scholarly journals A deep neural network classifier for P300 BCI speller based on Cohen's class time-frequency distribution

2021 ◽  
Keyword(s):  
Neural Network ◽  
Frequency Distribution ◽  
Deep Neural Network ◽  
Neural Network Classifier ◽  
Time Frequency ◽  
Class Time ◽  
Cohen's Class ◽  
Time Frequency Distribution

scholarly journals Featureless EMG pattern recognition based on convolutional neural network

2019 ◽  
Vol 14 (3) ◽  
pp. 1291
Author(s):  
Too Jing Wei ◽  
Abdul Rahim Bin Abdullah ◽  
Norhashimah Binti Mohd Saad ◽  
Nursabillilah Binti Mohd Ali ◽  
Tengku Nor Shuhada Binti Tengku Zawawi
Keyword(s):  
Neural Network ◽  
Pattern Recognition ◽  
Feature Extraction ◽  
Convolutional Neural Network ◽  
Frequency Distribution ◽  
Classification Accuracy ◽  
Time Frequency ◽  
Frequency Representation ◽  
Emg Pattern Recognition ◽  
Time Frequency Distribution

In this paper, the performance of featureless EMG pattern recognition in classifying hand and wrist movements are presented. The time-frequency distribution (TFD), spectrogram is employed to transform the raw EMG signals into time-frequency representation (TFR). The TFRs or spectrogram images are then directly fed into convolutional neural network (CNN) for classification. Two CNN models are proposed to learn the features automatically from the images without the need of manual feature extraction. The performance of CNN with different number of convolutional layers is examined. The proposed CNN models are evaluated using the EMG data from 10 intact and 11 amputee subjects through the publicly access NinaPro database. Our results show that CNN classifier offered the best mean classification accuracy of 88.04% in recognizing hand and wrist movements.

Withdrawn: Automated Diagnosis of Glaucoma Using Deep Neural Network Classifier

2019 ◽  
Vol 14 ◽  
Author(s):  
M. Madhumalini ◽  
T. Meera Devi
Keyword(s):  
Neural Network ◽  
Signal Transduction ◽  
Deep Neural Network ◽  
Neural Network Classifier ◽  
Current Signal ◽  
Automated Diagnosis ◽  
Signal Transduction Therapy ◽  
Copyright Permission ◽  
Legal Right

The article has been withdrawn on the request of the authors and the editor of the journal Current Signal Transduction Therapy. Bentham Science apologizes to the readers of the journal for any inconvenience this may have caused. BENTHAM SCIENCE DISCLAIMER: It is a condition of publication that manuscripts submitted to this journal have not been published and will not be simultaneously submitted or published elsewhere. Furthermore, any data, illustration, structure or table that has been published elsewhere must be reported, and copyright permission for reproduction must be obtained. Plagiarism is strictly forbidden, and by submitting the article for publication the authors agree that the publishers have the legal right to take appropriate action against the authors, if plagiarism or fabricated information is discovered. By submitting a manuscript the authors agree that the copyright of their article is transferred to the publishers, if and when the article is accepted for publication.

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