Paper Reading #16: Using fNIRS brain sensing in realistic HCI settings: experiments and guidelines

Comments

Cindy Skach
Erin Schuchardt

Reference Information

Title: Using fNIRS brain sensing in realistic HCI settings: experiments and guidelines

Authors:Erin Treacy Solovey  Tufts University, Medford, MA, USA 
             Audrey Girouard  Tufts University, Medford, MA, USA 
             Krysta Chauncey  Tufts University, Medford, MA, USA 
             Leanne M. Hirshfield  Tufts University, Medford, MA, USA 
             Angelo Sassaroli  Tufts University, Medford, MA, USA 
             Feng Zheng  Tufts University, Medford, MA, USA
             Sergio Fantini  Tufts University, Medford, MA, USA 
             Robert J.K. Jacob  Tufts University, Medford, MA, USA 

Presentation Venue: UIST 2009: 22nd annual ACM  symposium on User interface software and technology; Date: 2009;
Location: New York, NY, USA

Summary
This paper deals with Functional Near-infrared Spectroscopy (fNIRS). In a nutshell, fNRIS measures the oxygen content of blood in the brain. It sends near-infrared light through the skull to a depth of 1.5 - 3 cm. This light is absorbed by both oxygenated hemoglobin and un-oxygenated hemoglobin and reflected back to sensors located near the light source. The data received from the sensors creates a cognitive state, which describes which sections of the brain are active.

 

As background, the authors give us some of the brain imaging techniques in use today:

• Functional Magnetic Resonance Imaging (fMRI) which is very effective in neural imaging, however does not do a good job when it comes to head movement. The slightest head movement results in corrupted images. In addition, the use of magnetic fields forbids the use of metal objects near the head.

 

• Electroencephalography (EEG). It also falls short as a viable solution because it requires participants to put gel in their hair. Since fNIRS does not require gel and is portable, the researchers believe it is the best brain imaging technique to be used in HCI.

Some historical background given by the paper reveals that brain imaging devices have been traditionally designed for disabled users, many of which paralyzed to receive special training. For the uses of HCI, the aim is to implement some type of cognitive control system. This explains the need to make the current available technology portable, and catered to things like head movement. A series of experiments have been performed to test the effects of these different sources of interference called artifacts. They focused on reading brain activity while the subject did nothing, used the mouse, used the keyboard, moved its head, made facial expressions.

They found that using the mouse and keyboard produced little or no interference with the fNIRS reading, where as head movement and facial expressions made the readings incomprehensible.

Based on these findings during the experiments the team outlined a set of guideline for using fNIRS in HCI. Future improvements may include using a chin rest so major head movements can be avoided and adding an accelerometer to the device so that head movements can be detected.

Discussion

This paper gave me a good introduction to brain imaging though I am a Computer Engineering major. This is a multidisciplinary project, that presents some good methods for reducing noise in fNIRS data. As mentioned in the paper, issues like a person's head movement will need to be resolved though. I do feel, however, that the authors of this paper have done effective work in laying down the foundation for future work on fNIRS. Future work, from this point, should be interesting. I am eager to see if we will ever be able to control our computers solely from the mind.