Electrocorticography based motor imagery movements classification using long short-term memory (LSTM) based on deep learning approach

QR Code

Electrocorticography based motor imagery movements classification using long short-term memory (LSTM) based on deep learning approach

Brain–computer interface (BCI) is an important alternative for disabled people that enables the innovative communication pathway among individual thoughts and different assistive appliances. In order to make an efficient BCI system, different physiological signals from the brain have been utilized f...

Full description

Bibliographic Details
Main Authors:	Rashid, Mamunur, Islam, Minarul, Norizam, Sulaiman, Bari, Bifta Sama, Saha, Ripon Kumar, Hasan, Md Jahid
Format:	Article
Language:	English
Published:	Springer Nature 2020
Subjects:	TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://umpir.ump.edu.my/id/eprint/27512/ http://umpir.ump.edu.my/id/eprint/27512/1/Electrocorticography%20based%20motor%20imagery1.pdf

Similar Items

Empirical Mode Decomposition Coupled with Fast Fourier Transform based Feature Extraction Method for Motor Imagery Tasks Classification
by: Islam, Md Nahidul, et al.
Published: (2020)

The classification of motor imagery response: an accuracy enhancement through the ensemble of random subspace k-NN
by: Rashid, Mamunur, et al.
Published: (2021)

Recent Trends and Open Challenges in EEG based Brain-Computer Interface Systems
by: Rashid, Mamunur, et al.
Published: (2019)

Wink based facial expression classification using machine learning approach
by: Rashid, Mamunur, et al.
Published: (2020)

Auditory Evoked Potential (AEP) Based Brain-Computer Interface (BCI) Technology: A Short Review
by: Islam, Md Nahidul, et al.
Published: (2021)

Prediction of dengue cases using the attention-based long short-term memory (LSTM) approach
by: Majeed, Mokhalad A., et al.
Published: (2023)

A hybrid environment control system combining EMG and SSVEP signal based on brain-computer interface technology
by: Rashid, Mamunur, et al.
Published: (2021)

A hybrid scheme for AEP based hearing deficiency diagnosis: CWT and convoluted k-nearest neighbour (CKNN) pipeline
by: Islam, Md Nahidul, et al.
Published: (2022)

Five-Class SSVEP Response Detection using Common Spatial Pattern (CSP)-SVM Approach
by: Rashid, Mamunur, et al.
Published: (2020)

Cardiotocogram Data Classification using Random Forest based Machine Learning Algorithm
by: Molla, M. M. Imran, et al.
Published: (2020)

Evaluation of time-domain features for motor imagery movements using FCM and SVM
by: Khorshidtalab, Aida, et al.
Published: (2012)

Evaluating the effectiveness of time-domain features for motor imagery movements using SVM
by: Khorshidtalab, Aida, et al.
Published: (2012)

Flat Price Prediction using Linear and Random Forest Regression based on Machine Learning Techniques
by: Jui, Julakha Jahan, et al.
Published: (2020)

3D visualization of movements can amplify motor cortex activation during subsequent motor imagery
by: Sollfrank, T., et al.
Published: (2015)

Motor imagery ability and internal representation of movement in children with probable developmental coordination disorder
by: Reynolds, J., et al.
Published: (2015)

The classification of EEG signal processing using different machine learning techniques for BCI application
by: Rashid, Mamunur, et al.
Published: (2019)

Motor imagery task classification using transformation based features
by: Khorshidtalab, Aida, et al.
Published: (2017)

Hearing disorder detection using auditory evoked potential (AEP) signals
by: Islam, Md Nahidul, et al.
Published: (2020)

Microsleep Predicting Comparison Between LSTM and ANN Based on the Analysis of Time Series EEG Signal
by: Hasan, Md Mahmudul, et al.
Published: (2024)

Structural damage quantification using long short-term memory (LSTM) auto-encoder and impulse response functions
by: Chencho,, et al.
Published: (2024)

Further Validation and Development of the Movement Imagery Questionnaire
by: Williams, S., et al.
Published: (2012)

A transform-based feature extraction approach for motor imagery tasks classification
by: Baali, Hamza, et al.
Published: (2015)

Rice disease identiﬁcation through leaf image and iot based smart rice fieldmonitoring system
by: Islam, Md Nahidul, et al.
Published: (2022)

Rice disease identification through leaf image and IoT based smart rice field monitoring system
by: Islam, Md Nahidul, et al.
Published: (2022)

Investigating the Possibility of Brain Actuated Mobile Robot through Single Channel EEG Headset
by: Rashid, Mamunur, et al.
Published: (2019)

Performance comparison of early breast cancer detection precision using ai and ultra-wideband (UWB) bio-antennas
by: Bari, Bifta Sama, et al.
Published: (2020)

Optimising LSTM and BiLSTM models for time series forecasting through hyperparameter tuning
by: Nur Haizum, Abd Rahman, et al.
Published: (2025)

A real-time approach of diagnosing rice leaf disease using deep learning-based faster R-CNN framework
by: Bari, Bifta Sama, et al.
Published: (2021)

Analysis of EEG features for brain computer interface application
by: Rashid, Mamunur, et al.
Published: (2019)

Channel selection for common spatial pattern Based on energy calculation of motor imagery EEG signal
by: Hilman, Fauzi, et al.
Published: (2017)

A novel BiGRUBiLSTM model for Multilevel Sentiment Analysis Using Deep Neural Network with BiGRU-BiLSTM
by: Islam, Md Shofiqul, et al.
Published: (2021)

Current status, challenges, and possible solutions of EEG-based brain-computer interface: a comprehensive review
by: Rashid, Mamunur, et al.
Published: (2020)

The Classiﬁcation of Electrooculogram (EOG) through the application of Linear Discriminant Analysis (LDA) of selected time-domain signals
by: Farhan Anis, Azhar, et al.
Published: (2022)

The classification of Electrooculogram (EOG) through the application of Linear Discriminant Analysis (LDA) of selected time-domain signals
by: Farhan Anis, Azhar, et al.
Published: (2022)

Offline EEG-based DC Motor Control for Wheelchair Application
by: Norizam, Sulaiman, et al.
Published: (2019)

Driver’s fatigue classification based on physiological signals using RNN-LSTM technique
by: Rabea, Ahmed Faozi Ahmed, et al.
Published: (2022)

Hyperspectral image classification by integrating attention-based LSTM and hybrid spectral networks
by: Ahmed AL-Kubaisi, Mohammed, et al.
Published: (2022)

Nonlinear Chemical Process Monitoring And Fault Detection Based On Modified Lstm Model
by: Zambri, Muhammad Ridzuan
Published: (2022)

Sign language recognition using deep learning through LSTM and CNN
by: Kiran, Pandian, et al.
Published: (2023)

Kesan Latihan Imageri Terhadap Prestasi Kemahiran Motor Diskrit
by: Abd. Ghani, Norzah
Published: (1997)