The EEG-based On-line Closed-loop Lapse Detection and Mitigation system successfully detected fatigue signatures and delivered auditory warnings that improved response times to lane-departure events.
Observational (n=14)
No
Does the OCLDM System improve response times to lane-departure events in subjects experiencing cognitive lapses during simulated driving?
An EEG-based closed-loop system can detect cognitive lapses during simulated driving and deliver auditory warnings that improve response times to lane-departure events.
p-value: p=<0.01
In America, 60% of adults reported that they have driven a motor vehicle while feeling drowsy, and at least 15-20% of fatal car accidents are fatigue-related. This study translates previous laboratory-oriented neurophysiological research to design, develop, and test an On-line Closed-loop Lapse Detection and Mitigation (OCLDM) System featuring a mobile wireless dry-sensor EEG headgear and a cell-phone based real-time EEG processing platform. Eleven subjects participated in an event-related lane-keeping task, in which they were instructed to manipulate a randomly deviated, fixed-speed cruising car on a 4-lane highway. This was simulated in a 1st person view with an 8-screen and 8-projector immersive virtual-reality environment. When the subjects experienced lapses or failed to respond to events during the experiment, auditory warning was delivered to rectify the performance decrements. However, the arousing auditory signals were not always effective. The EEG spectra exhibited statistically significant differences between effective and ineffective arousing signals, suggesting that EEG spectra could be used as a countermeasure of the efficacy of arousing signals. In this on-line pilot study, the proposed OCLDM System was able to continuously detect EEG signatures of fatigue, deliver arousing warning to subjects suffering momentary cognitive lapses, and assess the efficacy of the warning in near real-time to rectify cognitive lapses. The on-line testing results of the OCLDM System validated the efficacy of the arousing signals in improving subjects' response times to the subsequent lane-departure events. This study may lead to a practical on-line lapse detection and mitigation system in real-world environments.
Wang et al. (Mon,) conducted a observational in Fatigue-related cognitive lapses (n=14). On-line Closed-loop Lapse Detection and Mitigation (OCLDM) System with auditory warning vs. No auditory warning was evaluated on Response time to lane-departure events and EEG spectral changes (p=<0.01). The EEG-based On-line Closed-loop Lapse Detection and Mitigation system successfully detected fatigue signatures and delivered auditory warnings that improved response times to lane-departure events.