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Proceedings Paper

Acquiring neural signals for developing a perception and cognition model
Author(s): Wei Li; Yunyi Li; Genshe Chen; Dan Shen; Erik Blasch; Khanh Pham; Robert Lynch
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Paper Abstract

The understanding of how humans process information, determine salience, and combine seemingly unrelated information is essential to automated processing of large amounts of information that is partially relevant, or of unknown relevance. Recent neurological science research in human perception, and in information science regarding contextbased modeling, provides us with a theoretical basis for using a bottom-up approach for automating the management of large amounts of information in ways directly useful for human operators. However, integration of human intelligence into a game theoretic framework for dynamic and adaptive decision support needs a perception and cognition model. For the purpose of cognitive modeling, we present a brain-computer-interface (BCI) based humanoid robot system to acquire brainwaves during human mental activities of imagining a humanoid robot-walking behavior. We use the neural signals to investigate relationships between complex humanoid robot behaviors and human mental activities for developing the perception and cognition model. The BCI system consists of a data acquisition unit with an electroencephalograph (EEG), a humanoid robot, and a charge couple CCD camera. An EEG electrode cup acquires brainwaves from the skin surface on scalp. The humanoid robot has 20 degrees of freedom (DOFs); 12 DOFs located on hips, knees, and ankles for humanoid robot walking, 6 DOFs on shoulders and arms for arms motion, and 2 DOFs for head yaw and pitch motion. The CCD camera takes video clips of the human subject's hand postures to identify mental activities that are correlated to the robot-walking behaviors. We use the neural signals to investigate relationships between complex humanoid robot behaviors and human mental activities for developing the perception and cognition model.

Paper Details

Date Published: 25 May 2012
PDF: 9 pages
Proc. SPIE 8385, Sensors and Systems for Space Applications V, 83850I (25 May 2012); doi: 10.1117/12.918767
Show Author Affiliations
Wei Li, California State Univ., Bakersfield (United States)
Yunyi Li, Duke Univ. (United States)
Genshe Chen, I-Fusion Technologies, Inc. (United States)
Dan Shen, I-Fusion Technologies, Inc. (United States)
Erik Blasch, Air Force Research Lab. (United States)
Khanh Pham, Air Force Research Lab. (United States)
Robert Lynch, Naval Undersea Warfare Ctr. (United States)


Published in SPIE Proceedings Vol. 8385:
Sensors and Systems for Space Applications V
Khanh D. Pham; Joseph L. Cox; Richard T. Howard; Henry Zmuda, Editor(s)

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