Brain-Computer Interface (BCI) research are emerging in the last few years providing non-invasive, wireless and low-cost ElectroEncephaloGraphy (EEG) devices. The increasing study of neurosciences and the need to respond to specific human brain diseases are two important factors to this evolution.
Follow it in this blog with a readout accessible to everyone.
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
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.
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.
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.
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
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