Usman Rashid

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Research Fellow

Email: usman.rashid@aut.ac.nz

ORCID: ORCID logo https://orcid.org/0000-0002-1109-5493

Links to relevant web pages:

Academic appointments:

  • Research Fellow, Auckland University of Technology (2019 - ongoing)
  • Research Officer, Auckland University of Technology (2016 - 2019)

Qualifications:

  • PhD, Auckland University of Technology
  • MSc, Robotics and Intelligent Machines Engineering, National University of Sciences and Technology
  • BSc, Electrical Engineering, University of Engineering and Technology

Research interests:

Neuroengineering
Artificial Intelligence
Inferential Statistics
Control Systems

Professional activities:

Award, prize, fellowship, and scholarship

  • Best multidisciplinary oral presentation, Health and Rehabilitation Research Institute Symposium (2019)

Editorship, reviewing, examining, and judging

  • Reviewer, Electronics, ISSN 2079-9292, MDPI (2020)
  • Reviewer, Sensors, ISSN 1424-8220, MDPI (2020)
  • Reviewer, Journal of electromyography and kinesiology, ISSN : 1873-5711, Elsevier (2019 - ongoing)
  • Reviewer, Journal of neural engineering, ISSN : 1741-2552, IOPScience (2019)
  • Reviewer, IEEE Transactions on Neural Systems and Rehabilitation Engineering, ISSN : 1558-0210, IEEE (2019 - ongoing)
  • Reviewer, Therapeutic Advances in Neurological Disorders, ISSN : 1756-2864, SAGE. (2019)

Research outputs:

Journal articles

  • Olsen, S., Signal, N., Niazi, I. K., Rashid, U., Alder, G., Mawston, G., . . . Taylor, D. (2020). Peripheral electrical stimulation paired with movement-related cortical potentials improves isometric muscle strength and voluntary activation following stroke. Frontiers in Human Neuroscience, 14. doi:10.3389/fnhum.2020.00156

  • Alder, G., Signal, N., Rashid, U., Olsen, S., Niazi, I. K., & Taylor, D. (2020). Intra- and inter-rater reliability of manual feature extraction methods in movement related cortical potential analysis. Sensors, 20(8). doi:10.3390/s20082427

  • Rashid, U., Niazi, I. K., Jochumsen, M., Krol, L. R., Signal, N., & Taylor, D. (2019). Automated labeling of movement- related cortical potentials using segmented regression. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 27(6), 1282-1291. doi:10.1109/TNSRE.2019.2913880

  • Jochumsen, M., Navid, M. S., Rashid, U., Haavik, H., & Niazi, I. K. (2019). EMG- versus EEG-triggered electrical stimulation for inducing corticospinal plasticity. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 27(9), 1901-1908. doi:10.1109/tnsre.2019.2932104

  • Rashid, U., Niazi, I. K., Signal, N., Farina, D., & Taylor, D. (2019). Optimal automatic detection of muscle activation intervals. Journal of Electromyography and Kinesiology, 48, 103-111. doi:10.1016/j.jelekin.2019.06.010

  • Jochumsen, M., Navid, M. S., Nedergaard, R. W., Signal, N., Rashid, U., Hassan, A., . . . Niazi, I. K. (2019). Self-paced online vs. cue-based offline brain-computer interfaces for inducing neural plasticity. Brain Sciences, 9(6). doi:10.3390/brainsci9060127

  • Rashid, U., Kumari, N., Taylor, D., David, T., & Signal, N. (2019). Gait event anomaly detection and correction during a split-belt treadmill task. IEEE Access, 7, 68469-68478. doi:10.1109/ACCESS.2019.2918559

  • Rashid, U., Niazi, I. K., Signal, N., & Taylor, D. (2018). An EEG experimental study evaluating the performance of Texas instruments ADS1299. Sensors (Switzerland), 18(11). doi:10.3390/s18113721

  • Jochumsen, M., Cremoux, S., Robinault, L., Lauber, J., Arceo, J. C., Navid, M. S., . . . Niazi, I. K. (2018). Investigation of optimal afferent feedback modality for inducing neural plasticity with a self-paced brain-computer interface. Sensors (Switzerland), 18(11). doi:10.3390/s18113761

  • Jamil, M., Rashid, U., Arshad, R., Khan, M. N., Gilani, S. O., & Ayaz, Y. (2015). Robust Repetitive Current Control of Two-Level Utility-Connected Converter using LCL Filter. Arabian Journal for Science and Engineering, 40(9), 2653-2670. doi:10.1007/s13369-015-1759-x

Conference contributions

  • Olsen, S., Signal, N., Niazi, I., Mawston, G., Alder, G., Rashid, U., & Taylor, D. (2019). Paired associative stimulation delivered by pairing movement-related cortical potentials with peripheral electrical stimulation improves voluntary activation in people with stroke. In European Congress of NeuroRehabilitation. Budapest.

  • Kumari, N., Taylor, D., Rashid, U., Vandal, A., Smith, P. F., & Signal, N. (2019). Can cerebellar transcranial direct current stimulation influence motor learning in healthy adults?. In K. Hillman (Ed.), Proceedings of the 37th International Australasian Winter Conference on Brain Research, 2019 (pp. 66). Queenstown. Retrieved from https://www.otago.ac.nz/awcbr/otago717176.pdf

  • Rashid, U., Signal, N., Niazi, I. K., & Taylor, D. (2019). footpress: An open-source MATLAB toolbox for analysis of pedobarography data. In Converging clinical and engineering research on neurorehabilitation III: Proceedings of the 4th International Conference on NeuroRehabilitation (ICNR2018) Vol. 21 (pp. 361-364). Pisa. doi:10.1007/978-3-030-01845-0_72

  • Rashid, U., & Jamil, M. (2016). Design of higher order repetitive controller for non minimum phase plants. In Proceedings of the American Control Conference Vol. 2016-July (pp. 7510-7515). doi:10.1109/ACC.2016.7526859

  • Rashid, U., Jamil, M., Gillani, S. O., & Niazi, I. K. (2015). LQR based training of adaptive neuro-fuzzy controller. : 25th Italian Workshop on Neural Networks, WIRN, 20-22 May 2015, Salerno, Italy. Retrieved from http://www.wirn2015.polito.it/program.html

  • Jamil, M., Arshad, R., Rashid, U., Ayaz, Y., & Khan, M. N. (2014). Design and analysis of repetitive controllers for grid connected inverter considering plant bandwidth for interfacing renewable energy sources. In 3rd International Conference on Renewable Energy Research and Applications, ICRERA 2014 (pp. 468-473). doi:10.1109/ICRERA.2014.7016429

Reports

  • Alder, G., Signal, N., Taylor, D., Niazi, I., Rashid, U., Brebner, S., . . . Alsmefer, F. (2017). Rehabilitation Innovation Team, C-Prize Wearables Competition Team Journal. Auckland, New Zealand. Retrieved from https://www.cprize.nz/lab-books/rehab-innovation

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