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AAWSAP DIRD, Technological Approaches to Controlling External Devices, March 2010

U.S. Department of War · 2010-03-23 · 36 pages · text from the file's own layer

This Defense Intelligence Reference Document was produced by the Defense Intelligence Agency's Defense Warning Office under the Advanced Aerospace Weapon System Applications program and dated 23 March 2010. It surveys noninvasive and invasive brain-machine interface technologies, including EEG, MEG, fMRI, NIRS and implanted electrode arrays, that could control external devices without limb-operated interfaces. It concludes that noninvasive electrical monitoring is the most promising near-term approach. For the long term it favors invasive single-neuron cortical connections.

From the source: Release of 2026-09-18 Incident: 3/23/10, Las Vegas, Nevada. Released with redactions. This document is a Defense Intelligence Reference Document (DIRD), a technical reference format used by the Defense Intelligence Agency (DIA) to capture baseline knowledge on a specific topic for later analytic use. DIRDs are best understood as reference and synthesis products rather than as original research. It is one of 38 DIRDs produced under the Advanced Aerospace Weapon System Applications Program (AAWSAP) between 2009 and 2011. Because AAWSAP’s scope permitted a broad range of supporting topics, not every DIRD in the series directly concerns aerospace systems or future threat assessment. The following summary reflects the DIRD’s scope and framing at the time of writing and should not be read as implying current validation of the concepts discussed. This DIRD surveys brain-machine interface technologies intended to allow users to control external devices without conventional manual controls, and it evaluates both noninvasive and invasive approaches for turning neural or related physiological signals into usable commands. The report reviews the underlying neural signals, distinguishes between open- and closed-loop control systems, and examines technologies including scalp-based electrical recording, magnetic and imaging-based methods, and implanted cortical interfaces, with particular attention to bandwidth, response time, signal quality, and practical usability. It concludes that, in the near term, the most practical systems are likely to be noninvasive electrical approaches that draw heavily on muscle and neural signals, while longer-term high-bandwidth control would likely require more advanced invasive interfaces capable of robust two-way communication with individual neurons. The document presents thought-based control of external devices as a research field with plausible assistive and specialized applications, while emphasizing that naturalistic, high-performance control remained constrained by major technical and physiological limits.

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Technological Approaches to Controlling External Devices
in the Absence of Limb-Operated Interfaces
Introduction
Since the advent of modern interactive control of computers, technologies
have been sought to directly connect the biological and the physical to form a
seamless entity. While science fiction explores the possibilities of shared
consciousness between brains and mainframes, real-life scientists work
toward an equally fantastic but more pedestrian goal of eliminating required
electromechanical human-machine interfaces (HMis). Such technologies
promise integration of thought and computer-controlled action, without the
need for a limb-operated device to translate intent from physiological
networks to physical circuits.
This paper first briefly reviews underlying neural structure, function, and
activity to provide background on the type of signals and the scale of temporal
changes that arise from conscious control within the nervous system. A short
primer on brain-machine interfaces (BMis) is included at the end of the
background material. This is followed by a survey of the state-of-the-art
detection and stimulation technologies available utilizing noninvasive and
invasive methods, including several studies that exemplify research paths
currently being undertaken. Discussion brings together elements of the
technology survey, application limitations, a timeline for useful commercial
deployment, and predicted future research directions. Two technology
research paths are highlighted as the most probable to produce functionally
useful devices (defined as nearly equal or even superior to the control
capabilities of current HMis) in the near and far term.
The technology endpoint this paper seeks is thought-based operation of
remote machinery during normal human activities without mechanical device
interaction-that is, control of external devices without the need to go to a
specified location, such as a shielded room; without the need to remain
perfectly motionless to reduce signal noise; and without the need for
interaction with a normal electro-mechanical device, such as an i-Phone or
other handheld device with buttons and trackballs. Data transfer rates are
sought to exceed 5-10 bits/second to be useful for operation of complex
devices; this rate range and above is referred to as high-bandwidth BMis.
Response time for a 1-of-N selection of commands is targeted at 300
milliseconds or less. These are the operational parameters assumed for final
implementation unless some limitation or supercapability is described.
The paper concludes that noninvasive electrical monitoring of neural activity,
primarily reading combined action of muscles and neurons, is the most
promising commercial technology in the near term. Inherent limitations in the
noninvasive electrical approach require future development of different
research paths. The paper argues, mainly by eliminating other approaches,
that the most probable technology in the long term involves invasive single
neuron-based direct cortical connections to form a network of high-bandwidth
duplex communication pathways. Currently the most promising technologies
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Official release, from the pursue 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.