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Defense Intelligence Reference Document Technological Approaches To Controlling

Defense Intelligence Agency · 36 pages · text from the file's own layer

This Defense Intelligence Reference Document from the Defense Intelligence Agency, dated 23 March 2010, was produced under the Advanced Aerospace Weapon System Applications (AAWSA) Program. It surveys invasive and noninvasive brain-machine interface technologies for controlling external devices without limb-operated interfaces. The technologies covered include EEG, MEG, fMRI, NIRS, and implanted electrode arrays. It concludes that noninvasive electrical monitoring is the most promising near-term approach. In the long term, it favors invasive single-neuron cortical connections that use optical stimulation or chip-based arrays.

  • p. 36 …50 Martinez Santiesteban FM, Swanson SD, Noll DC, Anderson DJ. Magnetic resonance compatibility of multichannel silicon…
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data is averaged over several electrodes time-locked to a stimulus (Reference 19). Both
the previous methods record summed electrical activity of nominally 50,000 local
neurons, thus large coherent group spiking activity7 is required to produce appreciable
signal.
EEG
EEG-based BMI systems use pattern recognition among the several electrodes to
transmit information. In closed-loop systems, audio or visual feedback is utilized.
Training on the system and adaptation by the processing software can increase target
detection efficiency, though some recent work shows that systems can be produced
that nearly work right out of the box. Blankertz demonstrated a system that required
only 20 minutes of training on na'ive subjects (Reference 20).
Development is partially being driven by the need to provide a means of communication
or action on the environment to patients that have lost control of their body. Much of
this clinically-orientated research has focused on 'locked-in' patients, who suffer from
total paralysis following brainstem stroke or degenerative diseases such as amyotrophic
lateral sclerosis (ALS) (Reference 21). The goal has been to extract control signals
either from surface EEG signals or from electrodes implanted near or within the cerebral
cortex: ECoG (see next section on invasive technologies for details on ECoG). ALS
deteriorates peripheral motor function before progression to cognitive areas. This
greatly reduces a primary source of bioelectric noise, cranial and facial muscle action,
and thus provides a reduced signal processing problem to decode neural signals.
Successful communication has been established via EEG BMI in several studies based
on both spiking activity and P300 signals (References 22-25). The response time to
execute a command using these systems is measured in seconds. The results from ALS
patients represent a best-case scenario for what could be accomplished using EEG-only
sensors in a normal, healthy human who would have significant muscle noise to sift
through.
The number of electrodes and the time-consuming application of conducting gel make
EEG arrays bulky and slow to put on. An improvement would be a reduction in the
number of electrodes, typically a few dozen for traditional EEG, and electrodes that
could operate without conducting gel. Commercial versions of dry-electrode devices are
being released on the market from companies such as Neurosky, OCZ Technology, and
Emotiv. 8 The Neurosky and Emotive systems claim proprietary processing algorithms,
lack peer-reviewed literature supporting their claims, and even discuss using facial
muscle movement to send signals (References 26, 27), raising doubt about whether
neural signals are being measured at all. The NIA, for Neural Impulse Actuator, from
OCZ clearly states that the electrodes pick up a combination of EEG, EMG, and EOG, 9
and that the algorithm is only interpreting the net signal patterns instead of trying to
sort out the EEG component.
7 Spiking activity is the term used for recognition of action potentials. Spikes are fast and easy to recognize with
electronic triggering circuits, while more complex waveforms require additional processing.
~ Websites www.emotiv.com, www.ocztechnology.com, and www.neurosky.com, last accessed 12 May 2009.
9 The electrco-myogram (EMG) reads signals from muscle activity, in this case facial muscles. The electro-
oculogram (EOG) measures electrical signals arising from muscles associated with the eyes.
7
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Report, from the dia collection. The PDF is mirrored here; the original link is above. 36 pages are in the text index: search them above, or from the library's search.