Citi, Luca and Tonet, Oliver and Marinelli, Martina (2009) Chapter 15 Matching Brain–Machine Interface Performance to Space Applications. International Review of Neurobiology, 86. pp. 199-212. DOI https://doi.org/10.1016/s0074-7742(09)86015-7
Citi, Luca and Tonet, Oliver and Marinelli, Martina (2009) Chapter 15 Matching Brain–Machine Interface Performance to Space Applications. International Review of Neurobiology, 86. pp. 199-212. DOI https://doi.org/10.1016/s0074-7742(09)86015-7
Citi, Luca and Tonet, Oliver and Marinelli, Martina (2009) Chapter 15 Matching Brain–Machine Interface Performance to Space Applications. International Review of Neurobiology, 86. pp. 199-212. DOI https://doi.org/10.1016/s0074-7742(09)86015-7
Abstract
A brain-machine interface (BMI) is a particular class of human-machine interface (HMI). BMIs have so far been studied mostly as a communication means for people who have little or no voluntary control of muscle activity. For able-bodied users, such as astronauts, a BMI would only be practical if conceived as an augmenting interface. A method is presented for pointing out effective combinations of HMIs and applications of robotics and automation to space. Latency and throughput are selected as performance measures for a hybrid bionic system (HBS), that is, the combination of a user, a device, and a HMI. We classify and briefly describe HMIs and space applications and then compare the performance of classes of interfaces with the requirements of classes of applications, both in terms of latency and throughput. Regions of overlap correspond to effective combinations. Devices requiring simpler control, such as a rover, a robotic camera, or environmental controls are suitable to be driven by means of BMI technology. Free flyers and other devices with six degrees of freedom can be controlled, but only at low-interactivity levels. More demanding applications require conventional interfaces, although they could be controlled by BMIs once the same levels of performance as currently recorded in animal experiments are attained. Robotic arms and manipulators could be the next frontier for noninvasive BMIs. Integrating smart controllers in HBSs could improve interactivity and boost the use of BMI technology in space applications. © 2009 Elsevier Inc. All rights reserved.
Item Type: | Article |
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Uncontrolled Keywords: | Brain; Humans; Communication Aids for Disabled; Man-Machine Systems; Psychomotor Performance; Reaction Time; Space Flight; User-Computer Interface |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 13 Mar 2014 10:48 |
Last Modified: | 30 Oct 2024 19:46 |
URI: | http://repository.essex.ac.uk/id/eprint/8782 |
Available files
Filename: Citi2009MatchingBMIPerfSpaceAppl.pdf