A novel method for analyzing nonlinear EEG signal using local SVM method

2014 ◽  
Author(s):  
Lisha Sun ◽  
Zhifei Su ◽  
Minfen Shen
Keyword(s):  
Eeg Signal ◽  
Novel Method

A novel method of motor imagery classification using eeg signal

2020 ◽  
Vol 103 ◽  
pp. 101787
Author(s):  
Venkatachalam K. ◽  
Devipriya A. ◽  
Maniraj J. ◽  
Sivaram M. ◽  
Ambikapathy A. ◽  
...  
Keyword(s):  
Motor Imagery ◽  
Eeg Signal ◽  
Novel Method

scholarly journals A deep descriptor for cross-tasking EEG-based recognition

2021 ◽  
Vol 7 ◽  
pp. e549
Author(s):  
Mariana R.F. Mota ◽  
Pedro H.L. Silva ◽  
Eduardo J.S. Luz ◽  
Gladston J.P. Moreira ◽  
Thiago Schons ◽  
...  
Keyword(s):  
Data Augmentation ◽  
Vital Signs ◽  
Motor Task ◽  
Eeg Signal ◽  
Convolutional Networks ◽  
Motor Movement ◽  
Biometric Verification ◽  
Evaluation Protocol ◽  
Novel Method ◽  
The Impact

Due to the application of vital signs in expert systems, new approaches have emerged, and vital signals have been gaining space in biometrics. One of these signals is the electroencephalogram (EEG). The motor task in which a subject is doing, or even thinking, influences the pattern of brain waves and disturb the signal acquired. In this work, biometrics with the EEG signal from a cross-task perspective are explored. Based on deep convolutional networks (CNN) and Squeeze-and-Excitation Blocks, a novel method is developed to produce a deep EEG signal descriptor to assess the impact of the motor task in EEG signal on biometric verification. The Physionet EEG Motor Movement/Imagery Dataset is used here for method evaluation, which has 64 EEG channels from 109 subjects performing different tasks. Since the volume of data provided by the dataset is not large enough to effectively train a Deep CNN model, it is also proposed a data augmentation technique to achieve better performance. An evaluation protocol is proposed to assess the robustness regarding the number of EEG channels and also to enforce train and test sets without individual overlapping. A new state-of-the-art result is achieved for the cross-task scenario (EER of 0.1%) and the Squeeze-and-Excitation based networks overcome the simple CNN architecture in three out of four cross-individual scenarios.

Epileptic Seizure Prediction Using Exponential Squirrel Atom Search Optimization-Based Deep Recurrent Neural Network

2021 ◽  
Vol 12 (3) ◽  
pp. 166-184
Author(s):  
Ratnaprabha Ravindra Pune Borhade ◽  
Manoj S. Nagmode
Keyword(s):  
Epileptic Seizure ◽  
Information Gain ◽  
Classical Method ◽  
The Novel ◽  
Eeg Signal ◽  
Search Optimization ◽  
Spectral Flux ◽  
Deep Recurrent Neural Network ◽  
Processing Module ◽  
Novel Method

Electroencephalogram (EEG) signal is broadly utilized for monitoring epilepsy and plays a key role to revitalize close loop brain. The classical method introduced to find the seizures relies on EEG signals which is complex as well as costly, if channel count increases. This paper introduces the novel method named exponential-squirrel atom search optimization (Exp-SASO) algorithm in order to train the deep RNN for discovering epileptic seizure. Here, the input EEG signal is given to the pre-processing module for enhancing the quality of image by reducing the noise. Then, the pre-processed image is forwarded to the feature extraction module. The features, like statistical features, spectral features, logarithmic band power, wavelet coefficients, common spatial patterns, along with spectral decrease, pitch chroma, tonal power ratio, and spectral flux, are extracted. Once the features are extracted, the feature selection is carried out using fuzzy information gain model for choosing appropriate features for further processing.

The removal and morphology of intact biofilms from implanted venous access devices

1995 ◽  
Vol 53 ◽  
pp. 1020-1021
Author(s):  
M.A. Gregory ◽  
G.P. Hadley
Keyword(s):  
Patient Selection ◽  
Surgical Oncology ◽  
Venous Access ◽  
Common Procedure ◽  
Indwelling Catheters ◽  
Careful Patient ◽  
Novel Method ◽  
The Subject ◽  
Vascular Catheters ◽  
Venous Access Devices

The insertion of implanted venous access systems for children undergoing prolonged courses of chemotherapy has become a common procedure in pediatric surgical oncology. While not permanently implanted, the devices are expected to remain functional until cure of the primary disease is assured. Despite careful patient selection and standardised insertion and access techniques, some devices fail. The most commonly encountered problems are colonisation of the device with bacteria and catheter occlusion. Both of these difficulties relate to the development of a biofilm within the port and catheter. The morphology and evolution of biofilms in indwelling vascular catheters is the subject of ongoing investigation. To date, however, such investigations have been confined to the examination of fragments of biofilm scraped or sonicated from sections of catheter. This report describes a novel method for the extraction of intact biofilms from indwelling catheters.15 children with Wilm’s tumour and who had received venous implants were studied. Catheters were removed because of infection (n=6) or electively at the end of chemotherapy.

Development of novel method for measuring optical activity of solids and its applications

1997 ◽  
Vol 71-72 (1-3) ◽  
pp. 403-425 ◽  
Author(s):  
J Kobayashi
Keyword(s):  
Optical Activity ◽  
Novel Method

Author response for "A novel method to identify Post‐Aire stages of medullary thymic epithelial cell differentiation"

2020 ◽  
Author(s):  
Pedro Ferreirinha ◽  
Camila Ribeiro ◽  
Junko Morimoto ◽  
Jonathan J. M. Landry ◽  
Minoru Matsumoto ◽  
...  
Keyword(s):  
Cell Differentiation ◽  
Epithelial Cell ◽  
Author Response ◽  
Thymic Epithelial Cell ◽  
Epithelial Cell Differentiation ◽  
Medullary Thymic Epithelial Cell ◽  
Novel Method

Longitudinal Changes in Individual BrainAGE in Healthy Aging, Mild Cognitive Impairment, and Alzheimer’s Disease

GeroPsych ◽  
2012 ◽  
Vol 25 (4) ◽  
pp. 235-245 ◽  
Author(s):  
Katja Franke ◽  
Christian Gaser
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Healthy Aging ◽  
Brain Aging ◽  
Elderly Subjects ◽  
Additional Increase ◽  
Longitudinal Changes ◽  
Novel Method ◽  
The Brain

We recently proposed a novel method that aggregates the multidimensional aging pattern across the brain to a single value. This method proved to provide stable and reliable estimates of brain aging – even across different scanners. While investigating longitudinal changes in BrainAGE in about 400 elderly subjects, we discovered that patients with Alzheimer’s disease and subjects who had converted to AD within 3 years showed accelerated brain atrophy by +6 years at baseline. An additional increase in BrainAGE accumulated to a score of about +9 years during follow-up. Accelerated brain aging was related to prospective cognitive decline and disease severity. In conclusion, the BrainAGE framework indicates discrepancies in brain aging and could thus serve as an indicator for cognitive functioning in the future.

Complexity Measures of Brain Electrophysiological Activity

2010 ◽  
Vol 24 (2) ◽  
pp. 131-135 ◽  
Author(s):  
Włodzimierz Klonowski ◽  
Pawel Stepien ◽  
Robert Stepien
Keyword(s):  
Brain Activity ◽  
Deterministic Chaos ◽  
Epileptic Seizures ◽  
Eeg Signal ◽  
Eeg Signals ◽  
Complexity Measures ◽  
Electrophysiological Activity ◽  
Signal Complexity ◽  
Physiological Sleep ◽  
The Brain

Over 20 years ago, Watt and Hameroff (1987 ) suggested that consciousness may be described as a manifestation of deterministic chaos in the brain/mind. To analyze EEG-signal complexity, we used Higuchi’s fractal dimension in time domain and symbolic analysis methods. Our results of analysis of EEG-signals under anesthesia, during physiological sleep, and during epileptic seizures lead to a conclusion similar to that of Watt and Hameroff: Brain activity, measured by complexity of the EEG-signal, diminishes (becomes less chaotic) when consciousness is being “switched off”. So, consciousness may be described as a manifestation of deterministic chaos in the brain/mind.

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