This complete system includes the B-Alert X10 for wireless acquisition of 9 channels of high fidelity EEG plus ECG, and AcqKnowledge software with powerful analysis tools, including automated scoring and reporting options, and B-Alert Cognitive State software. The B-Alert X10 mobile-wireless EEG system delivers real-time measurements for a variety of research and engineering applications, including closed-loop performance monitoring and simulation training; HCI design assessment; situational awareness and team dynamics monitoring; tools for productivity and training enhancement; and fatigue management
Set up in less than 5 minutes
Comfortable and nonintrusive—low profile fits comfortably under headgear
Data quality monitoring and feedback simplifies acquisition for non-technical personnel
Cognitive state classification for engagement, confusion/distraction, drowsiness, workload and stress
Patented real-time artifact decontamination
Standard Signals
9 mono-polar EEG with impedance 2-lead ECG Heart rate PSD by channel
Optional signals
Differential signals for B-Alert and workload
Plus—Classify Cognitive States
This system includes the B-Alert Cognitive State software with proprietary metrics for real-time monitoring of subject fatigue, stress, confusion, engagement and workload (classify data from B-Alert Wirless EEG systems). The GUI intuitively represents both the raw and processed data for easy understanding by even the untrained user and up to six systems can run simultaneously on a single PC— Windows 7/XP OS only.
To facilitate both real-time and offline analysis, the B-Alert gauges are fully customizable to fit the requirements of the user. In the standard format (shown below), the easy-to-read dashboard gauges ( Top Left) and time series ( Bottom) windows present B-Alert's highly validated second by second metrics: Engagement, Workload and Drowsiness (along with Heart Rate). Heat maps ( Top Right) display EEG power spectral densities (PSD) in both spatial and temporal maps for the traditional Hz bands (Beta, Alpha, Theta, Sigma).
B-Alert Wireless EEG bio-metrics are normalized to an individual subject using 5-minutes of baseline data from three distinct tasks with the sleep onset class predicted from the baseline PSD values. A probability-of-fit is then generated for each of the four classes for each epoch with the sum of the probabilities across the four classes equaling 1.0 (e.g., 0.45 high engagement, 0.30 low engagement, 0.20 distraction and 0.05 sleep onset). Cognitive State for a given second represents the class with the greatest probability. B-Alert cognitive state metrics are derived for each one-second epoch using 1 Hz power spectra densities (PSD) bins from differential sites FzPO and CzPO in a four-class quadratic discriminant function analysis (DFA) that is fitted to the individual’s unique EEG patterns. The table below identifies and briefly describes each baseline task, and associates the task with the B-Alert classification.
• B-Alert peer-reviewed metrics validation: Johnson, R.R., et al., Drowsiness/alertness algorithm development and validation using synchronized EEG and cognitive performance to individualize a generalized model. Biol. Psychol. (2011), doi: 10.1016/j.biopsycho.2011.03.003. Click here to request a copy.
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