Prospective on Brain Machine Interfaces for Space System Control
- Paper number
IAC-06-D1.1.05
- Author
Prof. Carlo Menon, Simon Fraser University, Canada
- Coauthor
Dr. José del R. Millán, Switzerland
- Coauthor
Mr. Paolo Dario, Scuola Superiore Sant' Anna (SSSUP), Italy
- Coauthor
Dr. Federico Carpi, University of Pisa, Italy
- Coauthor
Ms. Cristina de Negueruela, European Space Agency (ESA)/ESTEC, Switzerland
- Coauthor
Mr. Pierre W. Ferrez, Switzerland
- Coauthor
Ms. Anna Buttfield, Switzerland
- Coauthor
Dr. Oliver Tonet, Scuola Superiore Sant' Anna (SSSUP), Italy
- Coauthor
Mr. Luca Citi, Italy
- Coauthor
Dr. Cecilia Laschi, Italy
- Coauthor
Dr. Francisco Sepulveda, University of Essex, United Kingdom
- Coauthor
Prof. Riccardo Poli, University of Essex, United Kingdom
- Coauthor
Dr. Ramaswamy Palaniappan, University of Essex, United Kingdom
- Coauthor
Prof. Paolo Maria Rossini, Italy
- Coauthor
Dr. Franca Tecchio, ISTI-CNR, Italy
- Coauthor
Mr. Mario Tombini, Italy
- Coauthor
Prof. Danilo De Rossi, University of Pisa, Italy
- Year
2006
- Abstract
Controlling and guiding computer-based systems using human brain signals has slowly but steadily become a reality. The available technology allows real-time implementation of processes which measure neuronal activity, convert their signals, and elaborate their output to the purpose of controlling mechanical systems. There are mainly two kinds of brain-machine interfaces: invasive and non-invasive. So far, the first kind has been found to be the most effective. Outstanding results have already been achieved with implanted devices where primates are able to guide robotic manipulators by means of their neural activity with spatial errors in the order of centimetres. The second kind of BMI is to date less efficient even as it is often based on classical techniques for brain diagnoses and could have a more direct impact for space applications and for our society. The use of electroencephalogram signals is an example of a non-invasive sensing method to detect neuron’s spikes. Other examples of already developed measurement systems for detecting brain activities are magnetoencephalography signals, functional magnetic resonance imaging and optical imaging, though some of these require bulky equipment that precludes their use in BMIs, while the others are widely untested. The space environment is inherently hostile and dangerous for astronauts. For this reason, Extra-Vehicular Activity should be limited as much as possible and robotic systems should be used instead. It would be desirable to optimise the interface between astronauts and external semi-automatic manipulators. The advantages of using Brain Machine Interfaces (BMI) are numerous, e.g., commands could be sent with high accuracy and without any output delays. BMI could also enable new operations leading to a new approach of mission and spacecraft design. Multi-teleoperations could simultaneously be performed using one single brain-machine interface. This would maximise the efficiency of astronaut activity that is of primary interest. Robotic aids could also be useful to astronauts weakened by a long duration transfer of many months in micro-gravity. This paper describes the state of the art of non-invasive BMIs and critically investigates both the technological limit and the potential that BMIs have for both near and far future space applications. Different scenarios are proposed and an assessment of the advantages, which BMIs can lead, is discussed. A comparison of standard space interfaces and BMIs is performed highlighting pros and cons of this new technology. A time scale estimate on the evolution of non-invasive BMIs for future feasible applications is presented and discussed.
- Abstract document
- Manuscript document
IAC-06-D1.1.05.pdf (🔒 authorized access only).
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