Thought Cubes: Exploring the Use of an Inexpensive Brain-Computer Interface on a Mental Rotation Task

G Michael Poor* Laura Marie Leventhal* Scott Kelley* Jordan Ringenberg* Samuel D. Jaffee** Computer Science Department* Psychology Department**

Bowling Green State University, Bowling Green, Ohio 43402

gmp, leventhal, kelleys, jringen, jaffees@bgsu.edu

ABSTRACT Brain-computer interfaces (BCI) allow users to relay information to a computer by capturing reactions to their thoughts via brain waves (or similar measurements). This “new” type of interaction allows users with limited motor control to interact with a computer without a mouse/keyboard or other physically manipulated interaction device. While this technology is in its infancy, there have been major strides in the area allowing researchers to investigate potential uses. One of the first such interfaces that has broached the commercial market at an affordable price is the Emotiv EPOC™ headset. This paper reports on results of a study exploring usage of the EPOC headset.

Categories and Subject Descriptors D.2.2, H.1.2 [User Interfaces, Human-Information Processing]:

General Terms Human Factors

Keywords Accessibility, brain-computer interaction

1. INTRODUCTION The ability to manipulate objects on a computer screen without use of hands potentially expands access to computing, especially for persons with motor control limitations. BCIs (brain-computer interfaces) tap into cognitive and/or autonomic responses from the user. The inexpensive Emotiv™ EPOC neuroheadset (see Fig. 2) is a “high resolution, neuro-signal acquisition and processing wireless neuroheadset. It uses a set of sensors to tune into electric signals produced by the brain to detect [user] thoughts, feelings and expressions” [1]. EPOC offers other hands-free modalities as well. Until recently, most BCI research has focused on helping disabled people interact with computers. However, current BCI research has moved in two directions, 1) providing alternative means of input to voice or hand press in dangerous or noisy environments (e.g. radioactive environment) [2] and 2) providing an alternative interaction method for video games [2,3]; game control is the primary reason for the development of the EPOC device. [1] With no current usability studies of EPOC, our project is exploratory, focusing on understanding the usage characteristics of the BCI and other hands-free modalities of the device.

Copyright is held by the author/owner(s). ASSETS’11, October 24–26, 2011, Dundee, Scotland. UK. ACM 978-1-4503-0919-6/11/10

2. TASK, PROCEDURES, MATERIALS [4] evaluated a BCI on a task involving spatial information processing. Similarly we evaluated EPOC using the cube comparison task (CCT), a task thought to tap into mental rotation and visualization skills that effectively discriminates between high and low spatial ability along these dimensions. [cf. 5,6,7]. In CCT, a participant (P) is presented with images of two cubes, side by side, with three visible faces on each cube. The P determines whether the cube pairs are definitely different or could be the same. In our interactive version of CCT, the P can rotate the right cube on the three Cartesian axes passing through the faces of the cubes in both clockwise and counterclockwise directions (hereafter, the axes are defined as x, y, and z). In CCT, the P can rotate as many times as he/she wishes. Our stimuli are based on the stimuli used in [5] and consist of six problem types; the problem types differ in the number of degrees of angular disparity between the left and right cubes and perceived difficulty.

Figure 1: Image from CCT task

The CCT is a useful task for exploring interactions: Rotations are clockwise/counterclockwise along the 3 axes so

it is possible to track behaviors at the rotation level. CCT is “context-free” in the sense that there are no experts. Interactive CCT includes selection/rotation of interface

objects.

2.1 Emotiv EPOC Interaction Controls The EOPC has three types of controls: EEG (electroencephalograph) – measured electrical activity in the brain, EMG (electromyograph) – measured electrical activity in facial muscles, and a Gyroscope (controlled by head/neck movements). In our study, three of the six possible CCT rotations were directly available by the EEG control: clockwise x, counterclockwise y and clockwise z (the EPOC Control Panel only allows for a maximum of four EEG inputs to be available at one time and we used only three). All six rotations were available via the EMG controls; six facial expressions were chosen to represent each possible rotation. With the EMG control, rotations

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over an individual axis were controlled by a pair of related expressions: each pair was performed by a different set of muscles to reduce the number of false occurrences. Because G only functions in two dimensions, four rotations, clockwise and counterclockwise x and y axes were used. Any of the six cube rotations were possible with the EEG or G control although some rotations would have required multiple rotations in the opposite direction or a combination of the available rotations.

Figure 2: Emotiv EPOC Device

2.2 Participants and Procedure Seventeen introductory programming students completed the study. Each P took two standardized tests of spatial ability, which were used to generate a composited spatial ability score. Ps received training with the EPOC controls before completing the CCT; we presented the cubes in an oblique projection [6].

2.3 Limitations of the Study The EPOC sacrifices technological sophistication for reduced costs and has fewer scalp contacts than more expensive BCIs, leading to potentially less accuracy from EEG. Also, although CCT involves selection of interface objects, similar to selections of objects in other presentations, CCT itself is a task that involves spatial information processing and limits conclusions that we might make about the general use of the EPOC, especially for tasks involving processing of symbolic and textual information.

3. RESULTS1

Using the median of the composite spatial ability scores, the P pool was split into high and low spatial ability with the three Ps at the median dropped leaving 14 Ps.

Following the procedure of [5,6,7], we analyzed the results from the “same” trials only. In terms of accuracy on the task, the Ps did well, with an average error rate of 12% and unsurprisingly were differentially accurate by problem type (F(2.8, 42.6) = 16.3, p = 0). There were no significant differences in accuracy by spatial ability and as all controls were continuously available, we could not definitely determine which control contributed most to errors.

To understand and compare usage patterns of EEG, EMG and G, we extracted two measures from the history logs of each P: counts of the initiation of rotations by control and problem type and counts of successful rotations by control and problem type. Note that if a P initiated an x rotation and actually made a y rotation, the x rotation would not have been considered successful and would not have been in the count. There were no significant differences in these measures by control. We next divided the number of successful rotations by the number of initiated

1Repeated measures degrees of freedom reflect a Greenhouse-Geisser adjustment.

rotations to yield a sort of efficiency measure for each tool for each problem. The measure is crude – a P could have intended a particular rotation but used the controls incorrectly and the resulting rotation would have been scored as “successful”. The logs also recorded what appear to be a few spurious rotations for the EMG and they were backed out of the calculations. The results are interesting nonetheless. The mean efficiency across the controls is 59% meaning that the Ps successfully completed initiated rotations for about 59% of their tries. We found no significant differences in efficiency.

4. CONCLUSIONS Because our study was necessarily exploratory, we draw conclusions about the use of the EPOC cautiously. First, we found no significant differences by spatial ability on our dependent variables, suggesting that Ps of a variety of spatial abilities could effectively use the EPOC controls. Second, we found the EEG no less responsive than the other 2 controls and Ps used all of the controls about equally. Third, real rotations occurred for about 59% of the attempts across the controls. It seems likely that this relatively low efficiency scores across the controls was a result of a number of factors including unfamiliarity with any of the controls and only one training session before use, the complexities of rotational control for all six axes for EEG and G, and the relative difficulty of the CCT task itself. Whether this efficiency rate is acceptable is difficult to know and acceptability is probably context dependent. We believe that our results begin to demonstrate that Ps could effectively use the BCI component (EEG), but users may choose EEG controls along with the other UI options. For persons with limited motor control, the EPOC could be useful but likely would require additional training on the device and a possible willingness to use all of the controls.

5. ACKNOWLEDGMENTS G. Zimmerman, T. Donahue, M. Mott and B. Tomlinson.

6. REFERENCES [1] Emotiv EPOC (2010) http://www.emotiv.com

[2] Allison, B., Graimann, B., Graser, A. “Why Use a BCI if You Are healthy?” ACE Workshop – Brainplay ’07: Brain-computer Interfaces and Games. 2007. Salzburg.

[3] Nijholt, A. “Turning Shortcomings into challenges: Brain-computer interfaces for games.” Entertainment Computing 1.2 (2009): 85-94

[4] Yoo, S. et al. “Brain-computer interface using fMRI: spatial navigation by thoughts.” NeuroReport 15.10 (2004)

[5] Just, M., Carpenter, P. “Cognitive Coordinate Systems: Accounts of Mental Rotation and Individual Differences in Spatial Ability.” Psychological Review 92.2 (1985): 137-172

[6] Jaffee, S. “Tipping Cubes: The Effect of Projection on Performance and Strategy in a Mental Rotation Task in a Virtual Environment.” Poster. Annual Meeting Midwestern Psychological Association. April 29–May 1 2010. Chicago.

[7] Hippler, R. Klopfer, D., Leventhal, L., Poor, G.P., Klein, B., Jaffee, S.D. “More than Speed? An Empirical Study of Touchscreens and Body Awareness on an Object Manipulation Task.” HCI International 2011. July 9-14, 2011. Orlando, Florida. 33 – 42

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