Name
Abstract | ||
|---|---|---|
The RSVP Keyboard™ is a brain-computer interface (BCI)-based typing system for people with severe physical disabilities, specifically those with locked-in syndrome (LIS). It uses signals from an electroencephalogram (EEG) combined with information from an n-gram language model to select letters to be typed. One characteristic of the system as currently configured is that it does not keep track of past EEG observations, i.e., observations of user intent made while the user was in a different part of a typed message. We present a principled approach for taking all past observations into account, and show that this method results in a 20% increase in simulated typing speed under a variety of conditions on realistic stimuli. We also show that this method allows for a principled and improved estimate of the probability of the backspace symbol, by which mis-typed symbols are corrected. Finally, we demonstrate the utility of automatically typing likely letters in certain contexts, a technique that achieves increased typing speed under our new method, though not under the baseline approach. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1145/2513383.2513453 | ASSETS |
Keywords | Field | DocType |
typing system,improved inference,past eeg observation,simulated typing speed,past observation,baseline approach,typing speed,eeg-based bci typing system,method result,user intent,principled approach,new method,language models,brain computer interfaces | Inference,Symbol,Computer science,Brain–computer interface,Speech recognition,Human–computer interaction,Typing,User intent,EEG observations,Electroencephalography,Language model | Conference |
Citations | PageRank | References |
0 | 0.34 | 5 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Andrew Fowler | 1 | 14 | 0.90 |
| Brian Roark | 2 | 479 | 48.82 |
| Umut Orhan | 3 | 60 | 8.66 |
| Deniz Erdogmus | 4 | 1299 | 169.92 |
| M Fried-Oken | 5 | 65 | 8.39 |