Feng WAN萬 峰
Associate Professor

Academic Qualifications | Teaching | Research | Awards | Selected Publications | Professional Affiliations | Contact Details


Academic Qualification

  • Ph.D in Electrical and Electronics Engineering, The Hong Kong University of Science and Technology, Hong Kong
  • M.Eng. in Control Theory and Engineering, Institute of Industrial Process Control, Zhejiang University, China
  • B.Eng. in Material Science and Engineering & B.Eng. in Electronics Engineering, Tianjin University, China

Teaching

B.Sc. Courses

  1. Quality Control (ELEC200)
  2. Probability and Statistics (ECEN2007)
  3. Control Systems (ECEN3000)
  4. Computer and Microprocessor Control Systems (ELEC409)
  5. Graduation Project I (ECEN4000)
  6. Graduation Project II (ECEN4001)
  7. Honours Project (HONR4000)

M.Sc. and PhD Courses

  1. Introduction to Research (ECEN7001)
  2. Advanced Topics in Control Systems (ECEN7006)
  3. Expert Systems (ECEN7008)
  4. Advanced Signal Processing and Analysis (ELCE801)
  5. Computational Intelligence and Intelligent Control (ELCE802)
  6. Advanced Topics in Electrical and Computer Engineering (ECEN8001)
  7. Thesis (ECEN7999)
  8. Thesis (ECEN8999)

Research

Research Interests

  • Biomedical Engineering: Brain-Computer Interfaces, Biomedical Signal Processing, Brain Imaging and Neurofeedback Training
  • Computational Intelligence and Machine Learning: Fuzzy Systems, Neural Networks, Deep and Transfer Learning
  • Control: Intelligent Control, Process Control, Nonlinear and Adaptive Control

Recent Research Projects

  • Decision-Making: EEG-Based Brain Network, Prediction and Intervention, by FDCT-NSFC Joint Scientific Research Project Funding, Principal Investigator, 2020-2022.
  • Steady-State Visual Evoked Potential-Based Brain Computer Interface Illiteracy: Its Assessment, Prediction and Improvement, funded by the Research Committee of University of Macau, Principal Investigator, 2018-2020.
  • Prediction of Learning Effectiveness in Neurofeedback Training, funded by the Research Committee of University of Macau, Principal Investigator, 2017-2019.
  • Neurofeedback Training Approach to the Performance Enhancement of Steady-State Visual Evoked Potential-based Brain-Computer Interfaces, funded by Macau Science and Technology Development Fund, Principal Investigator, 2016-2018.

Awards

  • 2019 World Robot Conference Brain-Computer Interfaces Contest / The Third China Brain-Computer Interfaces Contest (organized by NSFC, Chinese Institute of Electronics, and Tsinghua University, more than 400 teams participated in 3 technical competitions):
    (1) Grand Champion, (2) Brain-Computer Interfaces Tying Record, (3) SSVEP-Based Brain-Computer Interfaces Competition Champion, (4) Motor Imagery-Based Brain-Computer Interfaces Competition Champion.
    2019世界機器人大會腦控機器人大賽暨第三屆中國腦機接口比賽(國家自然科學基金委員會、中國電子學會及清華大學主辦,400余支參賽隊參加共三項單項技術賽),獲:
    技術賽總冠軍/特等獎、創腦控打字記錄、枕葉腦機組/基於穩態視覺誘發電位的腦機接口系統技術賽冠軍、顳葉腦機組/基於運動想像的腦機接口系統技術賽冠軍

Selected Publications

Selected Journal Papers

  1. “Changes of EEG phase synchronization and EOG signals along the use of SSVEP-based BCI,” Journal of Neural Engineering, DOI: 10.1088/1741-2552/ab933e, in press, 2020.
  2. “Common spatial pattern reformulated for regularizations in brain-computer interfaces,” IEEE Trans. on Cybernetics, DOI: 10.1109/TCYB.2020.2982901, Early Access, 2020.
  3. “Driving fatigue recognition with functional connectivity based on phase synchronization,” IEEE Trans. on Cognitive and Developmental Systems, DOI: 10.1109/TCDS.2020.2985539, Early Access, 2020.
  4. “Spatial filtering in SSVEP-based BCIs: Unified framework and new improvements,” IEEE Trans. on Biomedical Engineering, DOI: 10.1109/TBME.2020.2975552, Early Access, 2020.
  5. “Alpha down-regulation neurofeedback training facilitates implicit motor learning and consolidation,” Journal of Neural Engineering, 17(2), 026014, 2020.
  6. “Consensus on the reporting and experimental design of clinical and cognitive-behavioural neurofeedback studies (CRED-nf checklist),” Brain, DOI: 10.1093/brain/awaa009, 2020.
  7. “Effect of brain alpha oscillation on the performance in laparoscopic skills simulator training,” Surgical Endoscopy, DOI: 10.1007/s00464-020-07419-5, [Epub ahead of print], 2020.
  8. “Learning across multi-stimulus enhances target recognition methods in SSVEP-based BCIs,” Journal of Neural Engineering, 17(1), 016026, 2020.
  9. “Fatigue evaluation using multi-scale entropy of EEG in SSVEP-Based BCI,” IEEE Access, 7, 108200-108210, 2019.
  10. “Predicting individual decision-making responses based on the functional connectivity of resting-state EEG,” Journal of Neural Engineering, 16(6), 066025, 2019.
  11. “Competing with multinational enterprise’ entry: Search strategy, environmental complexity and survival of local firms,” International Business Review, 28(4), 727-738, 2019.
  12. “Sparse EEG source localization using LAPPS: Least absolute lp (0<p<1) penalized solution,” IEEE Trans. on Biomedical Engineering, 66(7), 1927-1939, 2018.
  13. “Fast basis search for adaptive Fourier decomposition,” EURASIP Journal on Advances in Signal Processing, 1, 74, 2018.
  14. “Eyes-closed resting EEG predicts the learning of alpha down-regulation in neurofeedback training,” Frontiers in Psychology, 9, 1067, 2018.
  15. “Reliable detection of implicit waveform-specific learning in continuous tracking task paradigm,” Scientific Reports, 7(1):12333, Sep. 26, 2017.
  16. “An exploratory study of intensive neurofeedback training for schizophrenia,” Behavioural Neurology, Article ID: 6914216, pp. 1-7, 2017.
  17. “Adaptive Fourier decomposition based ECG denoising,” Computers in Biology and Medicine, 77, 195-205, 2016.
  18. “Alpha neurofeedback training improves SSVEP-based BCI performance,” Journal of Neural Engineering, 13(3), 036019, 2016.
  19. “Resting and initial beta amplitudes predict learning ability in beta/theta ratio neurofeedback training in healthy young adults,” Frontiers in Human Neuroscience, 9:677, 2015.
  20. “Adaptive time-window length based on online performance measurement in SSVEP-based BCIs,” Neurocomputing, 149(A), 93-99, 2015.
  21. “Dynamic peripheral visual performance relates to alpha activity in soccer players,” Frontiers in Human Neuroscience, 8:913, 2014.
  22. “Objective evaluation of fatigue by EEG spectral analysis in steady-state visual evoked potential-based brain-computer interfaces,” Biomedical Engineering Online, 13(28), 2014.
  23. “Resting alpha activity predicts learning ability in alpha neurofeedback,” Frontiers in Human Neuroscience, 8:500, 2014.
  24. “Peripheral visual performance enhancement by neurofeedback training,” Applied Psychophysiology and Biofeedback, 38(4), 285-291, 2013.
  25. “15-nW biopotential LPFs in 0.35-µm CMOS using subthreshold-source-follower biquads with and without gain compensation,” IEEE Trans. on Biomedical Circuits and Systems, 7(5), 690-702, 2013.
  26. “One-unit second order blind identification (SOBI) with reference for short transient signals,” Information Sciences, 227, 90-101, 2013.
  27. “Individual alpha neural feedback training effect on short-term memory,” International Journal of Psychophysiology, 86(1), 83-87, 2012.
  28. “A 0.83-µW QRS detection processor using quadratic spline wavelet transform for wireless ECG acquisition in 0.35-µm CMOS,” IEEE Trans. on Biomedical Circuits and Systems, 6(6), 586-595, 2012.
  29. “A fast adaptive model reduction method based on Takenaka-Malmquist systems,” Systems and Control Letters, 61(1), 223-230, 2012.
  30. “Further study on the parameter convergence of fuzzy models in nonlinear system identifications,” Acta Automatica Sinica, 33(1), 109-112, 2007.
  31. “How to determine the minimum number of fuzzy rules to achieve given accuracy: A computational geometric approach to SISO case,” Fuzzy Sets and Systems, 150(2), 199-209, 2005.
  32. “Nonlinear discrete-time system identifications based on fuzzy models: Algorithms and performance analyses,” Acta Automatica Sinica, 30(6), 844-853, 2004.
  33. “Structured neural networks for constrained model predictive control,” Automatica, 37(8), 1235-1243, 2001.

Recent Conference Papers

  1. “EEG-based emotion recognition under convolutional neural network with differential entropy feature maps,” 2019 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA), Tianjin, June 2019.
  2. “Influence of stimuli color combination on online SSVEP-based BCI performance,” 2019 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA), Tianjin, June 2019.
  3. “A spiking neural network model mimicking the olfactory cortex for handwritten digit recognition,” The 9th International IEEE/EMBS Conference on Neural Engineering (NER), pp: 1167-1170, San Francisco, CA, USA, March 2019.
  4. “Learning prototype spatial filters for subject-independent SSVEP-based brain computer interface”, 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC), Miyazaki, Japan, Oct. 7-10, 2018.
  5. “Area-to-area transfer improves single-channel SSVEP classification”, The 7th International Brain-Computer Interface (BCI) Meeting, Pacific Grove, CA, May 21-25, 2018.
  6. “Between-class CCA for SSVEP based BCI”, The 7th International Brain-Computer Interface (BCI) Meeting, Pacific Grove, CA, May 21-25, 2018.
  7. “Change of brain functional connectivity associate with fatigue in SSVEP-BCI applications”, The 7th International Brain-Computer Interface (BCI) Meeting, Pacific Grove, CA, May 21-25, 2018.
  8. “Neurofeedback improves SSVEP-BCI performance on subject with both ‘high’ and ‘low’ performance”, The 7th International Brain-Computer Interface (BCI) Meeting, Pacific Grove, CA, May 21-25, 2018.
  9. “Adaptive Fourier decomposition based R-peak detection for noisy ECG signals”, The 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Jeju, Korea, July 11-15, 2017.
  10. “Online optimization of visual stimuli for reducing fatigue in SSVEP-based BCIs,” The 6th International Brain-Computer Interface (BCI) Meeting, Pacific Grove, CA, USA, May 30 – June 3, 2016.
  11. “Fatigue evaluation through EEG analysis using multi-scale Entropy in SSVEP-based BCIs,” The 6th International Brain-Computer Interface (BCI) Meeting, Pacific Grove, CA, USA, May 30 – June 3, 2016.
  12. “Frequency recognition based on wavelet-independent component analysis for SSVEP-based BCIs,” The 12th International Symposium on Neural Networks, ISNN 2015, Jeju Island, Korea, October 15-18, 2015. Also in X. Hu et al. (eds.): Advances in Neural Networks – ISNN 2015: Lecture Notes in Computer Science 9377, pp. 315-323, Springer International Publishing Switzerland 2015.
  13. “Fast basis searching method of adaptive Fourier decomposition based on Nelder-Mead algorithm for ECG signals,” The 12th International Symposium on Neural Networks, ISNN 2015, Jeju Island, Korea, October 15-18, 2015. Also in X. Hu et al. (eds.): Advances in Neural Networks – ISNN 2015: Lecture Notes in Computer Science 9377, pp. 305-314, Springer International Publishing Switzerland 2015.
  14. “Beta/theta ratio neurofeedback training effects on the spectral topography of EEG,” in the Proceedings of the 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Milan, Aug. 23-29, 2015.
  15. “A multi-channel SSVEP-based BCI for computer games with analogue control,” 2015 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications, Shenzhen, China, June 12-14, 2015.
  16. “Reliability and sensitivity analysis on the center of pressure measures in healthy young adults using Nintendo Wii balance board,” 2015 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications, Shenzhen, China, June 12-14, 2015.
  17. “Adaptive Fourier decomposition approach for lung-heart sound separation,” 2015 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications, Shenzhen, China, June 12-14, 2015.
  18. “Beta/Theta neurofeedback training effects in physical balance of healthy people,” IUPESM World Congress on Medical Physics and Biomedical Engineering (IUPESM WC 2015), Toronto, Canada, June 7-12, 2015.
  19. “How mental strategy affects Beta/Theta neurofeedback training,” IUPESM World Congress on Medical Physics and Biomedical Engineering (IUPESM WC 2015), Toronto, Canada, June 7-12, 2015.
  20. “Time varying VEP evaluation as a prediction of vision fatigue using stimulated brain-computer interface,” in H. Lijenstrom (ed.) Advances in Cognitive Neurodynamics (IV), pp. 157-160, Springer Science + Business Media Dordrecht 2015.

Professional Affiliations

  • Senior Member, Institute of Electrical and Electronics Engineering (IEEE)
  • Senior Member, Chinese Society of Biomedical Engineering (CSBME)
  • Chair, Hong Kong – Macau Joint Chapter, The IEEE Engineering in Medicine and Biology Society (2017-).
  • Chairman of Board of Supervisors, Macau Society of Biomedical Engineering (MSBME) (2014-)

Contact Details

Faculty of Science and Technology
University of Macau, E11
Avenida da Universidade, Taipa,
Macau, China

Room: E11-3055
Telephone: (+853) 8822-4473
Fax: (+853) 8822-2426
Email: fwan