Title :
The unlock project: A Python-based framework for practical brain-computer interface communication “app” development
Author :
Brumberg, J.S. ; Lorenz, S.D. ; Galbraith, B.V. ; Guenther, Frank H.
Author_Institution :
Dept. of Speech-Language-Hearing, Univ. of Kansas, Lawrence, KS, USA
fDate :
Aug. 28 2012-Sept. 1 2012
Abstract :
In this paper we present a framework for reducing the development time needed for creating applications for use in non-invasive brain-computer interfaces (BCI). Our framework is primarily focused on facilitating rapid software “app” development akin to current efforts in consumer portable computing (e.g. smart phones and tablets). This is accomplished by handling intermodule communication without direct user or developer implementation, instead relying on a core subsystem for communication of standard, internal data formats. We also provide a library of hardware interfaces for common mobile EEG platforms for immediate use in BCI applications. A use-case example is described in which a user with amyotrophic lateral sclerosis participated in an electroencephalography-based BCI protocol developed using the pIn this paper we present a framework for reducing the development time needed for creating applications for use in non-invasive brain-computer interfaces (BCI). Our framework is primarily focused on facilitating rapid software “app” development akin to current efforts in consumer portable computing (e.g. smart phones and tablets). This is accomplished by handling intermodule communication without direct user or developer implementation, instead relying on a core subsystem for communication of standard, internal data formats. We also provide a library of hardware interfaces for common mobile EEG platforms for immediate use in BCI applications. A use-case example is described in which a user with amyotrophic lateral sclerosis participated in an electroencephalography-based BCI protocol developed using the proposed framework. We show that our software environment is capable of running in real-time with updates occurring 50-60 times per second with limited computational overhead (5 ms system lag) while providing accurate data acquisition and signal analysis.roposed framework. We show that our software environment is capable of running in- real-time with updates occurring 50-60 times per second with limited computational overhead (5 ms system lag) while providing accurate data acquisition and signal analysis.
Keywords :
application program interfaces; brain-computer interfaces; electroencephalography; medical computing; medical control systems; software engineering; Python based framework; Unlock Project; amyotrophic lateral sclerosis; brain-computer interface; data acquisition; electroencephalography based BCI protocol; hardware interface library; intermodule communication; mobile EEG platforms; noninvasive BCI; practical BCI communication application development; rapid software app development; signal analysis; standard internal data formats; Brain computer interfaces; Data acquisition; Delay; Electroencephalography; Software; Standards; Visualization; Brain-Computer Interfaces; Electroencephalography; Humans; Programming Languages; Software;
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4244-4119-8
Electronic_ISBN :
1557-170X
DOI :
10.1109/EMBC.2012.6346473