OCTOBER 2008 (Vol. 41, No. 10) p. 4
0018-9162/08/$31.00 © 2008 IEEE
Published by the IEEE Computer Society
Published by the IEEE Computer Society
Challenges and Lessons in Developing Middleware on Smart Phones
Oriana Riva and Jaakko Kangasharju
During the past five years, several research projects at the Helsinki Institute for Information Technology have explored various topics relating to middleware for pervasive applications on smart phones, ranging from XML messaging and synchronization, to event-based communication and service migration, to context monitoring and reconfiguration. The researchers have also built several prototype systems running on modern phone platforms and have evaluated their performance in experimental test-beds, in some cases organizing field trials for more extensive evaluations. Based on these experiences, they have identified several middleware research challenges along with possible solutions.
Noninvasive BCIs: Multiway Signal-Processing Array Decompositions
Andrzej Cichocki, Yoshikazu Washizawa, Tomasz Rutkowski, Hovagim Bakardjian, Anh-Huy Phan, Seungjin Choi, Hyekyoung Lee, Qibin Zhao, Liqing Zhang, and Yuanqing Li
Brain computer interfaces use electric, magnetic, or hemodynamic brain signals to control external devices such as computers, switches, wheelchairs, or neuroprostheses. While BCI research endeavors to create new communication channels for severely handicapped people using their brain signals, recent efforts also have been focused on developing potential applications in rehabilitation, multimedia communication, virtual reality, and entertainment and relaxation.
To attain high-quality brain data and, thus, a reliable BCI system, we first need to create the stimulus conditions or mental task setting that will generate maximally measurable and classifiable brain states.
BioSig: A Free and Open Source Software Library for BCI Research
Alois Schlögl and Clemens Brunner
Software development is a key issue in BCI research. Software can show the similarities and differences between data processing methods. It can also make clear which hyperparameters must be determined for particular algorithms. It can also demonstrate whether certain neuroscientific concepts are compatible or not. With BioSig's comprehensive library of free and open source tools, combined with existing EEG databases, BCI researchers can avoid having to reinvent the wheel on every project.
Brain-Computer Interface Operation of Robotic and Prosthetic Devices
Dennis J. McFarland and Jonathan R. Wolpaw
Brain activity produces electrical signals detectable on the scalp or cortical surface or within the brain. BCIs translate these signals from mere reflections of brain activity into outputs that communicate the user's intent without the participation of peripheral nerves and muscles.
Because they don't depend on neuromuscular control, BCIs can provide communication and control for people with devastating neuromuscular disorders. BCI research and development aims to enable these users, who might be unable even to breathe or move their eyes, to convey their wishes to caregivers, use word-processing programs and other software, or control a robotic arm or a neuroprosthesis.
Rehabilitation with Brain-Computer Interface Systems
Gert Pfurtscheller, Gernot R. Müller-Putz, Reinhold Scherer, and Christa Neuper
Biotechnology can give those with neuromuscular disorders a higher degree of self-sufficiency. Through a process that records brain signals and uses special software, an otherwise incapacitated patient can change the TV channel, turn lights on and off, and answer e-mail simply by concentrating on moving a cursor to the appropriate box on a screen.
More recent experiments have expanded these possibilities to include neuroprosthetic control. By focusing on moving a specially programmed prosthetic device, a tetraplegic can grasp a glass of water and raise it to his lips or pick up any other graspable object simply by thinking about doing it.
Brain-Computer Interfaces, Virtual Reality, and Videogames
Anatole Lécuyer, Fabien Lotte, Richard B. Reilly, Robert Leeb, Michitaka Hirose, and Mel Slater
BCIs offer a new means of playing videogames or interacting with 3D virtual environments. Several impressive prototypes already exist that let users navigate in virtual scenes or manipulate virtual objects solely by means of their cerebral activity, recorded on the scalp via electroencephalography electrodes.
Meanwhile, virtual reality technologies provide motivating, safe, and controlled conditions that enable improvement of BCI learning as well as the investigation of the brain responses and neural processes involved. Over the long term, these innovations could lead to newer applications, such as novel types of neurorehabilitation.