Anirban Chowdhury

University of Essex — United Kingdom

Neuroscience · Life Sciences

16h-index981citations30works3.82yr avg
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Research Topics

EEG and Brain-Computer Interfaces(25), Neuroscience and Neural Engineering(10), Stroke Rehabilitation and Recovery(7), Functional Brain Connectivity Studies(6), Muscle activation and electromyography studies(6)

Publications30 total

Neurestore: A New Benchmark for Wearable BCI-Based Neuromotor Training in Real-World
IEEE Access·2026Open Access
Exploring Pupil Dilation as an Indicator of Performance in Gaze-Based Robot Navigation for Assistive Technology
2024· 1 cited
Acceleration of EEG Signal Processing on FPGA: A Step Towards Embedded BCI
2024· 3 cited
Pupil Diameter Classification using Machine Learning During Human-Computer Interaction
2024· 2 cited
Advancements in Temporal Fusion: A New Horizon for EEG-Based Motor Imagery Classification
IEEE Transactions on Medical Robotics and Bionics·2024· 8 cited
SCSP-3: A Spectrally Augmented Common Spatial Pattern Approach for Robust Motor Imagery-Based Brain–Computer Interface
IEEE Sensors Journal·2024· 9 cited
3D localization of objects of daily living activities for rehabilitation applications
2023· 2 cited
Sliding Window Along With EEGNet-Based Prediction of EEG Motor Imagery
IEEE Sensors Journal·2023· 35 cited
Clinical Brain–Computer Interface Challenge 2020 (CBCIC at WCCI2020): Overview, Methods and Results
IEEE Transactions on Medical Robotics and Bionics·2021· 23 citedOpen Access
Logistic Regression With Tangent Space-Based Cross-Subject Learning for Enhancing Motor Imagery Classification
IEEE Transactions on Cognitive and Developmental Systems·2021· 36 citedOpen Access
Real time estimation of task specific self-confidence level based on brain signals
Multimedia Tools and Applications·2021· 8 cited
A Sliding Window Common Spatial Pattern for Enhancing Motor Imagery Classification in EEG-BCI
IEEE Transactions on Instrumentation and Measurement·2021· 254 citedOpen Access
Assessing impact of channel selection on decoding of motor and cognitive imagery from MEG data
Journal of Neural Engineering·2020· 34 citedOpen Access
Deep Learning Based Inter-subject Continuous Decoding of Motor Imagery for Practical Brain-Computer Interfaces
Frontiers in Neuroscience·2020· 61 citedOpen Access
Single-Trial EEG Classification with EEGNet and Neural Structured Learning for Improving BCI Performance
2020· 37 cited
Deep Learning based Prediction of EEG Motor Imagery of Stroke Patients’ for Neuro-Rehabilitation Application
2020· 47 cited
Cortico-Muscular-Coupling and Covariate Shift Adaptation based BCI for Personalized Neuro- Rehabilitation of Stroke Patients
TUGraz OPEN Library (Graz University of Technology)·2020· 3 citedOpen Access
Corticomuscular Co-Activation Based Hybrid Brain-Computer Interface for Motor Recovery Monitoring
IEEE Access·2020· 18 citedOpen Access
Can Corticomuscular Coupling be Useful in Designing Hybrid-Brain Robot Interfaces Towards Hand Functional Recovery?
2019· 4 cited
Brain–Machine Interface-Driven Post-Stroke Upper-Limb Functional Recovery Correlates With Beta-Band Mediated Cortical Networks
IEEE Transactions on Neural Systems and Rehabilitation Engineering·2019· 38 citedOpen Access
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Frequent Co-authors

Girijesh Prasad(14), Ashish Dutta(13), Haider Raza(8), Yogesh Kumar Meena(7), Karl McCreadie(4), Pramod Gaur(3), Ram Bilas Pachori(3), Hui Wang(2), Braj Bhushan(2), Sujit Roy(2), Saugat Bhattacharyya(2), Dheeraj Rathee(2), Shyam Sunder Nishad(2), Hubert Cecotti(2), Saran Kundu(2), Aman Singh Tomar(2), Subhasis Bhaumik(2), Parastoo Azizinezhad(2), Harsh Gupta(1), Ashwani Kumar Uttam(1)