{"content":[{"text":"Brain Board: A Context Based BCI keyboard","bbox":{"left":0.309412,"top":0.091633,"width":0.381316,"height":0.016611}},{"text":"Jett Hays; Jaylem Brar; Ethan Todd","bbox":{"left":0.357048,"top":0.126628,"width":0.28555900000000006,"height":0.016611000000000015}},{"text":"Part I. Abstract","bbox":{"left":0.117643,"top":0.161623,"width":0.132338,"height":0.016611000000000015}},{"text":"As the world has become increasingly digitized, social relevance and economic viability have \n become dependent upon the ability to push buttons in a complex manner. Keyboards have \n become our link to vast amounts of information and computing power, but they have also \n restricted this access to those with the ability to express thought physically. Our project aims to \n sidestep this dependency through the development a mind-controlled keyboard that is 50% faster \n and 5% more accurate than those currently available. While brain computer interface (BCI) \n keyboards are not a new concept, current implementations suffer from excessive lag times and \n model inaccuracy. The blended method of direct sensing, machine learning, and text analytics we \n propose, is expected to increase the low signal to noise ratio characteristic of EEG data by \n providing autocomplete models and brainwave classifiers with the context of a user’s neural \n activity. If successful, this context-based approach to BCI keyboards will grant the physically \n impaired increased access to the digital age, while simultaneously providing new ground upon \n which the BCI field can stand.","bbox":{"left":0.117585,"top":0.197083,"width":0.7644200000000001,"height":0.225771}},{"text":"Part II: Research Question and Significance","bbox":{"left":0.117585,"top":0.441238,"width":0.368011,"height":0.016610999999999987}},{"text":"While technology blazes a path into a digital future, those with physical disabilities are left with \n a present in which input systems remain reliant upon the complex movement of fingers. An \n alternative keyboard industry has attempted to establish a link between the disabled and \n computers, but current solutions on the market have focused on the ergonomics of a keyboard as \n opposed to attacking the concept of a keyboard itself (NIOSH).","bbox":{"left":0.117585,"top":0.476233,"width":0.7575670000000001,"height":0.08618100000000006}},{"text":"A truly accessible keyboard will not merely make buttons bigger or reformat the QWERTY \n layout, but rather bypass a physical implementation of keys altogether; if you can think, then you \n can type. Research is being done in the area of BCI keyboards, however, previous attempts to \n bridge the divide between disabled humans and computers through noninvasive brain computer \n interfaces have resulted in only tenuous connections fraught with inaccuracies and excessive lag \n times. The current noninvasive standard is about 16 letters per minute (Nagel & Spüler, 2019). \n Invasive BCI implementations have fared better—achieving a ‘typing’ speed of 8-40 WPM— \n but the nature of an invasive process prevents these methods from being accessible alternatives \n to physical keyboards (Goldman, 2017). Our research objective is to develop a noninvasive \n mind-controlled keyboard that is faster and more precise than those currently available through \n a context-based approach. The software-based approach we propose, combined with readily \n available hardware, will decrease the economic and training burden associated with existing BCI \n approaches, while simultaneously providing a high performing model that can be incorporated \n within other virtual keyboard systems that are under development.","bbox":{"left":0.117507,"top":0.581263,"width":0.7613559999999999,"height":0.24305100000000002}},{"text":"Part III: Project Design and Feasibility","bbox":{"left":0.117507,"top":0.842698,"width":0.32675999999999994,"height":0.016611000000000042}}],"images_bbox":[],"images_bbox_not_text_overlap":[]}