BioSemi activeTwo EEG using SSVEP

The BCI and Neural Engineering Lab of University of Essex shows in the next video how to control a cursor using SSVEP.

For more information about BCI/EEG press here.

Movements of the same limb being classified from low frequency time domain EEG signals

Patrick Ofner gave this talk on movements of the same limb being classified from low frequency time domain EEG signals at the BCI Meeting in 2016.

Jon Wolpaw's Talk on the Future of BCI

Dr. Jon Wolpaw, a neurologist and President of the BCI Society, gives a talk on the future of Brain Computer Interfaces at the Sixth International Brain-Computer Interface Meeting at the Asilomar Conference Grounds from May 30th to June 3rd, 2016

Open-Source Biosignal Acquisition Device

Glasgow Neuro has released an open-source data acquisition device for wearable health monitoring applications. It can amplify electroencephalography (EEG) signals, also ECG and EMG, and be processed by external devices such as tablets and smartphones.

The ATTYS is able to transmit raw data, uncompressed signal data at 24 bits wirelessly via Bluetooth. Apps can then be easily built that filter and process this data while maintaining the ability to see the original source, a feature particularly useful for scientific studies. See the video.

For more information about BCI/EEG press here.

Natural brain-information interfaces: Recommending information by relevance inferred from human brain signals

A new concept of BCI called Brain-Information Interface is being studied with already published results.

Finding relevant information from large document collections such as the World Wide Web is a common task in our daily lives. Estimation of a user’s interest or search intention is necessary to recommend and retrieve relevant information from these collections. We introduce a brain-information interface used for recommending information by relevance inferred directly from brain signals. In experiments, participants were asked to read Wikipedia documents about a selection of topics while their EEG was recorded. Based on the prediction of word relevance, the individual’s search intent was modeled and successfully used for retrieving new relevant documents from the whole English Wikipedia corpus.

The results show that the users’ interests toward digital content can be modeled from the brain signals evoked by reading. The introduced brain-relevance paradigm enables the recommendation of information without any explicit user interaction and may be applied across diverse informationintensive applications.

For more information press here. 

Average Salary of BCI Jobs

Using the Indeed application, the Average Salary of a BCI Engineer in USA is $8.500/month (8.000€).

Facebook is looking for a BCI Engineer - Salary: $145.000/year

Facebook's mission is to give people the power to share, and make the world more open and connected. The Technical Project Team has the responsibility for scoping the effort from inception to product, communicating it to others, creating the partnerships necessary to achieve targeted results, and hitting key milestones. 

B8 seeks an experienced Brain-Computer Interface (BCI) Engineer who will be responsible for working on a 2-year B8 project focused on developing advanced BCI technologies. We are looking for a slightly impatient individual willing to face down their fear of failure to accomplish bold things. This is a two-year position based in our Menlo Park office.

Responsibilities

• Application of machine learning methods, including encoding and decoding models, to neuroimaging and electrophysiological data
• Oversee collaborative research, data management, and software development across a diverse set of external partners including academic and industrial organizations
• Travel to partner sites to review progress and facilitate collaboration

Minimum Qualifications

• Ph.D. degree in neuroscience, computer science, electrical engineering, or related quantitative technical field required
• 3+ years of experience with brain-computer interface technologies or other applications or machine learning methods to neuroimaging and/or electrophysiological data
• Ability to work effectively with diverse partners, vendors, and internal teams.
• Knowledge with software engineering and development
• Familiarity with commercial or open source software packages for artificial speech recognition, natural language processing, or computer vision methods

More information press here

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Global BCI Market is Expected to Reach a Value of US$1.23 bn by 2024

RESEARCHMOZ added Most up-to-date research on BCI Market .

• By Type: Invasive BCI, Partially Invasive BCI, Noninvasive BCI; 
• By Technology: Electroencephalography (EEG), Electrocorticography (ECOG), Near Infrared Spectroscopy (NIRS), Functional Magnetic Resonance Imaging (fMRI), Magnetoencephalography (MEG); 
• By Application: Health Care, Gaming and Entertainment, Communication and Others.

For more information about BCI/EEG press here.

How We Learn - Neurons, Brain Chemistry and Neurotransmission

Synapses and Neural Pathways - Brain Nertworking increasing our knowledge.

One more year dedicated to BCI

Greetings from Lisbon, Portugal: https://goo.gl/bdIAer

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JOBS in Human Computer Interaction Institute at Carnegie Mellon

Cognitive Systems Engineers (CSE) work with interdisciplinary CSE teams to create the concepts and detailed designs for revolutionary information systems.  The CSE team is dedicated to providing principle-driven design of human-machine systems with the central focus being creating effective systems that embed user expertise and support decision making. 

CSEs are responsible for the interface designs as well as the comprehensive cognitive work analysis that informs those designs. Our CSEs also work closely with our talented group of software developers, providing design concepts, representational designs, and functionality requirements as guidance for their system development effort.

For more information press here.

Brain Assessment with Ahead 300

BrainScope, develop technology for assessing traumatic brain injuries (TBI), just won FDA clearance for its latest device, the Ahead 300. 

It can provide a rapid electroencephalographic (EEG) assessment of a person who suffered a head injury, utilizing disposable electrodes and a connected smartphone to process the information. It relies on the firm’s proprietary algorithms and machine learning to spot certain patterns and correlations within the recorded brainwaves.

Following the test it produces a report that highlights important aspects that are of note. These can then be used to help pin down a diagnosis. More information here.

JOB - PhD student Sleep for traumatic memories

Post-traumatic stress disorder (PTSD) is a severely disabling mental disorder with traumatic memories at its core, resulting in nightmares and flashbacks. Sleep is crucial in the treatment of PTSD, since traumatic memories that get neutralized during treatment subsequently get integrated in long-term storage during memory consolidation while asleep. This stabilizes the updated memories and further reduces their affective charge. Recent advances in basic memory research show that memory consolidation can be enhanced by presenting reminder cues. This project aims to integrate these memory reactivation strategies during sleep for the first time in standard PTSD treatment to increase overall therapeutic effectiveness. By using functional MRI before and after and polysomnography during treatment, the project will at the same time elucidate the underlying neurobiological mechanism.

The candidate is responsible for conducting experimental research (including patient inclusion and fMRI/EEG measurements), data analysis and reporting findings in international journals. He/she is expected to submit a high quality dissertation for examination within four years of the appointment.

For more information about this Psychiatry/Neuroscience Job in GGZ inGeest press here.

BCI for Basic Research

Why BCI researchers should focus on attempted, not imagined, movement?

Sensorimotor Rhythm BCI with TDCS Alters Task Performance

Noninvasive EEG Based Control of a Robotic Arm for Reach and Grasp Tasks

A team at University of Minnesota has created a control system that relies non-invasive electroencephalography (EEG) to allow people to use a robotic arm to move objects.

One more long step in brain-computer interfaces that can be used to control the complex motion of powered robotic arms. More information here.

PhD positions in University of Rhode Island, USA

The National Center for Adaptative Neurotechnologies (NCAN) is looking for two PhD positions in Biomedical Engineering until December, 15th.

For more information contact the Assistant Professor, Yalda Shahriari.

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Comparing Brain–Computer Interfaces Equipments

Source: https://en.wikipedia.org/wiki/Comparison_of_consumer_brain%E2%80%93computer_interfaces

PhyCS 2017 Conference, Madrid - Spain

PhyCS is the annual meeting (28-29 July, 2017) 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.

Researchers attending PhyCS seek to extend the state-of-the-art, design of new wearable devices that make physiological data acquisition more pervasive, design of user interfaces capable of recognizing and adapting to changes in the physiological state of the user, and / or the creation of algorithms to enable robust and seamless control of computational resources.

Important Dates:

• Regular Paper Submission: March 2, 2017
• Position Paper Submission: April 18, 2017

For more information press here.

BCI in 2045

According to the Pentagon in 2045 we will communicate using neural activity and control gadgets with brain signals. Watch the video:

7th Graz BCI Conference

The Institute of Neural Engineering is currently organizing the 7th Graz BCI Conference, in September 2017 endorsed by the BCI Society.

Important Dates:

• Submission opens: Dec. 1st 2016
• Deadline Paper submission: Feb. 1st 2017
• Deadline Satellite Events: Feb. 1st 2017
• Satellite Event Notification: Mar. 1st 2017
• Paper Acceptance Notification: April 15th 2017

NeuroAdaptive Technology Conference

The conference is based around the theme of Neuroadaptive Technology where measures of the brain and CNS are used for closed-loop control. The aim is to bring together researchers from applied neurosciences, engineering and computer science to explore the emergence of this nascent technology.  The range of relevant topics includes: passive BCI, physiological computing, affective computing, robotics, neurofeedback, autonomous technology, gaming, wearable sensors, HCI evaluation and neuroethics.

Paper submission opens at December 1st, 2016 and the deadline is January 31st, 2017. For more informations press here.

Cybathlon 2016 Powered Exoskeleton Finals

Cybathlon 2016 provides a platform for the development of novel assistive technologies that are useful for daily life. Through the organisation of the Cybathlon we want to remove barriers between people with disabilities, the public and technology developers.

Individuals with physical disabilities competed side by side in six demanding disciplines, using the latest assistive technologies.

Watch the athletes as they tackled flights of stairs in the new wheel chairs and proved their speed and skill using the most up-to-date modern prostheses. The various races tested how the competitors cope with specific challenges and activities from everyday life.

The Faculty of Science and Technology (FCT) from Universidade NOVA de Lisboa, Portugal receives the Prime Minister and the Minister of Science, Technology and Higher Education that will visit laboratories and classrooms where actions arising host new students.

This initiative aims to integrate the new students by strengthening their curiosity and enthusiasm for natural science area of the respective courses, including hands-sessions on conducted by young researchers and students. The themes show the current limits of knowledge and the challenges facing the development incluing Brain-Computer Interface projects from LIBphys department.

New EEG device from OpenBCI - Do it yourself!

OpenBCI has a new concept of EEG devices where you can create yourself with a desktop 3D-printer. You can also buy the product fully-assembled.

The Ultracortex is an open-source, 3D-printable headset intended to work with any OpenBCI Board. It is capable of recording research-grade brain activity (EEG), muscle activity (EMG), and heart activity (ECG). The Ultracortex Mark IV is capable of sampling up to 16 channels of EEG from up to 35 different 10-20 locations.

The Ultracortex Mark IV is the latest edition of the Ultracortex—a comfortable, adjustable, and 3D-printable EEG headset, compatible with all of the OpenBCI boards.

EMOTIV Community SDK at GitHub

For all developers who want to use the EMOTIV equipment can utilize the code already developed and archived on GitHub.

For more informations press here.

The most Grand Challenges for Brain Science in the next 10 Years

The first grand challenge seeks to understand what makes brains unique.

The second is to find out how the brain solves the complex computational problems of life.

And the final challenge is how to use the information to help diagnose, prevent brain disease and to restore function when brains become damaged.

More informations here.

How does the BRAIN work

Video about neurological basis of higher brain function from the National Institute of Mental Health (NIMH).

Learn how different human behaviors and functions can be isolated to specific areas of the brain, and how with the help of imaging techniques like MRI we can visualize brain activity in a way that gives insight into how the brain functions and allows scientists to develop treatment methods for various mental illnesses in the future. 

NEURABLE - Looking for inspired minds to work with BCIs

Neurable wants to create a world where people live without limitations by enabling 3-D control of software and devices through brain activity in real-time enabling people to play games, operate toys and drive a full-sized car using their brain activity.

They are also looking for a Machine Learning Scientist/Researcher with a salary of $100.000/year.

If you are looking to create new possibilities and unlocks the true potential of existing non-invasive BCIs press here. 

WE ARE THE CHAMPIONS - Portugal UEFA Euro 2016

I know it's not a matter of BCI or EEG but I must share my happiness together with more than 10 million Portuguese!!!:-) :-) :-)

11th International Symposium on Medical Information and Communication Technology - ISMICT 2017

ISMICT 2017 aims to establish a forum to present new research and development results, exchange ideas, discuss practices and share experiences among Technology and Medicine sides including healthcare, wellness, clinical therapy, and surgery as well as ICT, mechanical, and biomedical engineering. Moreover, activities of standard, regulation, and business for medical ICT devices, systems and services will be promoted by national, European and global government and industry.

Some of the symposium topics:

• CPS for medical applications
• BAN technology (PHY, MAC, protocols)
• Antennas and radio propagation for wireless BAN
• Medical BAN applications and services
• Wearable and implantable devices
• E-Health systems and electronic medical records
• Hospital data networks and wireless hospital
• Privacy and Security issues
• Pervasive health care and patient monitoring
• Human body communication

ISMICT 2017 will be held in Instituto Superior Técnico, Lisbon, Portugal, from 6th to 8th February 2017.

6th International BCI Meeting in Asilomar, 2016 - Poster Presentations

POSTER PRESENTATIONS

Decoding decision outcomes from single realizations of lateral prefrontal cortex ensemble activity Predicting Forelimb Muscle Activity from Corticospinal Signals in Rats Upper Limb Movement Encoding by Intracortical Recordings in Human Sensorimotor Cortex Reliable BMI control using epidural ECoG by an hemiplegic user Time domain classification of grasp and hold tasks NAO race: exploring social context on motor imagery performance Movements of the same upper limb can be classified from low-frequency time-domain EEG signals Temporal dynamics of mouth motor cortex activity during speech Motivation matters: Psychological models in brain-computer interfacing Extraction of motor patterns from joint EEG/EMG recording: A Riemannian Geometry approach Hyperparameter Optimization for Machine Learning Problems in BCI

Towards a BCI Based on Vergence Eye Movements Spatial Abilities Play a Major Role in BCI Performance Effect of visuomotor coordination and relaxation repeated interventions for Sensorimotor BCI Comparison Between Discrete and Continuous Motor Imageries: toward a Faster Detection A visual BCI system using mild peripheral visual field stimulation M3BA: New Technology for Mobile Hybrid BCIs Comparison of session-to-session transfer (...) in motor imagery BCI Turbo-Satori: A novel real-time fNIRS data processing and analysis toolbox Attentional processes during P3-based BCI task in amyotrophic lateral sclerosis patients P300 Latency Jitter More Likely for People with ALS BCI as a New AAC Access Modality for Individuals with Advanced Paralysis. Combining Methods To Predict Accuracy of Individual Brain-Computer Interface Selections Fusion of P300 and Eye Tracker Data for Spelling Using BCI2000 Improving Motor Imagery BCI with User Response to Feedback On the pursuit of classification of EEG recorded during imagined speech FlashTypeTM: A Context Aware, Language Independent, (...) using c-VEP or Eye Tracking Sheet Music by Mind: A BCI for Composing “Brain Invaders 2”: an open source Plug & Play multi-user BCI videogame Neurofeedback via intracranial depth electrodes Intracortical Microstimulation as a Feedback Source for Brain-Computer Interface Users Sensorimotor Rhythm BCI with Simultaneous High Definition-Transcranial Direct (...)  Controlling UAVs with a SSVEP-Based BCI Extended BCI controlled alpha band neurofeedback training in schizophrenia patients Improving Motor Recovery after Stroke by Combined rTMS and BCI Training Comparison of Three Modalities of SMR-BCI within Stroke Patients Detecting walking intention using EEG phase patterns Prediction of Subject Ratings of Emotional Pictures from EEG Features Home-Based Rehabilitation System Using Portable BCI and Functional Electrical Stimulation Thought-controlled nanoscale robots in a living host Factors and values related to technology acceptance of BCI as assistive technology Online Accuracy of Invasive and Non-invasive MI BCI Adaptive assistance for BCI: a locked-in syndrome end-user case study Time varying EEG Bandpower Estimation Improves 3D Hand Motion Trajectory Prediction Accuracy Discriminating goal-directed from nongoal-directed movements (...) for BCI control Single Trial Classification of Neural Correlates of Anticipatory Behavior during Real Car Driving Detecting P300 ERPs with Convolutional Networks Frontal-Temporal Connectivity Dysfunction in a Mouse Model of Schizophrenia Tactile BCI performance of sensory experts Online classification of visual perception Attention in Complex Environment of Brain Computer Interface New approach based on frequency features of EEG signals (...) during walking Spatial Frequency Characterization and Optimization of SSVEP Stimuli Image and Neural Classifier Co-Training (...) in Rapid Serial Visual Presentation Online Optimization of Visual Stimuli for Reducing Fatigue in SSVEP-based BCIs Classification of Visual Target Detection during Guided Search using EEG Source Localization Pipeline for ECoG electrode localization on brain surface: towards a one click approach Relevant Frequency Estimation in EEG Recordings for Source Power Co-Modulation Non-verbal Communication using BCI, Haptic Feedback and Dance MindBEAGLE: An EEG-based BCI developed for patients with disorders of consciousness An Improved Cognitive Brain-Computer Interface for Patients with Amyotrophic Lateral Sclerosis Speech envelope tracking using around the ear EEG Toward improved covert attention application using shifting stimuli Recursive Queries for BCIs: SSVEP Shuffle Speller Predicting BCI Performance with the Detectability Index Boosting BCI accuracy using wavelet enhanced CBLE scores as a classifier feature Prediction of Difficulty Levels in Video Games from EEG Cortico-Muscular-Coupling and Covariate Shift Adaptation based BCI for (,,,) Stroke Patients Volitional Control of Beta Band Power (...) with Nexus-D Streaming Neurophysiological correlates of mind-wandering, towards a predictive BCI-based Neurofeedback Adaptive Interactive Learning for Training BCI Systems Enhanced modulation of working memory activity through fMRI neurofeedback An Automated Method for Determining Awareness and Predicting Recovery after Brain Injury (...) BCI-NMES therapy enhances effective connectivity in the damaged hemisphere in stroke patients Evaluation of Motion Artifacts on EEG Signals during Exoskeleton Gait. Lateralization patterns for movement execution (...) with concurrent EEG-fMRI and EEG-fNIRS Programming for Pediatrics: A literature review of brain-computer interfaces for neurorehabilitation in children Classification of attempted and executed hand movements from ipsilateral motor cortex in amputees Can amputees control a brain-computer interface with their missing hand? Sensorimotor Rhythms During Preparation for Robot-Assisted Movement Multiuser Spatial cVEP BCI Direct Brain-robot Control Mirage91: The Graz BCI-Racing Team – making students familiar with BCI research Demonstration of a Chronic Brain-Computer Interface using a Deep Brain Stimulator Intelligence and Brain Dynamics in Children with Cerebral Palsy Why BCI researchers should focus on attempted, not imagined movement The quantified cook – Physiological responses during cooking food (...)  Comparison of Hierarchical and Non-Hierarchical Classification for Motor Imagery Based BCI Systems Detection of errors using multiple spectro-temporal features related to distinct post-error neural processes Effects of Off-Site Attention on SSSEP Amplitude Soft Drink Effects on Brain Computer Interface Online Performance and Resting-State Arousal Tripolar Concentric Ring Electrode Encephalography Reduces Muscle Artifacts for BCI Applications Fatigue Evaluation through EEG Analysis Using Multi-scale Entropy in SSVEP-based BCIs Towards a simulator of mu rhythms for the development of BCI applications in children: (...)  Improved estimates of BCI accuracy with hierarchical Bayesian models Skipping BCI calibration: fundamental investigations on Restricted Boltzmann Machines Estimated Prevalence of Severe Paralysis With Loss of Communication in The Netherlands. Analyzing the Performance of Dry Electrodes for P300 Brain-Computer Interfaces in Participants with ALS Home use of an EEG-based BCI by people with amyotrophic lateral sclerosis (ALS)  (...) Towards an Auditory BCI for Binary Communiation in the ICU Development of a Real Time Speech Synthesizer Based Brain Computer Interface Toward a Brain Interface for Tracking Attended Auditory Sources Initial evaluation of an auditory P300 brain-computer interface for the Japanese Hiragana syllabary Bio-inspired Filter Banks for SSVEP BCIs An Online Brain-Computer Interface Using Dynamically Detected Steady-State Visual Evoked Potentials EEG Clustering Based on Phase Synchrony for Self-paced BCI Development Influence of cognitive variables in a Brain-Computer Interface driven application Social inclusion as feature to improve BCI skill training: A feasibitly case study in cerebral palsy The impact of a BCI for creative expression on the quality of life of two arists in the locked-in state Virtual Reality, Graphics and mVEP Classification Predicting Single-Trial Motor Performance from Oscillatory EEG in Chronic Stroke Patients BCI-approach for cognitive rehabilitation in stroke: pilot data from patient with spatial neglect Why and How to Use Intelligent Tutoring Systems to Adapt MI-BCI Training to Each User? Importance of the Window Size for Neurofeedback based on fMRI Functional Connectivity A Prognostic Measure on EEG-based Motor Imagery Brain-Computer Interface for Stroke The Effect of Deep Brain Stimulation on the Pallido-Cortical Coherency Pattern of Parkinson’s Disease Neurogoggles for Stroke Rehabilitation Classifying force levels of hand grasping and opening using electroencephalography cortical currents Magnetoencephalography-based Real-time Control of a Prosthetic Hand in Paralyzed Patients Pushing the limits of BCI accuracy: Winning solution of the Grasp & Lift EEG challenge. BCI-based Semi-Autonomous Wheelchair Control using (...) Cyber Physical System Approach  Decoding of two hand grasping types from EEG Development of an SSVEP Brain Computer Interface Robust to Data Nonstationarity Comparisons and Calculations in the Human Posterior Parietal Cortex Tactile BCI training for elderly people ERP Responses of the Elderly for Bisyllabic Word Stimuli Visual Perceptual-based Spatial Location Discrimination Using Single-trial EEG Analysis How is subject-to-subject transfer probable in motor imagery BCI? Potential Use of Electrical Somatosensory Modality for Brain Computer Interface Decoding auditory attention using behind the ear EEG Autocorrelation based EEG Dynamics depicting Motor Intention A New Statistical Model of EEG Noise Spectra for Real-time, Low-gamma-band SSVEP BCI Comparison of a consumer grade EEG amplifier with medical grade equipment in BCI applications Deep Transfer learning for Cross-Experiment Prediction of Rapid Serial Visual Presentation Events Communication Strategies to Involve Potential Users in BCI Research Blink Artifact Rejection Algorithms May Interfere with P3 Speller BCI Accuracy Noninvasive detection of neural sources underlying ECoGbased P300 speller performance Single-trial Classification of Inner Speech and the No-control State Using Electroencephalography Cognitive workload BCI in the maritime environment Incorporating neuroscience priors into brain-computer interfaces to detect attentional state Error-Related Potentials for EEG-Based Typing Systems Classification of motor imagery with distractions Large Scale EC research projects: ComaWare and recoveriX Leveraging Temporal Confusion in P300 Spellers BCI-controlled Brain Painting at home: years of use Brain Painting V2: long-term evaluation by an end-user at home – an update Unity Plugin for Immersive BCI Applications GKT-Enhanced Applications Motor Imagery Based BCI Racing: Challenge a Friend with 4 Channel Dry Electrode EEG First steps towards adaptive deep brain stimulation in Parkinson’s disease Treating attention deficits in chronic stroke patients using Slow Cortical Potential (SCP) Neurofeedback A Quest for the Cortical Representation of Subjective Surprise With a Virtual Reality Neurofeedback Platform Volitional control of basal ganglia activity for the treatment of Parkinson’s disease Analysis of Subcortical Beta Activities in Stroke Patients for Motor Rehabilitation Comparing EEG and fNIRS for a covert attention BCI Theta phase coupling with rhythmic motor output during visuomotor tracking Noninvasive EEG Based Control of a Robotic Arm for Reach and Grasp Tasks Detecting and utilizing the idle state in an intracortical brain-computer interface Scenario screen: P300 speller variation for wheelchair control Separable decoding of cue, intention, and movement information from the fronto-parietal grasping-network A surgeon’s brain switch: cortical dynamics of cognitive load in surgeons Movement Related Cortical Potential based on Multi-Class Motor Imagery Effect of a cognitive involving videogame on MI task Towards Mobile and Wearable Brain-Computer Interfaces Oscillatory modulations during human verbal interaction – A simultaneous EEG/MEG study Combination of EEG and fNIRS for the (Un)Conscious Discrmination during Anesthesia Design of Duty-cycle Screening Paradigm for Steady-State Somatosensory Evoked Potential Transfer Learning with Large-Scale Data in Brain-Computer Interfaces NPXLab Suite 2016: tools for BCI signal analysis Word networks for BCI decoding purposes Distinct timescales of cortical reorganization in a long-term learning task using an intracortical BCI Electrophysiological recording stability in human intracortical brain-computer interface users Visual and auditory P300-BCI: influence of daytime on P300 amplitude in patients with ALS Beyond the control: idle state detection in human intracortical Brain-Computer Interfaces Spelling with cursor movements modified by implicit user response Subject-Specific Electrode Subsets for P300 BCI: Typically Developing and Cerebral Palsy Populations Using congruent activity from primary motor cortex and the cognitive attention network to improve the specificity of the BCI control signal. Features reduction for P300 Spellers Re(con)volution: accurate response prediction for BBVEP-based BCI The contribution of counting to neural activity evoked by the oddball paradigm A yes/no auditory-based BCI: trying to communicate with complete locked-in patients Novel SSVEP-BCI Setup Evaluation During Emotional State Elicited by Unpleasant Sounds A New Region-based BCI Speller Design using Steady State Visual Evoked Potentials Multisensory Stimulation Framework for BCI-based Communication in the ICU Context Aware Recursive Bayesian Estimation in BCI for Graph Navigation An Affective Brain-Computer Music Interface Competitive and Collaborative Multiuser BCI Emotion Imagery BCI Improving Motor Imagination with Support of Real-Time LORETA Neurofeedback fMRI informed EEG Neurofeedback from the IFG Controlling Gestures of a Social Robot in a Brain Machine Interface Platform Neural activity in a simultaneous BCI & manual task A novel BCI based rehabilitation approach for aphasia rehabilitation Brain-Computer Interface based communication in patients diagnosed with post-stroke aphasia Toward standards in AAC-BCI performance measurement and a data repository Towards Detecting of Walking Intention from Readiness Potentials for a Powered Exoskeleton Control On the use of ROS as a common infrastructure for robotic BCI driven applications Full Body Spatial Tactile BCI for Direct Brain-robot Control Can SSVEP be modulated by tDCS? Investigating Depth of Cognitive Processing in the Brain Dynamics of Oscillations Single Channel Hybrid BCI System using Motor Imagery and SSVEP Efficient Transfer Learning in Brain Computer Interfaces using Spectral Meta Learning 2-D analog like control of a cursor by means of SSVEP acquired with two dry electrodes and elicited by 4 LEDs ERP features correlate with reaction time in a covert-attention task Disentangeling working memory load – finding inhibition and updating components in EEG data Pilot Study on Using Fractional Order Calculus-Based Filtering for the Purpose of EEG Signals Analysis CEBL3: A New Software Platform for EEG Analysis and Rapid Prototyping of BCI Technologies A Real-Time Neural Spike Based Data Reduction Platform Predicting Serial Visual Presentation Events from EEG Using Spatial-temporal Convolution Neural Network Neural Signature of Selective Sensation based Tactile BCI in the Context of ECoG Investigation Music rhythm reconstruction from ECoG Visual and audiory P300-BCI: psychological predictors of performance in healthy subjects Articulatory gestures are insensitive to within-word context Nationwide survey of 780 Japanese patients with amyotrophic lateral sclerosis: Their present status and expectations from brain–computer interfaces Online BCI Typing using Language Models by ALS Patients in their Homes Detecting Drowsiness in RSVP KeyboardTM BCI Users with SSPI Effects of Stimuli Relevance on Auditory BCI A user-focused study of auditory P300 brain-computer interface design Improving the information transfer rate at auditory BCI system using virtual sound Optimizing the face Paradigm for BCI systems with the modified Mismatch Negativity paradigm An Audiovisual BCI for Awareness Evaluation in Patients with Disorder of Consciousness FLashLifeTM: A Context Aware Solution for Everyday Life Robust, accurate spelling based on error-related potentials A Transfer Learning Approach for Adaptive Classification in P300 Paradigms Affective BCI for characterizing museum visitors response A method for estimating emotional arousal changes (...) during movie screening using SSVEP My Virtual Dream: Brain Computer Interface In An Immersive Art Environment Real-time self-regulation across multiple visual neurofeedback presentations Improving Memory Performance Using a Wearable BCI Reducing BCI calibration time with transfer learning: a shrinkage approach Keeping disability in mind: A qualitative study of BCI researcher and end user perspectives Hemicraniectomy-based EEG as a platform for low-risk investigations of BCIs in subjects with brain injuries A Portable, Low-Cost BCI for Stroke Rehabilitation Enhanced Motor Imagery Classification in EEG-BCI using Multivariate EMD based filtering and CSP Features BCI controlled neuromuscular electrical stimulation enables sustained motor recovery in chronic stroke victims

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6th International BCI Meeting in Asilomar, 2016 - Oral Presentations

ORAL PRESENTATIONS Why BCI researchers should focus on attempted, not imagined movement An Audiovisual BCI for Awareness Evaluation in Patients with Disorder of Consciousness Treating attention deficits in chronic stroke patients using Slow Cortical Potential (SCP) Neurofeedback Movements of the same upper limb can be classified from low-frequency time-domain EEG signals Beyond the control: idle state detection in human intracortical Brain-Computer Interfaces Sensorimotor Rhythm BCI with Simultaneous High Definition-Transcranial Direct Current Stimulation Alters Task Performance Lateralization patterns for movement execution and imagination investigated with concurrent EEG-fMRI and EEG-fNIRS Intracortical Microstimulation as a Feedback Source for Brain-Computer Interface Users Separable decoding of cue, intention, and movement information from the fronto-parietal grasping-network Neurophysiological correlates of mind-wandering, towards a predictive BCI-based Neurofeedback BCI controlled neuromuscular electrical stimulation enables sustained motor recovery in chronic stroke victims Attentional processes during P3-based Brain Computer Interface task in amyotrophic lateral sclerosis patients Combining Methods To Predict Accuracy of Individual Brain-Computer Interface Selections Improving Memory Performance Using a Wearable BCI For more informations press here.