Paper Reading #27

Sensing cognitive multitasking for a brain-based adaptive user interface

 

Authors:	Erin Treacy Solovey	Tufts University, Medford, Massachusetts, USA
	Francine Lalooses	Tufts University, Medford, Massachusetts, USA
	Krysta Chauncey	Tufts University, Medford, Massachusetts, USA
	Douglas Weaver	Tufts University, Medford, Massachusetts, USA
	Margarita Parasi	Tufts University, Medford, Massachusetts, USA
	Matthias Scheutz	Tufts University, Medford, Massachusetts, USA
	Angelo Sassaroli	Tufts University, Medford, Massachusetts, USA
	Sergio Fantini	Tufts University, Medford, Massachusetts, USA
	Paul Schermerhorn	Indiana University, Bloomington, Indiana, USA
	Audrey Girouard	Queen's University, Kingston, Ontario, Canada
	Robert J.K. Jacob	Tufts University, Medford, Massachusetts, USA

 

Proceeding  

CHI '11 Proceedings of the 2011 annual conference on Human factors in computing systems 

 

 

 Summary

• Hypothesis - The researchers want to prove that fNIRS is a reliable way to measure brain states and to test the amount of stress different types of multitasking has on participants. 
• Content - FNIRS stands for functional near-infrared spectroscopy. It directly measures the oxygenation of the blood in the brain to determine how much stress user's brain is exhibiting. Multitasking is broken up into 3 possible scenarios, each with a different amount of stress on the brain. 

1. Branching - Changing focus to another task requires keeping a state memory of the tasks. 
2.  Dual Task - Changing focus to another task does not require keeping a state memory. 
3.  Delay - The interfering task can be ignored until the first task is done. 

• Methods - The researchers tested the three types of multitasking with different scenarios of problem solving involving directing a robot explorer. Delay multitasking was tested by asking the participant whether two successive rock classifications follow in immediate consecutive order. Getting a message about distance can simply be ignored. Dual Task was handled by duplicating the circumstances of delay, but with focus being on both distance and rock classification. Only an immediate change in the current type of message required attention. Branching was tested by requiring the participant to remember the previous states of each message. 12 participants were selected. Each participant practiced the system before hand to get used to the multitasking environment before using the fNIRS equipment. 
• Results - Delay tasks were the most accurate and done the quickest. The slowest and least accurate was the branching test. The stresses caused by multitasking were easily seen by the fNIRS data, showing the greatest amount of oxygen depletion with branch-type multitasking.

Discussion
I find myself multitasking all the time. Using these principles if I created scenarios where I worked with delay-based multitasking primarily, I could theoretically become 26% more efficient according to the timing data collected. However, I'm fairly certain with the relative newness of computation in society in regards to evolutionary time, there is a very likely chance that a distinct evolutionary pressure is being put on people who can multitask more efficiently. In the mean time, technology such as fNIRS can be used to minimize "harmful" types of multitasking that our brains can not fully handle yet.