A Aldo Faisal

O Tonet

William W Abbott

BMC Neuroscience

English

PubMed

Springer - Publisher Connector

POSTER PRESENTATION Open Access
Ultra-low cost eyetracking as an high-information
throughput alternative to BMIs
William W Abbott1, A Aldo Faisal1,2*
From Twentieth Annual Computational Neuroscience Meeting: CNS*2011
Stockholm, Sweden. 23-28 July 2011
Advancement in Brain machine interfaces (BMIs) holds
the hope to restore vital degrees of independence for
patients with high-level neurological disorders, improv-
ing their quality of life while reducing their dependency
on others [1]. Unfortunately these emerging rehabilita-
tive methods come at considerable clinical and post-
clinical operational costs, beyond the means of the
majority of patients [1]. Here we consider an alternative:
eye movements. Eye movements provide a feasible alter-
native BMI basis as they tend to be spared degradation
by neurological disorders such as Muscular dystrophy,
high-level spinal injuries and multiple sclerosis because
the Occululomotor system is innervated from the mid-
brain rather than the spinal column. Eye tracking and
gaze based interaction is a long established field, how-
ever cost, accuracy and effective system integration have
meant these systems are not widely used. We have
developed an ultra-low cost 3D gaze-tracker based on
mass market video game equipment that matches the
performance of commercial systems 500 times as
expensive.
We developed a calibration method for 3D eye gaze,
that requires only a standard computer monitor as
opposed to 3D equipment, no information on eye geo-
metry, and allows free head movement following calibra-
tion. Our method enables us to track eye movements off
the computer screen, e.g. to drive a wheel chair or the
end-point of a prosthetic arm. Unlike other BMIs, train-
ing is virtually unnecessary as the control intention can
be taken from natural eye movements. By tracking both
eyes, a significantly higher information rate can be
obtained both by making 2D gaze estimates more accu-
rate and by adding another spatial dimension in which
to make commands. Our ultra-low cost 3D eye tracking
system operates at below 50 USD material cost with 0.5-1
degree resolution at 120 Hz sample rate, we achieved this
by reverse engineering mass-marketed video console com-
ponents. This high-speed accuracy allows us to drive a
mouse cursor at this performance level in real-time at a
data rate of over 1100 bits/s, while capturing depth allows
us, in theory to drive a continuous control user interface
at a multiple of that rate. These information rates are
orders of magnitude times higher than other BMI
approaches e.g. non-invasive cortical methods (maximum
1.63 bits/sec) such as Electroencephalography (EEG),
Magnetoencephalography (MEG), functional Magnetic
Resonance imaging (fMRI), and Near Infrared Spectro-
scopy (NIRS); Cortical Invasive methods (maximum 3.30
bits/sec) such as MEAs and EcOG and non-cortical non-
invasive methods (maximum 6.13 bits/sec) such as EMG,
Speech Recognition and Mechanical Switches[1,2]. Thus,
our delay free, real-time control is suitable to allow paral-
yzed patients to play live action video games, as we
recently demonstrated to the public[3]. Moreover, the
novel approach of using 3D point of gaze makes the users
interaction with their surroundings more intuitive, without
detracting from the eye’s sensory function. A potential
example, in a wheelchair context, is that the user simply
looks where they would like to drive. With this low cost
device and the rich 3D gaze information we provide an
extremely intuitive and non-intrusive BMI alternative that
can be developed that is economically accessible to
patients in the developed and the developing world.
Author details
1Department of Bioengineering, Imperial College London, London, SW7 2AZ,
UK. 2Department of Computing, Imperial College London, London, SW7 2AZ,
UK.
Published: 18 July 2011
* Correspondence: aldo.faisal@imperial.ac.uk
1Department of Bioengineering, Imperial College London, London, SW7 2AZ,
UK
Full list of author information is available at the end of the article
Abbott and Aldo Faisal BMC Neuroscience 2011, 12(Suppl 1):P103
http://www.biomedcentral.com/1471-2202/12/S1/P103
© 2011 Abbott and Aldo Faisal; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative
Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and
reproduction in any medium, provided the original work is properly cited.
References
1. Hochberg L, Nurmikko A, Donoghue JE: Brain Machine Interface. Annual
Rev of Biomedical Eng , 13.
2. Tonet O, et al: Defining brain–machine interface applications by
matching interface performance with device requirements. J Neurosci
Methods 2008, 167:91-104.
3. [http://www.youtube.com/watch?v=9gU8RqttXeo].
doi:10.1186/1471-2202-12-S1-P103
Cite this article as: Abbott and Aldo Faisal: Ultra-low cost eyetracking as
an high-information throughput alternative to BMIs. BMC Neuroscience
2011 12(Suppl 1):P103.
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Abbott and Aldo Faisal BMC Neuroscience 2011, 12(Suppl 1):P103
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Ultra-low cost eyetracking as an high-information throughput alternative to BMIs

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Defining brain–machine interface applications by matching interface performance with device requirements.

Submit your next manuscript to BioMed Central and take full advantage of: • Convenient online submission • Thorough peer review • No space constraints or color ﬁgure charges • Immediate publication on acceptance

http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3240194

Ultra-low cost eyetracking as an high-information throughput alternative to BMIs

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