scholarly journals Adaptive Spatial Filter Based on Similarity Indices to Preserve the Neural Information on EEG Signals during On-Line Processing

Sensors ◽  
2017 ◽  
Vol 17 (12) ◽  
pp. 2725 ◽  
Author(s):  
Denis Delisle-Rodriguez ◽  
Ana Villa-Parra ◽  
Teodiano Bastos-Filho ◽  
Alberto López-Delis ◽  
Anselmo Frizera-Neto ◽  
...  
Keyword(s):  
Spatial Filter ◽  
Eeg Signals ◽  
Similarity Indices ◽  
Neural Information ◽  
On Line ◽  
Adaptive Spatial Filter

scholarly journals Adaptive spatial filter based on similarity indices to preserve the neural information on EEG signals during on-line processing

2021 ◽  
Author(s):  
Denis Delisle-Rodriguez ◽  
Ana Cecilia Villa-Parra ◽  
Teodiano Bastos-Filho ◽  
Alberto López-Delis ◽  
Anselmo Frizera-Neto ◽  
...  
Keyword(s):  
Spatial Pattern ◽  
Low Frequency ◽  
Spatial Filter ◽  
Eeg Signals ◽  
Common Spatial Pattern ◽  
Gait Planning ◽  
Sliding Windows ◽  
Neural Information ◽  
On Line ◽  
Highly Correlated

This work presents a new on-line adaptive filter, which is based on a similarity analysis between standard electrode locations, in order to reduce artifacts and common interferences throughout electroencephalography (EEG) signals, but preserving the useful information. Standard deviation and Concordance Correlation Coefficient (CCC) between target electrodes and its correspondent neighbor electrodes are analyzed on sliding windows to select those neighbors that are highly correlated. Afterwards, a model based on CCC is applied to provide higher values of weight to those correlated electrodes with lower similarity to the target electrode. The approach was applied to brain computer-interfaces (BCIs) based on Canonical Correlation Analysis (CCA) to recognize 40 targets of steady-state visual evoked potential (SSVEP), providing an accuracy (ACC) of 86.44 ± 2.81%. In addition, also using this approach, features of low frequency were selected in the pre-processing stage of another BCI to recognize gait planning. In this case, the recognition was significantly (p<0.01) improved for most of the subjects (ACC≥74.79%) , when compared with other BCIs based on Common Spatial Pattern, Filter Bank-Common Spatial Pattern, and Riemannian Geometry. Keywords: artifact reduction; brain-computer interface; EEG; EOG; Laplacian; spatial filter; feature selection; gait planning; SSVEP

scholarly journals Adaptive spatial filter based on similarity indices to preserve the neural information on EEG signals during on-line processing

2021 ◽  
Author(s):  
Denis Delisle-Rodriguez ◽  
Ana Cecilia Villa-Parra ◽  
Teodiano Bastos-Filho ◽  
Alberto López-Delis ◽  
Anselmo Frizera-Neto ◽  
...  
Keyword(s):  
Spatial Pattern ◽  
Low Frequency ◽  
Spatial Filter ◽  
Eeg Signals ◽  
Common Spatial Pattern ◽  
Gait Planning ◽  
Sliding Windows ◽  
Neural Information ◽  
On Line ◽  
Highly Correlated

This work presents a new on-line adaptive filter, which is based on a similarity analysis between standard electrode locations, in order to reduce artifacts and common interferences throughout electroencephalography (EEG) signals, but preserving the useful information. Standard deviation and Concordance Correlation Coefficient (CCC) between target electrodes and its correspondent neighbor electrodes are analyzed on sliding windows to select those neighbors that are highly correlated. Afterwards, a model based on CCC is applied to provide higher values of weight to those correlated electrodes with lower similarity to the target electrode. The approach was applied to brain computer-interfaces (BCIs) based on Canonical Correlation Analysis (CCA) to recognize 40 targets of steady-state visual evoked potential (SSVEP), providing an accuracy (ACC) of 86.44 ± 2.81%. In addition, also using this approach, features of low frequency were selected in the pre-processing stage of another BCI to recognize gait planning. In this case, the recognition was significantly (p<0.01) improved for most of the subjects (ACC≥74.79%) , when compared with other BCIs based on Common Spatial Pattern, Filter Bank-Common Spatial Pattern, and Riemannian Geometry. Keywords: artifact reduction; brain-computer interface; EEG; EOG; Laplacian; spatial filter; feature selection; gait planning; SSVEP

An Adaptive Spatial Filter for User-Independent Single Trial Detection of Event-Related Potentials

2015 ◽  
Vol 62 (7) ◽  
pp. 1696-1705 ◽  
Author(s):  
Hendrik Woehrle ◽  
Mario M. Krell ◽  
Sirko Straube ◽  
Su Kyoung Kim ◽  
Elsa A. Kirchner ◽  
...  
Keyword(s):  
Event Related Potentials ◽  
Spatial Filter ◽  
Single Trial ◽  
Related Potentials ◽  
Adaptive Spatial Filter

Effect of Domain Size on Fluid–Particle Statistics in Homogeneous, Gravity-Driven, Cluster-Induced Turbulence

2015 ◽  
Vol 138 (4) ◽  
Author(s):  
Jesse Capecelatro ◽  
Olivier Desjardins ◽  
Rodney O. Fox
Keyword(s):  
Volume Fraction ◽  
Finite Size ◽  
Domain Size ◽  
Spatial Filter ◽  
High Mass ◽  
Inertial Particles ◽  
Spatially Correlated ◽  
Gravity Driven ◽  
Adaptive Spatial Filter ◽  
Particle Statistics

Scaling of volume fraction and velocity fluctuations with domain size is investigated for high-mass-loading suspensions of finite-size inertial particles subject to gravity. Results from highly resolved Euler–Lagrange simulations are evaluated via an adaptive spatial filter with an averaging volume that varies with the local particle concentration. This filter enables the instantaneous particle velocity to be decomposed into a spatially correlated contribution used in defining the particle-phase turbulent kinetic energy (TKE), and a spatially uncorrelated contribution used in defining the granular temperature. The total granular energy is found to grow nearly linearly with the domain size, while the balance between the separate contributions remains approximately constant.

scholarly journals A New Adaptive Spatial Filtering Method in the Wavelet Domain for Medical Images

2020 ◽  
Vol 10 (16) ◽  
pp. 5693
Author(s):  
Maria Simona Răboacă ◽  
Cătălin Dumitrescu ◽  
Constantin Filote ◽  
Ioana Manta
Keyword(s):  
Spatial Filtering ◽  
Threshold Value ◽  
Spatial Filter ◽  
Wavelet Domain ◽  
Wavelet Coefficients ◽  
Local Statistics ◽  
Filtering Method ◽  
New Methods ◽  
Computational Resources ◽  
Adaptive Spatial Filter

Although there are many methods in the literature to eliminate noise from images, finding new methods remains a challenge in the field and, despite the complexity of existing methods, many of the methods do not reach a sufficient level of applicability, most often due to the relatively high calculation time. In addition, most existing methods perform well when the processed image is adapted to the algorithm, but otherwise fail or results in significant artifacts. The context of eliminating noise from images is similar to that of improving images and for this reason some notions necessary to understand the proposed method will be repeated. An adaptive spatial filter in the wavelet domain is proposed by soft truncation of the wavelet coefficients with threshold value adapted to the local statistics of the image and correction based on the hierarchical correlation map. The filter exploits, in a new way, both the inter-band and the bandwidth dependence of the wavelet coefficients, considering the minimization of computational resources.

Noncontacting Velocimetry Research Using Spatial Filter Based on Line Scan Sensor Arrays

2013 ◽  
Vol 427-429 ◽  
pp. 1765-1768
Author(s):  
Yong Du ◽  
Ai Dong Liu
Keyword(s):  
Sensor Arrays ◽  
Correlation Method ◽  
Primary Source ◽  
Spatial Filter ◽  
Line Scan ◽  
The Road ◽  
Auto Correlation ◽  
On Line ◽  
Measurement Algorithm ◽  
Double Channel

A noncontacting velocimetry technique based on line scan sensor arrays is proposed. Auto-correlation method is the mainly velocity measurement algorithm before. In my research, I will introduce a novel spatial filtering method based on line scan sensor for noncontacting velocimetry. When used for measuring a vehicles velocity, the variation of the distance between the sensor and the road may cause a primary source of errors. In this paper, an adaptive Double-channel optical system is recommended to eliminate the errors, and we verify the effectiveness of the design in theory.

Sign in / Sign up

Export Citation Format

Share Document