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Proceedings Paper

Beyond intuitive anthropomorphic control: recent achievements using brain computer interface technologies
Author(s): Eric A. Pohlmeyer; Matthew Fifer; Matthew Rich; Johnathan Pino; Brock Wester; Matthew Johannes; Chris Dohopolski; John Helder; Denise D'Angelo; James Beaty; Sliman Bensmaia; Michael McLoughlin; Francesco Tenore
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Paper Abstract

Brain-computer interface (BCI) research has progressed rapidly, with BCIs shifting from animal tests to human demonstrations of controlling computer cursors and even advanced prosthetic limbs, the latter having been the goal of the Revolutionizing Prosthetics (RP) program. These achievements now include direct electrical intracortical microstimulation (ICMS) of the brain to provide human BCI users feedback information from the sensors of prosthetic limbs. These successes raise the question of how well people would be able to use BCIs to interact with systems that are not based directly on the body (e.g., prosthetic arms), and how well BCI users could interpret ICMS information from such devices. If paralyzed individuals could use BCIs to effectively interact with such non-anthropomorphic systems, it would offer them numerous new opportunities to control novel assistive devices. Here we explore how well a participant with tetraplegia can detect infrared (IR) sources in the environment using a prosthetic arm mounted camera that encodes IR information via ICMS. We also investigate how well a BCI user could transition from controlling a BCI based on prosthetic arm movements to controlling a flight simulator, a system with different physical dynamics than the arm. In that test, the BCI participant used environmental information encoded via ICMS to identify which of several upcoming flight routes was the best option. For both tasks, the BCI user was able to quickly learn how to interpret the ICMSprovided information to achieve the task goals.

Paper Details

Date Published: 18 May 2017
PDF: 14 pages
Proc. SPIE 10194, Micro- and Nanotechnology Sensors, Systems, and Applications IX, 101941N (18 May 2017); doi: 10.1117/12.2263886
Show Author Affiliations
Eric A. Pohlmeyer, Johns Hopkins Univ. Applied Physics Lab. (United States)
Matthew Fifer, Johns Hopkins Univ. Applied Physics Lab. (United States)
Matthew Rich, Johns Hopkins Univ. Applied Physics Lab. (United States)
Johnathan Pino, Johns Hopkins Univ. Applied Physics Lab. (United States)
Brock Wester, Johns Hopkins Univ. Applied Physics Lab. (United States)
Matthew Johannes, Johns Hopkins Univ. Applied Physics Lab. (United States)
Chris Dohopolski, Johns Hopkins Univ. Applied Physics Lab. (United States)
John Helder, Johns Hopkins Univ. Applied Physics Lab. (United States)
Denise D'Angelo, Johns Hopkins Univ. Applied Physics Lab. (United States)
James Beaty, Johns Hopkins Univ. Applied Physics Lab. (United States)
Sliman Bensmaia, Univ. of Chicago (United States)
Michael McLoughlin, Johns Hopkins Univ. Applied Physics Lab. (United States)
Francesco Tenore, Johns Hopkins Univ. Applied Physics Lab. (United States)


Published in SPIE Proceedings Vol. 10194:
Micro- and Nanotechnology Sensors, Systems, and Applications IX
Thomas George; Achyut K. Dutta; M. Saif Islam, Editor(s)

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