Dr Andrew John McDaid

BE (Hons), PhD

Associate Professor

In: Mechanical Engineering » Faculty of Engineering

Research | Current

Medical devices - design and control
Rehabilitation robotics and wearables
Artifical intelligence and machine learning
Functional electrical stimulation (FES) - Neuroprosthetics
Smart materials and soft robotics
Intelligent and adaptive control systems
Physiological control (EEG, HD-EMG)
Neuroscience and human motor control/learning
Gamification
Novel additive manufacturing for customised medical devices

Research currently funded by:

Health Research Council (HRC), RSNZ, MBIE, Callaghan Innovation, Auckland Medical Research Foundation (AMRF), Cure Kids, NZ Artifical Limb Service, US Office of Naval Research (ONR), Lottery Health Research Board, Ministry of Social Development, The University of Auckland

Teaching | Current

Director - Medical Devices & Technologies Program

ENGGEN770 - Medical Device Technologies

MECHENG736 - Biomechatronic Systems

MECHENG762 - Mechatronics Research Project

MECHENG322 - Control Systems

MECHENG312 - Sensors and Actuators

MECHENG201 - Electronics and Computing for Mechanical Engineers

Postgraduate supervision

PhD

ME (Research)

MEngSt (Medical Devices and Technolgies)

MEngSt (Mechanical Engineering)

Distinctions/Honours

RSNZ Rutherford Discovery Fellowship

UoA Early Career Research Excellence Award - 2015

AUEA Emerging Researcher Award - 2015

RSNZ Marsden Grant - 2014

Spark Ideas Challenge Winner - 2014

AMP 'Do Your Thing' Award - 2012

Best Student Paper Award, IEEE/ASME AIM2011 Conference

Responsibilities

Programme Director - Medical Devices & Technologies

Postgraduate Advisor (Research) - Mechanical Engineering

Outreach (incl schools liason) - Mechanical Engineering

Committees/Professional groups/Services

Faculty of Engineering Research Committee

Member IEEE

Member ASME

Selected publications and creative works (Research Outputs)

Jayaneththi, V. R., Aw, K., Sharma, M., Wen, J., Svirskis, D., & McDaid, A. J. (2019). Controlled transdermal drug delivery using a wireless magnetic microneedle patch: Preclinical device development. SENSORS AND ACTUATORS B-CHEMICAL, 29710.1016/j.snb.2019.126708
URL: http://hdl.handle.net/2292/48237
Other University of Auckland co-authors: Kean Aw, Manisha Sharma, Jingyuan Wen, Darren Svirskis
Dwivedi, A., Kwon, Y., McDaid, A. J., & Liarokapis, M. (2019). A Learning Scheme for EMG Based Decoding of Dexterous, In-Hand Manipulation Motions. IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society, 27 (10), 2205-2215. 10.1109/tnsre.2019.2936622
Other University of Auckland co-authors: Minas Liarokapis, Anany Dwivedi
Jayaneththi, V. R., Aw, K. C., & McDaid, A. J. (2019). Coupled magneto-mechanical modeling of non-linear ferromagnetic diaphragm systems. International Journal of Mechanical Sciences, 155, 360-369. 10.1016/j.ijmecsci.2019.03.003
URL: http://hdl.handle.net/2292/46882
Other University of Auckland co-authors: Kean Aw
Ward, S. H., Wiedemann, L., Stinear, J., Stinear, C., & McDaid, A. (2018). The effect of a novel gait retraining device on lower limb kinematics and muscle activation in healthy adults. Journal of biomechanics, 77, 183-189. 10.1016/j.jbiomech.2018.07.012
Other University of Auckland co-authors: James Stinear, Cathy Stinear
Hope, J., Vanholsbeeck, F., & McDaid, A. (2018). A model of electrical impedance tomography implemented in nerve-cuff for neural-prosthetics control. Physiological measurement, 39 (4)10.1088/1361-6579/aab73a
Other University of Auckland co-authors: Frederique Vanholsbeeck, James Hope
Jayaneththi, V. R., Viloria, J., Wiedemann, L. G., Jarrett, C., & McDaid, A. J. (2017). Robotic assessment of neuromuscular characteristics using musculoskeletal models: A pilot study. Computers in Biology and Medicine, 86, 82-89. 10.1016/j.compbiomed.2017.05.007
URL: http://hdl.handle.net/2292/46979
Jarrett, C., & McDaid, A. J. (2017). Robust control of a cable-driven soft exoskeleton joint for intrinsic human-robot interaction. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 25 (7), 976-986. 10.1109/TNSRE.2017.2676765
Jarrett, C., & McDaid, A. (2017). Virtual normalisation of physical impairment: A pilot study to evaluate motor learning in presence of physical impairment. Frontiers in Neuroscience, 1110.3389/fnins.2017.00101