaces (BCI) are systems that allow through the thought to execute commands on computers or electronic devices. This technology, based on the reading of brain electrical impulses and its signal processing, is becoming more and more accessible to ordinary people when it was previously confined to enclosed spaces such as research laboratories or hospital clinics.


When we talk about BCIs, we have great contributions to its dissemination through Elon Musk and Mark Zuckerberg. These, in recent comments, have given as examples cars monitored with the mind or writing by thought. While the company Neuralink is recruiting experts in this field, the multinational Facebook has created a research department aimed at implementing a solution that allows you to write 100 words per minute on a computer, tablet or smartphone, just thinking. With the daily technological advance, associated with artificial intelligence increasingly present in data processing, the question to be asked will not be "if it is possible" but rather "when it will be possible". The BCIs present today as a technology of high potential, although in embryonic phase.


In my opinion, an example of enormous success in the medical field refers to Locked-In syndrome. There are patients who are permanently bedridden for weeks or months, in the conscious state, but without their body being able to communicate with the outside, only being able to hear and some have sensitivity to the touch. Using the electroencephalography, with the placement of sensors in the patient's head, BCIs allow the reading and identification of thought patterns. Once two of these patterns can be clearly identified, with the help of a computer that processes and classifies the signal, the patient will be able to answer "Yes" or "No" to the questions posed. Even within the limitations described, imagine the happiness of the patient and his family when establishing this communication channel.


Many other solutions are now used in the area of ​​BCIs, such as neuro-prosthetics, treatment of attention disorders, neuro-rehabilitation or simply fun and leisure. Regarding this last example, the MindX game is being developed at the Champalimaud Foundation, with the aim of "flying" between circles that appear on the screen. In order to perform this movement, the player uses only the thought, controlling in a natural way his movements. Contrary to other systems presented a little around the world, this solution developed by a team of portuguese neuroscientists does not require days of training. Its use is practically immediate, representing a huge advance and potential of applicability on new scenarios.

(This article was published @ pplware.sapo.pt)

For more information about BCI/EEG press here.


Friday, December 15, 2017

A Trip through the Cerebral Cortex by High-Throughput Array Tomography

It is very important to understand the structure and all synapses responsible for the electrical impulses inside our brain. Make a trip through the interior of the brain, from somatosensory cortex to white matter:


For more information about BCI/EEG press here.


Thursday, December 14, 2017

SMART - Open Source Platform for Healthcare

SMART Health IT is an open based technology platform that enables innovators to create apps that seamlessly and securely run across the healthcare system. Using an electronic health record (EHR) system or data warehouse that supports the SMART standard, patients, doctors, and healthcare practitioners can draw on this library of apps to improve clinical care, research, and public health.

The SMART App Gallery provides a central place to connect apps and app users, offering developers a free and open way to share their apps and healthcare providers an easy way to find and try SMART compatible apps.

For more information about BCI/EEG press here.


Tuesday, December 12, 2017

FB Career Openings for BCI

Facebook has more than 2500 career openings including some jobs related to Brain-Computer Interfaces.

As rumors pile up that Facebook is working on moving into consumer hardware, all eyes remain on the company’s Building 8 division, which handles those projects. Dugan presented onstage at Facebook’s F8 conference this year, talking about some of the company’s more long-shot projects, like embeddable brain sensors that could promote a more tight interface with hardware products.


For more information about BCI/EEG press here.


Sunday, December 10, 2017

BCI Award 2017 - Submission Deadline

The International Annual BCI-Research Award, endowed with 6,000 USD, is one of the top accolades in BCI research. The Award was created to recognize outstanding and innovative research in the field of Brain-Computer Interfaces. The Award is open to any brain-computer interface research worldwide and 12 projects are nominated before the winner is announced.


FACTS
  • The 12 nominated projects will be invited to submit a chapter to be published in Springer
  • The winner gets 3,000 USD, the 2nd place 2,000 USD and the 3rd place 1,000 USD
  • The BCI-award is donated by g.tec, a leading provider of BCI research equipment 
  • The competition is open to any BCI group worldwide. .


For more information about BCI/EGG press here.


Friday, December 08, 2017

Modeling 10,000 Neurons in the Visual Cortex

Scientists at the Allen Institute for Brain Science create models of neurons in the visual cortex of the mouse. With this work it is possible to understand better the neurons connections and the complexity to aquire EEG in a human brain.  


This movie shows preliminary data of 10,000 neurons: 8,000 replicated pyramidal cells (an excitatory neuron, shown first) and 2,000 replicated interneurons (an inhibitory neuron, shown second). Copies of these two cells are displayed one after another in the movie until approximately 10% of the whole model is shown; more than that would be too cluttered to see what is happening. Toward the middle of the movie, the cells are colored according to their properties: excitatory in red and inhibitory in blue. The second half of the movie illustrates activity of the cells in a two second-long simulation. The cells that fire action potentials are intermittently highlighted, giving the viewer an impression of the simulated neuronal activity.

For more information about BCI/EEG press here.


Wednesday, December 06, 2017

VR Headset for Smartphones with Eye Tracking and EEG Brain Sensors

The company LooxiLabs from South Korea just released on the market a Brain Wave solution with 6 EEG frontal channels + Eye Information + Open SDK.

Signal resolution:
  • Data transmission rate: 250 SPS Resolution: 24 bits
  • Bandwidth: To provide 1-50Hz, 7-13Hz, 15-50Hz, 5-50Hz Bandpass filters.
  • 50Hz and 60Hz Notch filters Filtering: 2nd order Butterworth iir filter
  • Dynamic range: +/- 2.5V analog operating voltage



Looxid Labs Development Kit is the world’s first VR headset embedded with miniaturized eye and brain sensors. The Development Kit provides information about where the users have looked and how the users’ brains are activated in VR, enabling early adopters and developers to create unique and incredible experience for VR users. Acquiring a considerable number of bio-signal datasets is key to defining user’s emotions by machine learning algorithm. Thus, we have been working on the experiment in which a research participant watches a series of VR contents and responds to the surveys on their feeling while wearing our VR headset embedded with eye tracking cameras and EEG sensors. 

For more information about BCI/EEG press here.


Tuesday, December 05, 2017

Learning Python with Dan Bader

Python is a great programming language that you can apply in a easy way to BCI/EEG. If you want to increase your knowledge in this area follow the videos of Dan Bader explaining it in a simple and coherent way.


For more information aboutBCI/EEG press here.


Monday, December 04, 2017

Creating EEG Graphs from Raw Data

RAW Graphs is an open source data visualization framework built with the goal of making the visual representation of complex data. Primarily conceived as a tool for designers and vis geeks, RAW Graphs aims at providing a missing link between spreadsheet applications (e.g. Microsoft Excel, Apple Numbers, OpenRefine) and vector graphics editors (e.g. Adobe Illustrator, Inkscape, Sketch).


The project, led and maintained by the DensityDesign Research Lab (Politecnico di Milano) was released publicly in 2013 and is regarded by many as one of the most important tools in the field of data visualization.

You can convert a EEG file to CSV, drag & drop it and get a data graphic representation.

For more information about BCI/EEG press here.


Saturday, November 04, 2017

3D Rotative Graph from a CSV file using Python

There are several modules in Python to create different types of graphs. "The Python Graph Gallery" brings together several examples, as rotating 3D chart, created from a data file in CSV format. The next code, from Yan Holtz, save 70 PNG images in the "filename" folder. Then you just need to convert them to GIF format using, for example, gifmaker.meThis code can easily be adapted to read EEG data files.

# library
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns

# Get the data (csv file is hosted on the web)
url = 'https://python-graph-gallery.com/wp-content/uploads/volcano.csv'
data = pd.read_csv(url)

# Transform it to a long format
df=data.unstack().reset_index()
df.columns=["X","Y","Z"]

# And transform the old column name in something numeric
df['X']=pd.Categorical(df['X'])
df['X']=df['X'].cat.codes

# We are going to do 20 plots, for 20 different angles
for angle in range(70,210,2):

   # Make the plot
   fig = plt.figure()
   ax = fig.gca(projection='3d')
   ax.plot_trisurf(df['Y'], df['X'], df['Z'], cmap=plt.cm.viridis, linewidth=0.2)

   # Set the angle of the camera
   ax.view_init(30,angle)

   # Save it
   filename='PNG/ANIMATION/Volcano_step'+str(angle)+'.png'
   plt.savefig(filename, dpi=96)
   plt.gca()

For more information about BCI/EEG press here.


Friday, November 03, 2017

Brain-Computer Interface online free course

Christian Kothe, from SCCN/UCSD, presents an online course on BCI designed with a focus on modern methods. It includes basics of EEG, BCI, signal processing, machine learning, and also contains tutorials on using BCILAB and the lab streaming layer software. Although it was published in 2012 it maintains several BCI principles.


For more information about BCI/EEG press here.


Sunday, October 29, 2017

Mental Work using a Motorized Wheel

The École polytechnique fédérale de Lausanne (EPFL) in Switzerland, as a new demonstration of brainwave reading technology. It will involve EEG being connected to a motorized wheel. People will be controlling the movement of the device while the data their brainwaves generate will be anonymized, collected, and provided to researchers for study.


“The industrial revolution was a dangerous period in history, literally dangerous for the laborer who might lose a hand while not paying attention. Now we are in the cognitive revolution and the stakes are potentially higher. Today, that won’t happen because you are not in touch with the machine in any physical way. Instead, you may lose your mind.”

For more information about BCI/EGG press here.


Tuesday, October 24, 2017

Monday, October 23, 2017

Typing 100 Words in a Smartphone using just Your Mind

As I published during June 2017, Facebook aims to allow people to type 100 words per minute with just your mind, 5X faster than typing on a smartphone. Knowing the technological evolution that we are living, in your opinion, how many years Facebook will need to create this BCI solution? The possible answers are: 2 years, 5 years, 10 years, 20 years or never. Share your opinion pressing here.


For more information about BCI/EEG press here.