Defense Intelligence Reference Document Technological Approaches To Controlling

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The remainder of discussion concentrates on the surveyed studies into five technology
areas, and listing their advantages and disadvantages, as well as their critical barriers
to further development and likely future paths of research.
NONINVASIVE ELECTRICAL DEVICES
The current state-of-the-art BMI devices that have shown the most promise in the near
term utilize muscle amplification of the neural signal. This is the result of commercial
investment in development. These primarily EMG based systems are noninvasive
connections to existing or constructed nerve-muscle pairs. Neurally operated
prosthetics have been demonstrated such as the artificial hand. Decoding algorithms
are nearly as fast as muscle response itself at selecting 1 of 10 actions. Commercial
products for entertainment are available for normal, healthy consumers. These
entertainment devices contain few sensors but make use of more complex decoding
algorithms. All sensors don't just turn on and off, rather they can relay amplitude,
polarity, and frequency of muscle action, as well as detect underlying spiking signals
from neurons. This combination, along with algorithms developed from a support vector
machine, will allow device selection of many more actions than the simple binary
combinatorics of the number of sensors. The gaming market will drive this noninvasive
technology in the next 5 years with advances in signal processing from current sensors.
The EMG based systems can be scaled to a large number of sensors for a more complex
control task. It has been demonstrated with amputees the feasibility to move existing
nerves around to control existing muscles. There has not been a study yet to explore
how many nerve-muscle pairs may be available for such use in a normal human, with
or without reinnervation. Such a study could be done theoretically based on current and
near term work with patients. The longer term for EMG will likely evolve toward very
small, wireless chronic implants that operate near the skin surface and are easy to
install and remove.
Devices based solely on noninvasive detection of EEG signals from the cortex in normal,
healthy individuals are unlikely in the next 5 years. This is primarily because of muscle
noise filtering issues which will need to be solved through development of better EMG
sensors and detection algorithms mentioned above. Even though such devices have
been shown to work in laboratory settings, moving them to the arbitrary conditions in
naturalistic settings introduces significant complication to signal detection and filtering
that greatly limits the information transfer bandwidth to a fraction of the target 5
bits/sec. Also an issue is the origin of surface EEG signals, which are still under
theoretical study even after 80 years. Some of the frequency bands directly related to
spiking activity in axons are somewhat understood, but the whole of the signals contain
many transients that are likely the more interesting and possibly more robust parts of
brain activity. In the medium to long term, many applications are envisioned in surface
or near surface detection of cortical spiking activity or ERP, once the background
separation issue in naturalistic environments is addressed. However, these signals still
require localized coherent firing of tens of thousands of neurons, a biological
requirement that has limited the information transfer rates of these techniques to 1
bit/sec or less, which is well below target rates but could be useful for some
applications.
One can suppose an ultra-high density EEG, thousands of sensors with wireless micro
probes embedded subcutaneously that track electrical activity and relative location
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