Paper Reading #27: Sensing cognitive multitasking for a brain-based adaptive user interface

References
Sensing cognitive multitasking for a brain-based adaptive user interface by Erin Treacy Solov, Francine Lalooses, Krysta Chauncey, Douglas Weaver, Margarita Parasi, Matthias Scheutz, Angelo Sassaroli, Sergio Fantini, Paul Schermerhorn, Audrey Girouard, Robert J.K. Jacob 

Author Bios

• Erin Treacy Solov is a postdoctoral fellow in the Humans and Automation Lab (HAL) at MIT. 
• Francine Laloosesis a PhD candidate at Tufts University and has a Bachelor's and Master's degree from Boston University
• Krysta Chauncey is a post doctorate researcher at Tufts University
• Douglas Weaver has a doctorate degree from Tufts University
• Margarita Parasi is working on a Master's degree at Tufts University
• Angelo Sassaroli is a research assistant professor at Tufts University and has a PhD from the University of Electro-Communication
• Sergio Fantini is a professor at Tufts University in the Biomedical Engineering Department
• Paul Schermerhorn is a post doctorate researcher at Tufts University and has studied at Indiana University
• Audrey Girouard is an assistant professor at The Queen's University and has a PhD from Tufts University
• Robert J.K. Jacob is a professor at Tufts University

Summary

• Hypothesis
• Cognitive multitasking is a common element in daily life, and the researchers' human-robot system can be useful in recognizing these multitasking tasks and assisting with their execution.
• Methods 
• The first experiment was designed to highlight three conditions: delay, dual-task, and branching.  The participants interacted with a simulation of a robot on Mars, sorting rocks.  Based on the pattern/order of rock classification, measure data related to each of the three conditions listed above.  
• The second experiment was used to determine whether they could distinguish specific variations of the branching task.  Branching was divided into to categories: Random branching and predictive branching, and the experiment followed the same basic procedure as the first experiment.  However, here there were only two experimental conditions.
• Results
• In the first experiment, statistical analysis was performed and all variables were tested for normal distribution.  There was statistical significance in response time between delay and dual, delay and branching, but not between dual and branching.  Correlations between accuracy and response time were not significant, and they did not find a learning effect. 
• As in the first experiment, the second experiment also collected data about response time and accuracy and statistical analysis was performed.  There was no statistically significant difference in response time between random and predictive branching, nor was there a significant difference in accuracy.  Additionally, there was no correlation between accuracy and response time for random branching, but there was a correlation under predictive branching.
• Contents
• This paper describes a study done to assess cognitive multitasking, and how the human-robot system can have an effect on this process.  It describes some of the related work that has been done in the field and explains how this paper expands on some of the pre-existing work.  It then goes on to describe the experiments carried out to test the effectiveness of the hypothesis.

Discussion

• While I feel that this research was not as resoundingly successful as the researchers had hoped, it does provide a solid stepping stone into further research.  To that end, I think that the authors did achieve their goal.  I think they were very thorough in their research, but they might have gotten more solid results with a larger test subject base.