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Computer Interfaces (computer + interface)

Distribution by Scientific Domains

Engineering	42%
Medical Sciences	21%

Selected Abstracts

Improved GMM with parameter initialization for unsupervised adaptation of Brain,Computer interface

INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING, Issue 6 2010
Guangquan Liu
Abstract An important property of brain signals is their nonstationarity. How to adapt a brain,computer interface (BCI) to the changing brain states is one of the challenges faced by BCI researchers, especially in real application where the subject's real intent is unknown to the system. Gaussian mixture model (GMM) has been used for the unsupervised adaptation of the classifier in BCI. In this paper, a method of initializing the model parameters is proposed for expectation maximization-based GMM parameter estimation. This improved GMM method and other two existing unsupervised adaptation methods are applied to groups of constructed artificial data with different data properties. Performances of these methods in different situations are analyzed. Compared with the other two unsupervised adaptation methods, this method shows a better ability of adapting to changes and discovering class information from unlabelled data. The methods are also applied to real EEG data recorded in 19 experiments. For real data, the proposed method achieves an error rate significantly lower than the other two unsupervised methods. Results of the real data agree with the analysis based on the artificial data, which confirms not only the effectiveness of our method but also the validity of the constructed data. Copyright © 2009 John Wiley & Sons, Ltd. [source]

A Windows-based interface for teaching image processing

COMPUTER APPLICATIONS IN ENGINEERING EDUCATION, Issue 2 2010
Melvin Ayala
Abstract The use of image processing in research represents a challenge to the scientific community interested in its various applications but is not familiar with this area of expertise. In academia as well as in industry, fundamental concepts such as image transformations, filtering, noise removal, morphology, convolution/deconvolution among others require extra efforts to be understood. Additionally, algorithms for image reading and visualization in computers are not always easy to develop by inexperienced researchers. This type of environment has lead to an adverse situation where most students and researchers develop their own image processing code for operations which are already standards in image processing, a redundant process which only exacerbates the situation. The research proposed in this article, with the aim to resolve this dilemma, is to propose a user-friendly computer interface that has a dual objective which is to free students and researchers from the learning time needed for understanding/applying diverse imaging techniques but to also provide them with the option to enhance or reprogram such algorithms with direct access to the software code. The interface was thus developed with the intention to assist in understanding and performing common image processing operations through simple commands that can be performed mostly by mouse clicks. The visualization of pseudo code after each command execution makes the interface attractive, while saving time and facilitating to users the learning of such practical concepts. © 2009 Wiley Periodicals, Inc. Comput Appl Eng Educ 18: 213,224, 2010; Published online in Wiley InterScience (www.interscience.wiley.com); DOI 10.1002/cae.20171 [source]

Cognition and Behavior in Normal-Form Games: An Experimental Study

ECONOMETRICA, Issue 5 2001
Miguel Costa-Gomes
This paper reports experiments designed to study strategic sophistication, the extent to which behavior in games reflects attempts to predict others' decisions, taking their incentives into account. We study subjects' initial responses to normal-form games with various patterns of iterated dominance and unique pure-strategy equilibria without dominance, using a computer interface that allowed them to search for hidden payoff information, while recording their searches. Monitoring subjects' information searches along with their decisions allows us to better understand how their decisions are determined, and subjects' deviations from the search patterns suggested by equilibrium analysis help to predict their deviations from equilibrium decisions. [source]

xBCI: A Generic Platform for Development of an Online BCI System

IEEJ TRANSACTIONS ON ELECTRICAL AND ELECTRONIC ENGINEERING, Issue 4 2010
I Putu Susila Non-member
Abstract A generic platform for realizing an online brain,computer interface (BCI) named xBCI was developed. The platform consists of several functional modules (components), such as data acquisition, storage, mathematical operations, signal processing, network communication, data visualization, experiment control, and real-time feedback presentation. Users can easily build their own BCI systems by combining the components on a graphical-user-interface (GUI) based diagram editor. They can also extend the platform by adding components as plug-ins or by creating components using a scripting language. The platform works on multiple operating systems and supports parallel (multi-threaded) data processing and data transfer to other PCs through a network transmission control protocol/internet protocol or user datagram protocol (TCP/IP or UDP). A BCI system based on motor imagery and a steady-state visual evoked potential (SSVEP) based BCI system were constructed and tested on the platform. The results show that the platform is able to process multichannel brain signals in real time. The platform provides users with an easy-to-use system development tool and reduces the time needed to develop a BCI system. Copyright © 2010 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [source]

Improved GMM with parameter initialization for unsupervised adaptation of Brain,Computer interface

Effects of Computerized Provider Order Entry and Nursing Documentation on Workflow

ACADEMIC EMERGENCY MEDICINE, Issue 10 2008
Phillip V. Asaro MD
Abstract Objectives:, The objective was to measure the effects of the implementation of computerized provider order entry (CPOE) and electronic nursing documentation on provider workflow in the emergency department (ED). Methods:, The authors performed a before-and-after time-motion study of the activities of physicians and nurses. The percentages of time spent in task categories were calculated by provider session and averaged across provider sessions. Results:, There was a shift in physician time from working with paper alone, 13.1% to 9.6% (p = 0.05), to working with paper while using a computer, 1.6% to 4.3% (p = 0.02), and an increase in time spent working on computer and/or paper from 30.0% to 38.9% (p = 0.02). For nurses, the increase in time spent on computer from 9.5% to 25.7% (p < 0.01) was offset by a decrease in time spent working with paper from 16.5% to 1.8% (p < 0.01). Direct care decreased minimally for nurses from 56.9% to 55.3% (p = 0.69), but from 36.8% to 29.1% (p = 0.07) for physicians, approaching statistical significance. Care planning decreased for nurses from 9.4% to 6.4% (p = 0.04) and from 21.7% to 19.5% (p = 0.60) for physicians. Conclusions:, The net effects of an implementation on provider workflow depend not only on changes in tasks directly related to the provider,computer interface, but also on changes in underlying patient care processes and information flows. The authors observed an unanticipated shift in physician time from interacting with nurses and patients toward retrieving information from the electronic patient record. Implementers should carefully consider how implementations will affect information flow and then expect the unexpected. [source]

Ophthalmic imaging today: an ophthalmic photographer's viewpoint , a review

CLINICAL & EXPERIMENTAL OPHTHALMOLOGY, Issue 1 2009
Timothy J Bennett FOPS
Abstract Ophthalmic imaging has changed dramatically since the 1960s with increasingly complex technologies now available. Arguably, the greatest changes have been the development of the digital camera and the speed, processing power and storage of electronic data. Already, ophthalmic practices in many major institutions overseas have paperless medium storage and electronically generated reporting from all equipment that use a computer interface. It is hard to remember the widespread use of photographic film with its attendant costs, or even to remember the days before optical coherence tomography (OCT). These latest technical improvements in ophthalmic imaging are now standard in large Australian institutions and becoming more widespread in smaller private practices. The technicians that operate and maintain this ever-increasing plethora of gadgetry have seen their work practices change from the darkroom to the complexities of data-based imaging and storage. It is a fitting time to examine the contemporary state of ophthalmic imaging and what lies on the horizon as we move towards 2020. [source]

Covert attention allows for continuous control of brain,computer interfaces

EUROPEAN JOURNAL OF NEUROSCIENCE, Issue 8 2010
Ali Bahramisharif
Abstract While brain-computer interfaces (BCIs) can be used for controlling external devices, they also hold the promise of providing a new tool for studying the working brain. In this study we investigated whether modulations of brain activity by changes in covert attention can be used as a continuous control signal for BCI. Covert attention is the act of mentally focusing on a peripheral sensory stimulus without changing gaze direction. The ongoing brain activity was recorded using magnetoencephalography in subjects as they covertly attended to a moving cue while maintaining fixation. Based on posterior alpha power alone, the direction to which subjects were attending could be recovered using circular regression. Results show that the angle of attention could be predicted with a mean absolute deviation of 51° in our best subject. Averaged over subjects, the mean deviation was ,70°. In terms of information transfer rate, the optimal data length used for recovering the direction of attention was found to be 1700 ms; this resulted in a mean absolute deviation of 60° for the best subject. The results were obtained without any subject-specific feature selection and did not require prior subject training. Our findings demonstrate that modulations of posterior alpha activity due to the direction of covert attention has potential as a control signal for continuous control in a BCI setting. Our approach will have several applications, including a brain-controlled computer mouse and improved methods for neuro-feedback that allow direct training of subjects' ability to modulate posterior alpha activity. [source]

Understanding intention of movement from electroencephalograms

EXPERT SYSTEMS, Issue 5 2007
Heba Lakany
Abstract: In this paper, we propose a new framework for understanding intention of movement that can be used in developing non-invasive brain,computer interfaces. The proposed method is based on extracting salient features from brain signals recorded whilst the subject is actually (or imagining) performing a wrist movement in different directions. Our method focuses on analysing the brain signals at the time preceding wrist movement, i.e. while the subject is preparing (or intending) to perform the movement. Feature selection and classification of the direction is done using a wrapper method based on support vector machines (SVMs). The classification results show that we are able to discriminate the directions using features extracted from brain signals prior to movement. We then extract rules from the SVM classifiers to compare the features extracted for real and imaginary movements in an attempt to understand the mechanisms of intention of movement. Our new approach could be potentially useful in building brain,computer interfaces where a paralysed person could communicate with a wheelchair and steer it to the desired direction using a rule-based knowledge system based on understanding of the subject's intention to move through his/her brain signals. [source]

A simple and low-cost solution for the automation of X-ray powder diffractometers with chart recorder output

JOURNAL OF APPLIED CRYSTALLOGRAPHY, Issue 4 2006
M. Jayaprakasan
X-ray powder diffraction is an established method for the qualitative identification of crystalline materials and their quantitative analysis. The new generation of X-ray diffraction systems are based on expensive digital/embedded control technology and computer interfaces. Yet many laboratories use conventional manual-controlled systems with XY strip-chart recorders. Since the output spectrum is a strip chart (hard copy), raw data, essential for structural and qualitative analysis, are not readily available for further analysis. Upgrading to modern computerized diffractometers is very expensive. The proposed automation design described here is intended to enable the conventional diffractometer user to collect, store and analyze data quickly. The design also improves the resolution by five times compared with the conventional setup. For the automation, a PC add-on card has been designed to control and collect the timing and intensity counts from the conventional X-ray diffractometer, and suitable software has been developed to collect, process and present the X-ray diffraction data for both qualitative and quantitative analysis. Moreover, a major advantage of this design is that it does not warrant any physical modification of the hardware of the conventional setup; it is simply an extension to enhance the performance of collecting raw data with a higher resolution at desired intervals/timings. [source]

An affordable modular mobile robotic platform with fuzzy logic control and evolutionary artificial neural networks

JOURNAL OF FIELD ROBOTICS (FORMERLY JOURNAL OF ROBOTIC SYSTEMS), Issue 8 2004
Maurice Tedder
Autonomous robotics projects encompass the rich nature of integrated systems that includes mechanical, electrical, and computational software components. The availability of smaller and cheaper hardware components has helped make possible a new dimension in operational autonomy. This paper describes a mobile robotic platform consisting of several integrated modules including a laptop computer that serves as the main control module, microcontroller-based motion control module, a vision processing module, a sensor interface module, and a navigation module. The laptop computer module contains the main software development environment with a user interface to access and control all other modules. Programming language independence is achieved by using standard input/output computer interfaces including RS-232 serial port, USB, networking, audio input and output, and parallel port devices. However, with the same hardware technology available to all, the distinguishing factor in most cases for intelligent systems becomes the software design. The software for autonomous robots must intelligently control the hardware so that it functions in unstructured, dynamic, and uncertain environments while maintaining an autonomous adaptability. This paper describes how we introduced fuzzy logic control to one robot platform in order to solve the 2003 Intelligent Ground Vehicle Competition (IGVC) Autonomous Challenge problem. This paper also describes the introduction of hybrid software design that utilizes Fuzzy Evolutionary Artificial Neural Network techniques. In this design, rather than using a control program that is directly coded, the robot's artificial neural net is first trained with a training data set using evolutionary optimization techniques to adjust weight values between neurons. The trained neural network with a weight average defuzzification method was able to make correct decisions to unseen vision patterns for the IGVC Autonomous Challenge. A comparison of the Lawrence Technological University robot designs and the design of the other competing schools shows that our platforms were the most affordable robot systems to use as tools for computer science and engineering education. © 2004 Wiley Periodicals, Inc. [source]

Breaking the silence: Brain,computer interfaces (BCI) for communication and motor control

PSYCHOPHYSIOLOGY, Issue 6 2006
Niels Birbaumer
Abstract Brain,computer interfaces (BCI) allow control of computers or external devices with regulation of brain activity alone. Invasive BCIs, almost exclusively investigated in animal models using implanted electrodes in brain tissue, and noninvasive BCIs using electrophysiological recordings in humans are described. Clinical applications were reserved with few exceptions for the noninvasive approach: communication with the completely paralyzed and locked-in syndrome with slow cortical potentials, sensorimotor rhythm and P300, and restoration of movement and cortical reorganization in high spinal cord lesions and chronic stroke. It was demonstrated that noninvasive EEG-based BCIs allow brain-derived communication in paralyzed and locked-in patients but not in completely locked-in patients. At present no firm conclusion about the clinical utility of BCI for the control of voluntary movement can be made. Invasive multielectrode BCIs in otherwise healthy animals allowed execution of reaching, grasping, and force variations based on spike patterns and extracellular field potentials. The newly developed fMRI-BCIs and NIRS-BCIs, like EEG BCIs, offer promise for the learned regulation of emotional disorders and also disorders of young children. [source]

Brain,computer interfacing based on cognitive control

ANNALS OF NEUROLOGY, Issue 6 2010
Mariska J. Vansteensel PhD
Objective Brain,computer interfaces (BCIs) translate deliberate intentions and associated changes in brain activity into action, thereby offering patients with severe paralysis an alternative means of communication with and control over their environment. Such systems are not available yet, partly due to the high performance standard that is required. A major challenge in the development of implantable BCIs is to identify cortical regions and related functions that an individual can reliably and consciously manipulate. Research predominantly focuses on the sensorimotor cortex, which can be activated by imagining motor actions. However, because this region may not provide an optimal solution to all patients, other neuronal networks need to be examined. Therefore, we investigated whether the cognitive control network can be used for BCI purposes. We also determined the feasibility of using functional magnetic resonance imaging (fMRI) for noninvasive localization of the cognitive control network. Methods Three patients with intractable epilepsy, who were temporarily implanted with subdural grid electrodes for diagnostic purposes, attempted to gain BCI control using the electrocorticographic (ECoG) signal of the left dorsolateral prefrontal cortex (DLPFC). Results All subjects quickly gained accurate BCI control by modulation of gamma-power of the left DLPFC. Prelocalization of the relevant region was performed with fMRI and was confirmed using the ECoG signals obtained during mental calculation localizer tasks. Interpretation The results indicate that the cognitive control network is a suitable source of signals for BCI applications. They also demonstrate the feasibility of translating understanding about cognitive networks derived from functional neuroimaging into clinical applications. ANN NEUROL 2010 [source]