Current brain-computer interface (BCI) systems utilizing the P300 Speller can provide an effective means of communication for locked-in patients if the patients are willing to spend considerable time training to use the system and are willing to accept a fairly slow communication rate. The overarching goal of this research is to transition current P300 Speller BCI systems from research labs to clinical use by increasing system robustness, increasing the communication rate achieved by the patient, and reducing the time required to train the patient to use the system. In the R21 phase of this work, three variations on the standard speller and training paradigm will be evaluated for their potential to achieve these goals: 1) improved real-time stimulus selection via optimal experiment design, 2) channel selection using feature selection techniques, and 3) improved communication rates via the sequential detection of P300 responses. At the completion of the R21 phase, these approaches have the potential to substantively improve communication rates, improve robustness, and increase accuracy in a set of normal subjects. In the R33 phase of this effort, we propose to evaluate the impact of our R21 developments in subjects with disabilities. Specifically, we will begin by assessing the impact of the baseline and improved speller system on subjects with disabilities while operating the system in a clinical environment. Using lessons learned from these subjects in the clinical environment, we will begin testing the baseline and improved system in the home environment. The goal of this phased development and proof of concept effort is to transition the current P300 speller system which operates fairly well in a research environment into a tool that can be used in the home environment by the clinical population for which it was developed. At the successful completion of this R21/R33 effort, an Augmentative and Alternative Communication (AAC) device that can be used in the home by ALS patients with robust and accurate performance will have been demonstrated and should be ready to begin a commercialization phase. While research and laboratory systems exist currently that are based on the P300 speller paradigm, they have not been successfully transitioned to the clinic, or the home. The goal of this effort is to effect that transition from research platform to clinically relevant AAC device prescribable by a clinician. In addition to providing a more powerful research tool in the clinic, ALS subjects would be able to communicate in a robust and accurate fashion in the home.
Severe developmental and acquired communication disabilities affect individuals of all ages, and prevalence estimates of people requiring AAC support range from 8 to 12 persons per 1000 for English speaking countries. While augmentative and assistive communication systems are available clinically, individuals affected by severe physical limitations, such as those caused by amyotrophic lateral sclerosis (ALS) or brain stem stroke, may not have the physical ability required to use these devices. Successfully overcoming the limitations of current P300 Speller systems, which are based on processing EEG signals, and transitioning these systems into the clinic and home will allow these individuals access to a communication aid that does not limit their vocabulary and allows them to maintain connection, independence and self determination.
|Sprague, Samantha A; McBee, Matthew T; Sellers, Eric W (2016) The effects of working memory on brain-computer interface performance. Clin Neurophysiol 127:1331-41|
|Mainsah, Boyla O; Morton, Kenneth D; Collins, Leslie M et al. (2015) Moving Away From Error-Related Potentials to Achieve Spelling Correction in P300 Spellers. IEEE Trans Neural Syst Rehabil Eng 23:737-43|
|Mainsah, B O; Collins, L M; Colwell, K A et al. (2015) Increasing BCI communication rates with dynamic stopping towards more practical use: an ALS study. J Neural Eng 12:016013|
|Sellers, Eric W; Ryan, David B; Hauser, Christopher K (2014) Noninvasive brain-computer interface enables communication after brainstem stroke. Sci Transl Med 6:257re7|
|Mainsah, Boyla O; Colwell, Kenneth A; Collins, Leslie M et al. (2014) Utilizing a language model to improve online dynamic data collection in P300 spellers. IEEE Trans Neural Syst Rehabil Eng 22:837-46|
|Colwell, K A; Ryan, D B; Throckmorton, C S et al. (2014) Channel selection methods for the P300 Speller. J Neurosci Methods 232:6-15|
|Sellers, Eric W (2013) New horizons in brain-computer interface research. Clin Neurophysiol 124:2-4|
|Jin, Jing; Sellers, Eric W; Zhang, Yu et al. (2013) Whether generic model works for rapid ERP-based BCI calibration. J Neurosci Methods 212:94-9|
|Jin, Jing; Sellers, Eric W; Wang, Xingyu (2012) Targeting an efficient target-to-target interval for P300 speller brain-computer interfaces. Med Biol Eng Comput 50:289-96|
|Ryan, D B; Frye, G E; Townsend, G et al. (2011) Predictive spelling with a P300-based brain-computer interface: Increasing the rate of communication. Int J Hum Comput Interact 27:69-84|
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