BCI Competition 2003—Data Set IIb: Enhancing P300 Wave Detection Using ICA-Based Subspace Projections for BCI Applications

2004 ◽  
Vol 51 (6) ◽  
pp. 1067-1072 ◽  
Author(s):  
N. Xu ◽  
X. Gao ◽  
B. Hong ◽  
X. Miao ◽  
S. Gao ◽  
...  
Keyword(s):  
Data Set ◽  
P300 Wave ◽  
Wave Detection ◽  
Subspace Projections

scholarly journals EEG P300 wave detection using Emotiv EPOC+: Effects of matrix size, flash duration, and colors

2017 ◽  
Author(s):  
Saleh Alzahrani ◽  
Charles W Anderson
Keyword(s):  
P300 Amplitude ◽  
Eeg Signals ◽  
Flash Duration ◽  
Matrix Size ◽  
P300 Wave ◽  
P300 Speller ◽  
Wave Detection ◽  
The Matrix

Objective: The P300 signal is an electroencephalography (EEG) positive deflection observed 300 ms to 600 ms after an infrequent, but expected, stimulus is presented to a subject. The aim of this study was to investigate the capability of Emotiv EPOC+ headset to capture and record the P300 wave. Moreover, the effects of using different matrix sizes, flash duration, and colors were studied. Methods: Participants attended to one cell of either 6x6 or 3x3 matrix while the rows and columns flashed randomly at different duration (100 ms or 175 ms). The EEG signals were sent wirelessly to OpenViBE software, which is used to run the P300 speller. Results: The results provide evidence of capability of the Emotiv EPOC+ headset to detect the P300 signals from two channels, O1 and O2. In addition, when the matrix size increases, the P300 amplitude increases. The results also show that longer flash duration resulted in larger P300 amplitude. Also, the effect of using colored matrix was clear on the O2 channel. Furthermore, results show that participants reached accuracy above 70% after three to four training sessions. Conclusion: The results confirmed the capability of the Emotiv EPOC+ headset for detecting P300 signals. In addition, matrix size, flash duration, and colors can affect the P300 speller performance. Significance: Such an affordable and portable headset could be utilized to control P300-based BCI or other BCI systems especially for the out-of-the-lab applications.

scholarly journals EEG P300 wave detection using Emotiv EPOC+: Effects of matrix size, flash duration, and colors

2017 ◽  
Author(s):  
Saleh Alzahrani ◽  
Charles W Anderson
Keyword(s):  
P300 Amplitude ◽  
Eeg Signals ◽  
Flash Duration ◽  
Matrix Size ◽  
P300 Wave ◽  
P300 Speller ◽  
Wave Detection ◽  
The Matrix

Objective: The P300 signal is an electroencephalography (EEG) positive deflection observed 300 ms to 600 ms after an infrequent, but expected, stimulus is presented to a subject. The aim of this study was to investigate the capability of Emotiv EPOC+ headset to capture and record the P300 wave. Moreover, the effects of using different matrix sizes, flash duration, and colors were studied. Methods: Participants attended to one cell of either 6x6 or 3x3 matrix while the rows and columns flashed randomly at different duration (100 ms or 175 ms). The EEG signals were sent wirelessly to OpenViBE software, which is used to run the P300 speller. Results: The results provide evidence of capability of the Emotiv EPOC+ headset to detect the P300 signals from two channels, O1 and O2. In addition, when the matrix size increases, the P300 amplitude increases. The results also show that longer flash duration resulted in larger P300 amplitude. Also, the effect of using colored matrix was clear on the O2 channel. Furthermore, results show that participants reached accuracy above 70% after three to four training sessions. Conclusion: The results confirmed the capability of the Emotiv EPOC+ headset for detecting P300 signals. In addition, matrix size, flash duration, and colors can affect the P300 speller performance. Significance: Such an affordable and portable headset could be utilized to control P300-based BCI or other BCI systems especially for the out-of-the-lab applications.

A Fast Internal Wave Detection Method Based on PCANet for Ocean Monitoring

2019 ◽  
Vol 28 (1) ◽  
pp. 103-113 ◽  
Author(s):  
Shengke Wang ◽  
Qinghong Dong ◽  
Lianghua Duan ◽  
Yujuan Sun ◽  
Muwei Jian ◽  
...  
Keyword(s):  
Internal Wave ◽  
Internal Waves ◽  
Detection Method ◽  
Feature Representation ◽  
Classification Model ◽  
Support Vector ◽  
Data Set ◽  
Wave Detection ◽  
Representation Model ◽  
Ocean Monitoring

Abstract Research on internal waves in the coastal ocean is one of the most important tasks both in physical oceanography and ocean monitoring network. Currently, how to quickly and accurately detect the ocean internal waves from the huge ocean surface is still a challenging issue. In this paper, we model the ocean internal wave detection as a task of region classification for texture images and then propose a rapid internal waves detection method based on a deep learning framework (PCANet). In the proposed method, two models have been trained: one is the deep feature representation model, which combines principal component analysis (PCA), binary hashing, and block-wise histograms and can extract more distinguishing features than handcraft feature. Moreover, because the filter learning in PCANet does not require regularized parameters and numerical optimization solver, the training process of the representation model is very fast. The other one is a classification model based on a linear support vector machine. The object proposal method has been applied to get the possible candidates when analyzing a captured image, which dramatically decreases the searching time. Experiment results on the data set captured by unmanned aerial vehicles verify the speed ability and effectiveness of the proposed method.

Rotational Characteristics of the Green Solar Corona: 1947-1991

1994 ◽  
Vol 144 ◽  
pp. 139-141 ◽  
Author(s):  
J. Rybák ◽  
V. Rušin ◽  
M. Rybanský
Keyword(s):  
Solar Corona ◽  
World Wide ◽  
Rotation Period ◽  
Original Data ◽  
Coronal Emission ◽  
Time Intervals ◽  
Data Set ◽  
The World ◽  
Coronal Emission Line ◽  
Homogeneous Data

AbstractFe XIV 530.3 nm coronal emission line observations have been used for the estimation of the green solar corona rotation. A homogeneous data set, created from measurements of the world-wide coronagraphic network, has been examined with a help of correlation analysis to reveal the averaged synodic rotation period as a function of latitude and time over the epoch from 1947 to 1991.The values of the synodic rotation period obtained for this epoch for the whole range of latitudes and a latitude band ±30° are 27.52±0.12 days and 26.95±0.21 days, resp. A differential rotation of green solar corona, with local period maxima around ±60° and minimum of the rotation period at the equator, was confirmed. No clear cyclic variation of the rotation has been found for examinated epoch but some monotonic trends for some time intervals are presented.A detailed investigation of the original data and their correlation functions has shown that an existence of sufficiently reliable tracers is not evident for the whole set of examinated data. This should be taken into account in future more precise estimations of the green corona rotation period.

Difference Fourier Analysis of Glucose Embedded and Frozen Hydrated Purple Membrane

1982 ◽  
Vol 40 ◽  
pp. 74-75
Author(s):  
Jules S. Jaffe ◽  
Robert M. Glaeser
Keyword(s):  
Purple Membrane ◽  
Data Set ◽  
High Resolution Data ◽  
X Ray ◽  
X Ray Crystallography ◽  
Fourier Techniques ◽  
Versus Protein ◽  
The Difference ◽  
Difference Fourier ◽  
Ideal Method

Although difference Fourier techniques are standard in X-ray crystallography it has only been very recently that electron crystallographers have been able to take advantage of this method. We have combined a high resolution data set for frozen glucose embedded Purple Membrane (PM) with a data set collected from PM prepared in the frozen hydrated state in order to visualize any differences in structure due to the different methods of preparation. The increased contrast between protein-ice versus protein-glucose may prove to be an advantage of the frozen hydrated technique for visualizing those parts of bacteriorhodopsin that are embedded in glucose. In addition, surface groups of the protein may be disordered in glucose and ordered in the frozen state. The sensitivity of the difference Fourier technique to small changes in structure provides an ideal method for testing this hypothesis.

Algorithms for automated montage synthesis of images from laser-scanning confocal microscopes

1995 ◽  
Vol 53 ◽  
pp. 650-651
Author(s):  
D. E. Becker
Keyword(s):  
Image Analysis ◽  
High Resolution ◽  
Laser Scanning ◽  
Cell Counting ◽  
Wide Area ◽  
Data Set ◽  
Computational Synthesis ◽  
Automated Cell Counting ◽  
Partial View ◽  
The Individual

An efficient, robust, and widely-applicable technique is presented for computational synthesis of high-resolution, wide-area images of a specimen from a series of overlapping partial views. This technique can also be used to combine the results of various forms of image analysis, such as segmentation, automated cell counting, deblurring, and neuron tracing, to generate representations that are equivalent to processing the large wide-area image, rather than the individual partial views. This can be a first step towards quantitation of the higher-level tissue architecture. The computational approach overcomes mechanical limitations, such as hysterisis and backlash, of microscope stages. It also automates a procedure that is currently done manually. One application is the high-resolution visualization and/or quantitation of large batches of specimens that are much wider than the field of view of the microscope.The automated montage synthesis begins by computing a concise set of landmark points for each partial view. The type of landmarks used can vary greatly depending on the images of interest. In many cases, image analysis performed on each data set can provide useful landmarks. Even when no such “natural” landmarks are available, image processing can often provide useful landmarks.

Merging of electron-diffraction intensities acquired with a slow-scan CCD camera of crotoxin complex crystals to 3.5Å resolution

1994 ◽  
Vol 52 ◽  
pp. 104-105
Author(s):  
Jaap Brink ◽  
Wah Chiu
Keyword(s):  
Electron Diffraction ◽  
Ccd Camera ◽  
Crystal Thickness ◽  
Local Contrast ◽  
Camera Model ◽  
Data Set ◽  
3 Dimensional ◽  
Diffraction Mode ◽  
Diffraction Patterns ◽  
Complex Crystals

Crotoxin complex is the principal neurotoxin of the South American rattlesnake, Crotalus durissus terrificus and has a molecular weight of 24 kDa. The protein is a heterodimer with subunit A assigneda chaperone function. Subunit B carries the lethal activity, which is exerted on both sides ofthe neuro-muscular junction, and which is thought to involve binding to the acetylcholine receptor. Insight in crotoxin complex’ mode of action can be gained from a 3 Å resolution structure obtained by electron crystallography. This abstract communicates our progress in merging the electron diffraction amplitudes into a 3-dimensional (3D) intensity data set close to completion. Since the thickness of crotoxin complex crystals varies from one crystal to the other, we chose to collect tilt series of electron diffraction patterns after determining their thickness. Furthermore, by making use of the symmetry present in these tilt data, intensities collected only from similar crystals will be merged.Suitable crystals of glucose-embedded crotoxin complex were searched for in the defocussed diffraction mode with the goniometer tilted to 55° of higher in a JEOL4000 electron cryo-microscopc operated at 400 kV with the crystals kept at -120°C in a Gatan 626 cryo-holder. The crystal thickness was measured using the local contrast of the crystal relative to the supporting film from search-mode images acquired using a 1024 x 1024 slow-scan CCD camera (model 679, Gatan Inc.).

Three-dimensional image analysis and visualization in confocal light microscopy

1993 ◽  
Vol 51 ◽  
pp. 158-159
Author(s):  
J. K. Samarabandu ◽  
R. Acharya ◽  
D. R. Pareddy ◽  
P. C. Cheng
Keyword(s):  
Depth Perception ◽  
Computer Graphic ◽  
Three Dimensional ◽  
Cellular Organization ◽  
Data Set ◽  
Computational Burden ◽  
Interactive Operation ◽  
Cell Organization ◽  
Confocal Images ◽  
3D Digitization

In the study of cell organization in a maize meristem, direct viewing of confocal optical sections in 3D (by means of 3D projection of the volumetric data set, Figure 1) becomes very difficult and confusing because of the large number of nucleus involved. Numerical description of the cellular organization (e.g. position, size and orientation of each structure) and computer graphic presentation are some of the solutions to effectively study the structure of such a complex system. An attempt at data-reduction by means of manually contouring cell nucleus in 3D was reported (Summers et al., 1990). Apart from being labour intensive, this 3D digitization technique suffers from the inaccuracies of manual 3D tracing related to the depth perception of the operator. However, it does demonstrate that reducing stack of confocal images to a 3D graphic representation helps to visualize and analyze complex tissues (Figure 2). This procedure also significantly reduce computational burden in an interactive operation.

Identifying groups of airborne particles by ordination

1994 ◽  
Vol 52 ◽  
pp. 856-857
Author(s):  
M. Shlepr ◽  
C. M. Vicroy
Keyword(s):  
Elemental Analysis ◽  
Energy Dispersive Spectroscopy ◽  
Manufacturing Process ◽  
Spatial Representation ◽  
Airborne Particles ◽  
Common Source ◽  
Data Set ◽  
Microelectronics Industry ◽  
Induced Changes ◽  
Source Materials

The microelectronics industry is heavily tasked with minimizing contaminates at all steps of the manufacturing process. Particles are generated by physical and/or chemical fragmentation from a mothersource. The tools and macrovolumes of chemicals used for processing, the environment surrounding the process, and the circuits themselves are all potential particle sources. A first step in eliminating these contaminants is to identify their source. Elemental analysis of the particles often proves useful toward this goal, and energy dispersive spectroscopy (EDS) is a commonly used technique. However, the large variety of source materials and process induced changes in the particles often make it difficult to discern if the particles are from a common source.Ordination is commonly used in ecology to understand community relationships. This technique usespair-wise measures of similarity. Separation of the data set is based on discrimination functions. Theend product is a spatial representation of the data with the distance between points equaling the degree of dissimilarity.

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