Real-Time Detection of Human Drowsiness via a Portable Brain-Computer Interface

Julia Shen, Baiyan Li, Xuefei Shi
2017 Open Journal of Applied Sciences  
In this paper, we proposed a new concept: depth of drowsiness, which can more precisely describe the drowsiness than existing binary description. A set of effective markers for drowsiness: normalized band norm was successfully developed. These markers are invariant from voltage amplitude of brain waves, eliminating the need for calibrating the voltage output of the brain-computer interface devices. A new polling algorithm was designed and implemented for computing the depth of drowsiness. The
more » ... f drowsiness. The time cost of data acquisition and processing for each estimate is about one second, which is well suited for realtime applications. Test results with a portable brain-computer interface device show that the depth of drowsiness computed by the method in this paper is generally invariant from ages of test subjects and sensor channels (P3 and C4). The comparison between experiment and computing results indicate that the new method is noticeably better than one of the recent methods in terms of accuracy for predicting the drowsiness.
doi:10.4236/ojapps.2017.73009 fatcat:jo6w7h2oavb6td7zaznihhogey