Contributions to Driving Ergonomics
and Fatigue Assessment Studies

All of the core characteristics of the B-Alert wireless-EEG headsets andsoftware make them ideal for driving ergonomics and fatigue assessment
studies. In addition to the medical-grade, dependable signals delivered in
portable, ease-to-use and comfortable-for-hours designs, here are somekey features to consider:
1) The B-Alert Cognitive State Metrics
2) Previous Examples of Research & Outcomes3) Extensive Synchronization & Integration Capabilities
B-Alert X4

1) The B-Alert Cognitive State Metrics
All B-Alert headsets run the second-by-second, real-time Cognitive State Metrics which classify each subject’s levelof engagement, distraction and fatigue. Researchers can integrate the Metric outputs directly into their own
analysis and/or custom algorithm research. There are peer-reviewed and validated publications frominternationally accredited scientific journals which outline how the Metrics were developed and tested across large
1and diverse subject populations.
The Cognitive State Metric classifications constitute a continuum from highly engaged & processing sensory inputs
on down to fatigue onset. The Metrics reflect how subjects are processing visual stimuli by assessing a
combination of their alertness & focus levels plus the presence of a stimulating environment. High Engagement
reflects how comprehensive motor skill and executive resources are being exercised. Low engagement occurs
when the amount of sensory scanning & processing decreases (e.g. when driving along monotonous road). Distraction occurs with disengagement from active sensory
processing; typically resulting from boredom or fatigue-related inabilities. Drowsy andSleep Onset occur when subjects exhibit EEG signs of fatigue.
To be clear, there are four total classification and the combined probabilities of allthem added up to equal 1 (i.e. 100%). The model was built by sampling EEG during avariety of highly engaging (mostly visual) & boring tasks during fully-rested and sleepdeprived conditions, so each subject's EEG is matched against the database toestimate states. There is always an interaction between the current state of thesubject (how rested are they) and the environment or activity. For example, a sleepdeprived person given a stimulating gaming task may have some period of time where
they return to high engagement before returning to a drowsy state.

B-Alert Large Payload Trucks Recordings
South Africa - July 2011

B-Alert Cognitive Metrics
Software GUI2) Previous Related Research & Outcomes
B-Alert wireless-EEG systems have been used in several humanperformance research studies over the past decade. The first B-Alertproduct was a drowsiness alarm system for the long haul trucking
community. Its development included multiple in laboratory
simulation studies as well as several on-the-road field tests, fundedthrough NIH initially, and later through ONR. Early studies utilized astandard EEG system to collect data on n=160 subjects while
completing a series of tasks that required variable levels of attention
and engagement, under both fully rested and sleep deprived

conditions. Using these data sets, along with data collected as persons were allowed to try to sleep, a four classmodel describing the alertness spectrum from sleep-onset to highly-engaged was developed. During this time, thefirst B-Alert portable, wireless system, requiring only 3 sensors, and 2 differential channels for the algorithm wasalso developed. The combined system was tested using a STISIM driving simulation that included a 45 min session
partitioned into 20-25 minutes of monotonous driving and 20-25 minutes of complex driving, ordercounterbalanced across participants. Using the sleep onset and distraction probabilities of the B-Alert alertness
algorithm, a metric of drowsiness was developed. When examining error rates in each driving session, thedrowsiness probabilities correlated positively and significantly with errors occurring during driving. Driving errors
included: collisions, lane departures, running stop signs, etc. In addition, alarms driven by the algorithm weredeveloped that effectively delayed fatigue related errors by up to 30 minutes.
Research teams have conducted additional studies with commercial
partners including Caterpillar, Daimler, and Yellow Trucking in parallelto leading several other internal driving simulation studies.
Caterpillar utilized the B-Alert algorithms and EEG monitoring system
to optimize safety interventions and monitoring during use of theirmining equipment. The Yellow Trucking studyled to the developmenta fatigue management program designed to elucidate the potentialcauses of driver fatigue and mitigate the impact of fatigue on driversafety. Because Yellow drivers were primarily middle-aged men(average age = 51) with high BMIs, the most important aspect of theMobile Roadside Assessment Capabilities
program was to identify and treat those with chronic fatigue resulting
from sleep apnea. Daimler executed several studies utilizing B-Alert capabilities. Their work found that the B-Alert
Cognitive State Metric increased with monotonous driving on The Autobahn. They followed this with a closerange, 30 km driving range study to examine how drowsiness effected detection of irregularly placed, rare eventson the course [2].
Internally, Advanced Brain Monitoring has continued to apply B-Alert systems
with STISIM and other colleagues in other driving, flight and othertransportation category studies. At the University of Iowa, the National
Advanced Driving Simulator lab, we examined the effects of drugged driving on
performance as well as fatigue and long distance driving for up to 4 hr. WithSTISIM, through several SBIRs and DoD contracts, we are examining theneuroergonomics of simulation versus real-world flight, as initial evaluation ofthe ecological validity of simulations. Finally, we are collaborating with the HIV
Neurobehavioral Research Program at the University of California- San Diego toLive Flight Recording with B-Alert
examine how B-Alert may add explanatory value in evaluation of driving
capability in the HIV population that develops cognitive deficits (up to 50%), as simulations alone have been foundinadequate to determine capabilities.
In 2012, a team of researchers at Nissan Automotive purchased multiple B-Alert systems for their internal car
ergonomics development studies.
3) Extensive Synchronization & Integration Capabilities
The B-Alert systems always include the complete Software Developers’ Kit (SDK) for integrating raw and processedsignals across existing platforms. The systems were designed around the philosophy that EEG adds the most value
when it can make sense relative to all data and stimuli so we provide all tools available to researchers. BMW
synchronized B-Alert’s second-by-second outputs with over 400 other real-time data points acquired in an
everyday 3-Series card during their 6 hour real-world highway driving studies. If the integration tool you need isnot yet available, our engineers will work with you to create it.
1Johnson RR, Popovic D, Olmstead RE, Stikic M, Levendowski DJ, Berka C. Drowsiness determination through EEG: development and validation.
Biol Psychol. in press March 2011.