Haider Raza

Haider Raza

Lecturer in AI for Decision Making, School of Computer Science and Electronics Engineering, University of Essex

Publications

A magnetoencephalography dataset for motor and cognitive imagery-based brain-computer interface

Published in Scientific Data, 2021

The dataset will be available for all AI and ML researchers around the globe to test/explore their MachineLearning and DataAnalytics algorithms to the first publicly available 306 channel four class MEG BCI data.

Recommended citation: Rathee, D., Raza, H., Roy, S., and Prasad, G. A magnetoencephalography dataset for motor and cognitive imagery-based brain-computer interface. Scientific Data, Nature.

Deep Learning based Prediction of EEG Motor Imagery of Stroke Patients’ for Neuro-Rehabilitation Application

Published in IEEE-IJCNN, Glasgow, Scotland, 2020

This paper focused on using Deep Learning Model (i.e. EEGNet) on Patient’s Data.

Recommended citation: Raza, H., Chowdhury, A., and Bhattacharyya, S. Deep Learning based Prediction of EEG Motor Imagery of Stroke Patients’ for Neuro-Rehabilitation Application. IEEE-IJCNN./i>. </p> </article> </div>

Bagging Adversarial Neural Networks for Domain Adaptation in Non-Stationary EEG

Published in IEEE-IJCNN, 2019

This paper implemented the GAN in EEG signals for domain adaptation

Recommended citation: Raza, H., and Samothrakis, S. Bagging Adversarial Neural Networks for Domain Adaptation in Non-Stationary EEG. 2019 International Joint Conference on Neural Networks (IJCNN). Budapest, Hungary, 2019, pp. 1-7.

Predictors of Objectively Measured Physical Activity in 12 month-Old Infants: A Study of Linked Birth Cohort Data with Electronic Health Records

Published in Paediatric Obesity, 2019

This paper examines factors associated with PA levels in 12‐month infants.

Recommended citation: Raza, H., Zhou, S., Todd, S., Christian, D., Merchant, E., Morgan, K., Khanom, A., Hill, R., Lynos, R., and Brophy, S. Predictors of objectively measured physical activity in 12‐month‐old infants: A study of linked birth cohort data with electronic health records. Pediatric obesity, p.e12512..

An EEG-EMG correlation-based brain-computer interface for hand orthosis supported neuro-rehabilitation

Published in Journal of neuroscience methods, 2019

In this study, we have introduced a new corticomuscular feature extraction method based on the correlation between band-limited power time-courses (CBPT) associated with EEG and EMG. 16 healthy individuals and 8 hemiplegic patients participated in a BCI-based hand orthosis triggering task, to test the performance of the CBPT method. The healthy population was equally divided into two groups; one experimental group for CBPT-based BCI experiment and another control group for EEG-EMG coherence based BCI experiment.

Recommended citation: Chowdhury, A., Raza, H., Meena, YK., Dutta, A., and Prasad, G. (2019). An EEG-EMG correlation-based brain-computer interface for hand orthosis supported neuro-rehabilitation. Journal of neuroscience methods, 2019.

Active Physical Practice Followed by Mental Practice Using BCI-Driven Hand Exoskeleton: A Pilot Trial for Clinical Effectiveness and Usability

Published in IEEE Journal of Biomedical and Health Informatics, 2018

This paper is about the BCI-driven handexoskeleton trails conducted on stroke participants.

Recommended citation: Chowdhury, A., Meena, YK., Raza, H., Bhushan, B., Uttam, AK., Pandey, N., Hashmi, AA., Bajpai, A., Dutta, A., and Prasad, G. (2018). Active Physical Practice Followed by Mental Practice Using BCI-Driven Hand Exoskeleton: A Pilot Trial for Clinical Effectiveness and Usability. IEEE Journal of Biomedical and Health Informatics, 2018.

Covariate Shift Estimation and Adaptation based Ensemble Learning for Handling Inter-or-Intra Session Non- Stationarity in EEG based Brain-Computer Interface

Published in Neurocomputing, 2018

This paper is about the adapting non-stationarity in EEG signals using ensemble learning methods.

Recommended citation: Raza, H., Rathee, D., Zhou, SM., Cecotti, H., and Prasad, G. (2018). Covariate Shift Estimation and Adaptation based Ensemble Learning for Handling Inter-or-Intra Session Non- Stationarity in EEG based Brain-Computer Interface.; Neurocomputing, 2018.

Published in , 2022

Online Covariate Shift Detection based Adaptive Brain-Computer Interface to Trigger Hand Exoskeleton Feedback for Neuro-Rehabilitation.

Published in IEEE Transactions on Cognitive and Developmental Systems, 2017

This paper is about detecting covariate shift and adaption in an online BCI system.

Recommended citation: Chowdhury, A., Raza., H., Meena, Y.K., Dutta, A., and Prasad,G. (2017). "Online Covariate Shift Detection based Adaptive Brain-Computer Interface to Trigger Hand Exoskeleton Feedback for Neuro-Rehabilitation." IEEE-TCDS-2017. 1(1).

Identification of predictors of objectively measured physical activity in 12-month-old British infants: a machine learning driven study.

Published in The Lancet, 2017

This paper is about finding predictors of objectively measured physical activity in 12-month-old British infants

Recommended citation: Raza, H., Zhou, SM., Hill, R., Lyons, RA., Brophy, S. (2017). "Identification of predictors of objectively measured physical activity in 12-month-old British infants: a machine learning driven study." The Lancet, 2017. 390, S74.

Current source density estimation enhances the performance of motor-imagery-related brain–computer interface.

Published in IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2017

This paper is about CSD pre-processing method for enhanceing the performance of motor-imagery-related brain–computer interface.

Recommended citation: Rathee, D., Raza., H., Prasad, G., and Cecotti, H. (2017). "Current source density estimation enhances the performance of motor-imagery-related brain–computer interface." IEEE-TNSRE, 2017. 25(12), 2461 - 2471.

Published in , 2022

A combination of transductive and inductive learning for handling non-stationarities in motor imagery classification.

Published in International Joint Conference on Neural Networks (IJCNN), 2016, 2016

This paper is proposes a combination of transductive and inductive learning for managing non-stationarity in EEG-based BCI

Recommended citation: Raza, H., Cecotti, H., and Prasad, G. (2016). "A combination of transductive and inductive learning for handling non-stationarities in motor imagery classification." IEEE-IJCNN, 2016. 1(1).

Published in , 2022