Dr Junhua LI

Peng, Y., Liu, H., Li, J., Huang, J., Lu, B-L. and Kong, W., (2023). Cross-session Emotion Recognition by Joint Label-common and Label-specific EEG Features Exploration. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 31, 759-768

Wang, Z., Chen, C., Li, J., Wan, F., Sun, Y. and Wang, H., (2023). ST-CapsNet: Linking Spatial and Temporal Attention with Capsule Network for P300 Detection Improvement. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 31, 991-1000

Zhang, Y., Peng, Y., Li, J. and Kong, W., (2023). SIFIAE: An adaptive emotion recognition model with EEG feature-label inconsistency consideration.. Journal of Neuroscience Methods. 395, 109909-109909

Xu, T., Zhou, Z., Yang, Y., Li, Y., Li, J., Bezerianos, A. and Wang, H., (2023). Motor Imagery Decoding Enhancement Based on Hybrid EEG-fNIRS Signals. IEEE Access. 11, 65277-65288

Jin, F., Peng, Y., Qin, F., Li, J. and Kong, W., (2023). Graph adaptive semi-supervised discriminative subspace learning for EEG emotion recognition. Journal of King Saud University - Computer and Information Sciences. 35 (8), 101648-101648

Yu, Y., Bezerianos, A., Cichocki, A. and Li, J., (2023). Latent Space Coding Capsule Network for Mental Workload Classification. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 31, 3417-3427

Zhu, L., Liu, Y., Liu, R., Peng, Y., Cao, J., Li, J. and Kong, W., (2023). Decoding Multi-Brain Motor Imagery From EEG Using Coupling Feature Extraction and Few-Shot Learning.. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 31, 4683-4692

Gong, S., Xing, K., Cichocki, A. and Li, J., (2022). Deep Learning in EEG: Advance of the Last Ten-Year Critical Period. IEEE Transactions on Cognitive and Developmental Systems. 14 (2), 348-365

Zhu, L., Cui, G., Li, Y., Zhang, J., Kong, W., Cichocki, A. and Li, J., (2022). Attention allocation on mobile app interfaces when human interacts with them. Cognitive Neurodynamics. 16 (4), 859-870

Duan, F., Lv, Y., Sun, Z. and Li, J., (2022). Multi-Scale Learning for Multimodal Neurophysiological Signals: Gait Pattern Classification as An Example. Neural Processing Letters. 54 (3), 2455-2470

Wang, T., Bezerianos, A., Cichocki, A. and Li, J., (2022). Multi-Kernel Capsule Network for Schizophrenia Identification. IEEE Transactions on Cybernetics. 52 (6), 4741-4750

Xu, T., Huang, J., Pei, Z., Chen, J., Li, J., Bezerianos, A., Thakor, N. and Wang, H., (2022). The Effect of Multiple Factors on Working Memory Capacities: Aging, Task difficulty, and Training. IEEE Transactions on Biomedical Engineering. 70 (6), 1967-1978

Harvy, J., Bezerianos, A. and Li, J., (2022). Reliability of EEG Measures in Driving Fatigue. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 30, 2743-2753

Wang, H., Liu, X., Li, J., Xu, T., Bezerianos, A., Sun, Y. and Wan, F., (2021). Driving Fatigue Recognition with Functional Connectivity Based on Phase Synchronization. IEEE Transactions on Cognitive and Developmental Systems. 13 (3), 668-678

Pei, Z., Wang, H., Bezerianos, A. and Li, J., (2021). EEG-Based Multi-Class Workload Identification Using Feature Fusion and Selection. IEEE Transactions on Instrumentation and Measurement. 70, 1-8

Wang, H., Pei, Z., Xu, L., Xu, T., Bezerianos, A., Sun, Y. and Li, J., (2021). Performance Enhancement of P300 Detection by Multi-Scale-CNN. IEEE Transactions on Instrumentation and Measurement. 70, 1-12

Li, J., (2021). Editorial: Recent Developments of Deep Learning in Analyzing, Decoding, and Understanding Neuroimaging Signals. Frontiers in Neuroscience. 15, 652073-

Li, J., (2021). Thoughts on Neurophysiological Signal Analysis and Classification. Brain Science Advances. 6 (3), 210-223

Wei, C-S., Keller, CJ., Li, J., Lin, Y-P., Nakanishi, M., Wagner, J., Wu, W., Zhang, Y. and Jung, T-P., (2021). Editorial: Inter- and Intra-subject Variability in Brain Imaging and Decoding.. Frontiers in Computational Neuroscience. 15, 791129-

Bose, R., Wang, H., Dragomir, A., Thakor, N., Bezerianos, A. and Li, J., (2020). Regression Based Continuous Driving Fatigue Estimation: Towards Practical Implementation. IEEE Transactions on Cognitive and Developmental Systems. 12 (2), 323-331

Wang, H., Tang, C., Xu, T., Li, T., Xu, L., Yue, H., Chen, P., Li, J. and Bezerianos, A., (2020). An Approach of One-vs-Rest Filter Bank Common Spatial Pattern and Spiking Neural Networks for Multiple Motor Imagery Decoding. IEEE Access. 8, 86850-86861

Wang, H., Xu, T., Tang, C., Yue, H., Chen, C., Xu, L., Pei, Z., Dong, J., Bezerianos, A. and Li, J., (2020). Diverse Feature Blend Based on Filter-Bank Common Spatial Pattern and Brain Functional Connectivity for Multiple Motor Imagery Detection. IEEE Access. 8, 155590-155601

Zhu, L., Su, C., Zhang, J., Cui, G., Cichocki, A., Zhou, C. and Li, J., (2020). EEG-based approach for recognizing human social emotion perception. Advanced Engineering Informatics. 46, 101191-101191

Li, J., Thakor, N. and Bezerianos, A., (2020). Brain functional connectivity in unconstrained walking with and without an exoskeleton. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 28 (3), 730-739

Feng, L., Romero-Garcia, R., Suckling, J., Tan, J., Larbi, A., Cheah, I., Wong, G., Tsakok, M., Lanskey, B., Lim, D., Li, J., Yang, J., Goh, B., Teck, TGC., Ho, A., Wang, X., Yu, J-T., Zhang, C., Tan, C., Chua, M., Li, J., Totman, JJ., Wong, C., Loh, M., Foo, R., Tan, CH., Goh, LG., Mahendran, R., Kennedy, BK. and Kua, E-H., (2020). Effects of choral singing versus health education on cognitive decline and aging: a randomized controlled trial. Aging. 12 (24), 24798-24816

Zhu, L., Zhou, C., Qu, Z. and Li, J., (2019). Monitoring time‐varying residential load operation modes: an efficient signal disaggregation approach. IEEJ Transactions on Electrical and Electronic Engineering. 14 (1), 85-96

Li, J., Dimitrakopoulos, GN., Thangavel, P., Chen, G., Sun, Y., Guo, Z., Yu, H., Thakor, N. and Bezerianos, A., (2019). What Are Spectral and Spatial Distributions of EEG-EMG Correlations in Overground Walking? An Exploratory Study. IEEE Access. 7, 143935-143946

Bose, R., Goh, SK., Wong, KF., Thakor, N., Bezerianos, A. and Li, J., (2019). Classification of Brain Signal (EEG) Induced by Shape-Analogous Letter Perception. Advanced Engineering Informatics. 42, 100992-100992

Li, J., Romero-Garcia, R., Suckling, J. and Feng, L., (2019). Habitual tea drinking modulates brain efficiency: evidence from brain connectivity evaluation. Aging. 11 (11), 3876-3890

Harvy, J., Thakor, N., Bezerianos, A. and Li, J., (2019). Between-Frequency Topographical and Dynamic High-Order Functional Connectivity for Driving Drowsiness Assessment. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 27 (3), 358-367

Li, J., Sun, Y., Huang, Y., Bezerianos, A. and Yu, R., (2019). Machine learning technique reveals intrinsic characteristics of schizophrenia: an alternative method. Brain Imaging and Behavior. 13 (5), 1386-1396

Li, J., Thakor, N. and Bezerianos, A., (2018). Unilateral Exoskeleton Imposes Significantly Different Hemispherical Effect in Parietooccipital Region, but Not in Other Regions. Scientific Reports. 8 (1), 13470-

Wang, H., Dragomir, A., Abbasi, NI., Li, J., Thakor, NV. and Bezerianos, A., (2018). A novel real-time driving fatigue detection system based on wireless dry EEG. Cognitive Neurodynamics. 12 (4), 365-376

Yokota, T., Struzik, ZR., Jurica, P., Horiuchi, M., Hiroyama, S., Li, J., Takahara, Y., Ogawa, K., Nishitomi, K., Hasegawa, M. and Cichocki, A., (2018). Semi-Automated Biomarker Discovery from Pharmacodynamic Effects on EEG in ADHD Rodent Models. Scientific Reports. 8 (1), 5202-

Jurica, P., Struzik, ZR., Li, J., Horiuchi, M., Hiroyama, S., Takahara, Y., Nishitomi, K., Ogawa, K. and Cichocki, A., (2018). Combining behavior and EEG analysis for exploration of dynamic effects of ADHD treatment in animal models. Journal of Neuroscience Methods. 298, 24-32

Goh, SK., Abbass, HA., Tan, KC., Al-Mamun, A., Thakor, N., Bezerianos, A. and Li, J., (2018). Spatio–Spectral Representation Learning for Electroencephalographic Gait-Pattern Classification. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 26 (9), 1858-1867

Sun, Y., Li, J., Suckling, J. and Feng, L., (2017). Asymmetry of Hemispheric Network Topology Reveals Dissociable Processes between Functional and Structural Brain Connectome in Community-Living Elders. Frontiers in Aging Neuroscience. 9 (NOV)

Dai, Z., de Souza, J., Lim, J., Ho, PM., Chen, Y., Li, J., Thakor, N., Bezerianos, A. and Sun, Y., (2017). EEG Cortical Connectivity Analysis of Working Memory Reveals Topological Reorganization in Theta and Alpha Bands. Frontiers in Human Neuroscience. 11

Li, J., Chen, Y., Taya, F., Lim, J., Wong, K., Sun, Y. and Bezerianos, A., (2017). A unified canonical correlation analysis-based framework for removing gradient artifact in concurrent EEG/fMRI recording and motion artifact in walking recording from EEG signal. Medical & Biological Engineering & Computing. 55 (9), 1669-1681

Sun, Y., Dai, Z., Li, J., Collinson, SL. and Sim, K., (2017). Modular‐level alterations of structure–function coupling in schizophrenia connectome. Human Brain Mapping. 38 (4), 2008-2025

Ren, S., Li, J., Taya, F., deSouza, J., Thakor, NV. and Bezerianos, A., (2017). Dynamic Functional Segregation and Integration in Human Brain Network During Complex Tasks. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 25 (6), 547-556

Sun, Y., Lim, J., Dai, Z., Wong, K., Taya, F., Chen, Y., Li, J., Thakor, N. and Bezerianos, A., (2017). The effects of a mid-task break on the brain connectome in healthy participants: A resting-state functional MRI study. NeuroImage. 152, 19-30

Li, J., Li, C. and Cichocki, A., (2017). Canonical Polyadic Decomposition With Auxiliary Information for Brain–Computer Interface. IEEE Journal of Biomedical and Health Informatics. 21 (1), 263-271

Li, J., Lim, J., Chen, Y., Wong, K., Thakor, N., Bezerianos, A. and Sun, Y., (2016). Mid-Task Break Improves Global Integration of Functional Connectivity in Lower Alpha Band. Frontiers in Human Neuroscience. 10

Li, J., Wang, Y., Zhang, L., Cichocki, A. and Jung, T-P., (2016). Decoding EEG in Cognitive Tasks With Time-Frequency and Connectivity Masks. IEEE Transactions on Cognitive and Developmental Systems. 8 (4), 298-308

Bodala, IP., Li, J., Thakor, NV. and Al-Nashash, H., (2016). EEG and Eye Tracking Demonstrate Vigilance Enhancement with Challenge Integration. Frontiers in Human Neuroscience. 10

Dai, Z., Chen, Y., Li, J., Fam, J., Bezerianos, A. and Sun, Y., (2016). Temporal efficiency evaluation and small-worldness characterization in temporal networks. Scientific Reports. 6 (1)

Li, J., Struzik, Z., Zhang, L. and Cichocki, A., (2015). Feature learning from incomplete EEG with denoising autoencoder. Neurocomputing. 165, 23-31

Liu, Y., Li, M., Zhang, H., Wang, H., Li, J., Jia, J., Wu, Y. and Zhang, L., (2014). A tensor-based scheme for stroke patients’ motor imagery EEG analysis in BCI-FES rehabilitation training. Journal of Neuroscience Methods. 222, 238-249

LI, J., LIANG, J., ZHAO, Q., LI, JIE., HONG, KAN. and ZHANG, L., (2013). DESIGN OF ASSISTIVE WHEELCHAIR SYSTEM DIRECTLY STEERED BY HUMAN THOUGHTS. International Journal of Neural Systems. 23 (03), 1350013-1350013

Li, J. and Zhang, L., (2012). Active training paradigm for motor imagery BCI. Experimental Brain Research. 219 (2), 245-254

Li, J. and Zhang, L., (2010). Bilateral adaptation and neurofeedback for brain computer interface system. Journal of Neuroscience Methods. 193 (2), 373-379

Zian, P., Tao, X., Anastasios, B., Li, J., Yu, S. and Hongtao, W., (2020). The Effect of Longitudinal Training on Working Memory Capacities: An Exploratory EEG Study

Harvy, J., Ewen, JB., Thakor, N., Bezerianos, A. and Li, J., (2019). Cortical Functional Connectivity during Praxis in Autism Spectrum Disorder

Sigalas, E., Li, J., Bezerianos, A. and Antonopoulos, C., (2018). Emergence of chimera-like states in prefrontal-cortex macaque intracranial recordings

Harvy, J., Sigalas, E., Thakor, N., Bezerianos, A. and Li, J., (2018). Performance Improvement of Driving Fatigue Identification Based on Power Spectra and Connectivity Using Feature Level and Decision Level Fusions

He, J., Zhou, G., Wang, H., Sigalas, E., Thakor, N., Bezerianos, A. and Li, J., (2018). Boosting Transfer Learning Improves Performance of Driving Drowsiness Classification Using EEG

Dimitrakopoulos, GN., Kakkos, I., Vrahatis, AG., Sgarbas, K., Li, J., Sun, Y. and Bezerianos, A., (2017). Driving Mental Fatigue Classification Based on Brain Functional Connectivity