Distributed Logging and Synchronization of Physiological and Performance Measures to Support Adaptive Automation Strategies
As advances in physiological sensors make them more minimally intrusive and easier to use, there is a clear desire by researchers in the fields of Augmented Cognition and Neuroergonomics to incorporate them as much as possible. To best support use of multiple measures, the data from each sensor must be accurately synchronized across all devices and tied to performance and environment events. However, each sensor provides different sampling frequencies, local timing information, and timing accuracy making data synchronization in logs or real time systems difficult. In this paper, a modular architecture is presented to address the issue of how to synchronize data to support analysis of physiological and performance measures. Specific design requirements are presented to ensure the ability to accurately measure raw sensor data and compute metrics in a distributed computing environment to support adaptive automation strategies in a research environment. Finally, an example system is described which combines multiple minimally invasive physiological sensors.
KeywordsAdaptive Automation Closed-Loop Training System Data Synchronization
Unable to display preview. Download preview PDF.
- 1.Vartak, A.: Cognative State Estimation for Adaptive Learning Systems Using Wearable Physiological Sensors. In: 1st International Conference on Biomedical Electronics and Devices (2008)Google Scholar
- 2.Sciarini, L.W.: Assessing Cognitive State with Multiple Phyiological Measures: A Modular Approach. In: Human-Computer Interaction International, pp. 533–542 (2009)Google Scholar
- 3.Fidopiastis, C.M.: Impact of Automation and Task Load on Unmanned System Operator’s Eye Movement Patterns. In: Human-Computer Interaction Interntional, pp. 229–238 (2009)Google Scholar
- 4.Barber, D.: The Mixed Initiative Experimental (MIX) Testbed for Human Robot Interactions with Varied Levels of Automation. In: 26th Army Science Conference, Olrando (2008)Google Scholar
- 5.Nicholson, D.: An Adaptive System for Improving and Augmenting Human Performance. In: Foundations of Augmented Cognition, pp. 215–222. Strategic Analysis, Inc., Arlington (2006)Google Scholar
- 6.Camilli, M.: ASTEF: A simple tool for examining fixations. Behavior Research Methods, 373–382 (2008)Google Scholar
- 7.Nilsson, J.: Implementing a Continuously Updating High-Resolution Time Provider for Windows. In: Microsoft, http://msdn.microsoft.com/en-us/magazine/cc163996.aspx (accessed March 2004)
- 8.Committee, A.-4.: JAUS Core Service Set. In: Society for Automotive Enginers. HYPERLINK, http://www.sae.org/technical/standards/AS5710 (accessed December 2008)